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Robust Decentralized Authentication in Peer-to-peer, Social, and Ad-hoc Networks 4 May 2009
Speaker: Vivek Pathak (Rutgers)Time: Monday, May 4, 2PM
Location: Babbio 221
Host: Philippos Mordohai
Abstract:
Authentication has traditionally been done either in a decentralized manner with human assistance or automatically through a centralized security infrastructure. In the security infrastructure approach, a central trusted authority takes on the responsibility of authenticating participants within its domain of control. While the security infrastructure approach works well in traditional organizations, it does not address the needs of open membership systems.
We propose automatic decentralized authentication mechanisms for peer-to-peer networks, social networks, and ad-hoc networks. Our byzantine fault tolerant public-key authentication protocol (BPKA) provides decentralized authentication to peer-to-peer systems with honest majority. Authentication is done over an insecure asynchronous network without using trusted third parties or human input. We also authenticate public keys in the email environment through our social-group key authentication protocol (SGKA). The protocol provides end-to-end authentication at the email client without using infrastructure or centralized authorities. Finally, location authentication in ad-hoc networks is proposed through our geographical secure path routing protocol (GSPR). The protocol authenticates geographic locations of anonymous nodes in order to provide location authentication and anonymity simultaneously.
Bio:
Vivek Pathak obtained the Ph.D. degree in Computer Science from Rutgers University in 2008. The focus of his research was on securing peer-to-peer, socially networked, and ad-hoc systems. The title of his dissertation was Robust Decentralized Authentication for Public Keys and Geographic Location. His research interests include infrastructure free security and ecommerce for decentralized systems, social networks, and the Internet.
Vivek Pathak is currently working for Ask.com (http://www.ask.com/) as the technical product manager responsible for web search. He has previously worked in software engineering roles for Ask.com and i2 technologies. He also has the B. Tech. degree in Aerospace Engineering from the Indian Institute of Technology, Bombay, and the M.B.A. degree from New York University. More information can be found at http://paul.rutgers.edu/~vpathak.
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Machine Learning with Graphs and Matchings 27 Apr 2009
Speaker: Tony Jebara, Columbia UniversityTime: Monday, April 27, 2PM
Location: Babbio 221
Host: Philippos Mordohai
Abstract:
Many machine learning problems on data can naturally be formulated as problems on graphs. For example, dimensionality reduction and visualization are related to graph embedding. Given a sparse graph between N high-dimensional data nodes, how do we faithfully embed it in low dimension? We present an algorithm that improves dimensionality reduction by extending semidefinite embedding methods. But, given only a dataset of N samples, how do we construct a sparse graph in the first place? The space to explore is daunting with 2^(N2) graphs to choose from yet two interesting subfamilies are tractable: matchings and b-matchings. By placing distributions over matchings and using loopy belief propagation, we efficiently infer the optimal graph. Matching not only has intriguing algebraic properties, it also leads to improvements in graph reconstruction, graph embedding, graph labeling, and graph partitioning. We show results on text, network and image data. Time permitting, we will show results on location data from millions of tracked mobile phone users which lets us discover patterns of human behavior, networks of places and networks of people.
Bio:
Tony Jebara is Associate Professor of Computer Science at Columbia University and director of the Columbia Machine Learning Laboratory. His research intersects computer science and statistics to develop new frameworks for learning from data with applications in vision, networks, spatio-temporal data, and text. Tony is also co-founder of Sense Networks. He has published over 50 peer-reviewed papers in conferences and journals including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is the author of the book Machine Learning: Discriminative and Generative. Tony is the recipient of the Career award from the National Science Foundation and has also received honors for his papers from the International Conference on Machine Learning and the Pattern Recognition Society. Tony's research has been featured on television (ABC, BBC, New York One, TechTV, etc.) as well as in the popular press (New York Times, Slash Dot, Wired, Scientific American, Newsweek, etc.). He obtained his PhD in 2002 from MIT. Recently, Esquire magazine named him one of their Best and Brightest of 2008. Tony's lab is supported in part by the NSF, CIA, NSA, DHS, and ONR .
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Making Fake Skin (and other things) Look Real 13 Apr 2009
Speaker: Craig Donner, Columbia UniversityTime: Monday, April 13, 2PM
Location: Babbio 221
Host: Philippos Mordohai
Abstract:
Natural materials such as juice, leaves, marble, and skin have a complex interaction with light. Light refracts into such materials and scatters many times before exiting, and this subsurface scatteringof light has a profound impact on their appearance. In this talk, I will present recent advances in computer graphics for making images and acquiring the appearance of natural materials, using examples including liquids, leaves, and especially human skin.
Bio:
Craig Donner is currently a Postdoctoral Research Scientist at Columbia University. His core research interests are appearance modeling and global illumination in the context of photorealistic image synthesis, as well as the acquisition and modeling of light transport in complex materials. His work is now used in the film, game, and even cosmetics industries. Craig received his doctorate at the University of California, San Diego, investigating the scattering of light in translucent materials.
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Distributed Control of Networked Robots and Systems 6 Apr 2009
Speaker: Michael Zavlanos, University of PennsylvaniaTime: Monday, April 6, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Philippos Mordohai
Abstract:
The field of robotics is evolving from single monolithic robots to teams of small but interconnected robots achieving global objectives using local coordination. Coordinated missions for teams of mobile robots include coordinated estimation, surveillance, and coverage, coordinated satellite alignment and synchronization, as well as distributed placement and assignment in creating desirable team structures. The fundamental challenge in such problems is the design of local rules, such as distributed controllers and estimators, which by local coordination give rise to the desired global objectives.
In this talk, I will first present the first distributed, scalable, and verifiable algorithm that allows teams of robots to dynamically create any desired structure, characterized by the relative locations of the robots in it, using local coordination rules. This is achieved using a combination of multi-destination potential fields and assignment coordination protocols. I will then address the problem of maintaining connectivity in robotic networks, where the robot nodes are mobile. The proposed solution is not only the first distributed solution to this problem, but has been both theoretically and experimentally verified, and can be composed with other objectives to give robotic structures that can adapt to environmental changes and handle node failures.
Bio:
Michael M. Zavlanos received the Diploma in mechanical engineering from the National Technical University of Athens, Athens, Greece, in 2002 and the M.S.E. and Ph.D. degrees in electrical and systems engineering from the University of Pennsylvania, Philadelphia, in 2005 and 2008, respectively. He is currently a Postdoctoral Researcher with the Department of Electrical and Systems Engineering, University of Pennsylvania. His current research interests include the areas of distributed control systems, networked systems, and hybrid dynamical systems with applications to robotics, sensor networks, and biomolecular networks. Dr. Zavlanos
was a finalist of the Best Student Paper Award at the 45th IEEE Conference on Decision and Control in 2006.
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Civitas: Toward a Secure Voting System 30 Mar 2009
Speaker: Michael Clarkson, CornellTime: Monday, March 30, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: David Naumann
Abstract:
Voting systems are hard to make trustworthy because they have strong, conflicting security requirements: Voters must be convinced that their votes are tallied correctly, while the secrecy of those votes must also be maintained---even when someone tries to buy votes or physically coerce voters. This talk presents Civitas, an electronic remote voting system satisfying these requirements and offering assurance through both cryptographic security proofs and information-flow analysis.
Bio:
Michael Clarkson is a PhD candidate in the Department of Computer Science at Cornell University. For more information, please visit http://www.cs.cornell.edu/people/clarkson/
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Detection, Tracking and Registration in 3D Radiology Image Analysis 23 Mar 2009
Speaker: Lin Yang, RutgersTime: Monday, March 23, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Philippos Mordohai
Abstract:
In this talk, we will describe a robust, fast and accurate 3D object detection/tracking algorithm which is developed for the 3D echocardiography. According to our knowledge, this is the first study reporting fast and reliable 3D ultrasound tracking of the left ventricle on a very large dataset, which contains 1143 3D volumetric data. From our research we report that collaborative trackers increased the tracking accuracy dramatically. The final accurate results are achieved by applying the motion priors using one-step forward prediction on the manifold. The robustness to complex background and weak edges come from the learned discriminative detectors and boundary classifiers, while the temporal consistence is preserved by template tracker. Instead of building specific models for heart, all the major steps in our algorithm are based on learning. Our proposed algorithm is therefore general enough to be extended to other 2D/3D medical image object detection/tracking problems.
We will also present a new method for fast and robust image registration combining landmark and region based techniques. The algorithm is completely unsupervised and computationally efficient. Due to a relatively small number of landmarks, the method runs faster than many existing nonlinear registration algorithms reported in the literature, such as B-Spline based image registration and the Demon's algorithm. The method can also handle large transformation and deformation while still providing good registration results. We will also explain how to implement the algorithm in a multi-core platform, the IBM Cell Broadband Engine.
Bio:
Lin Yang received his Ph. D. degree in the department of Electrical and Computer Engineering, Rutgers University in 2009.
He will serve as an assistant professor in the department of Radiology in the University of Medicine and Dentistry of New Jersey and also hold a joint assistant professor appointment in the department of Biomedical Engineering in Rutgers in August, 2009. His research interests include different areas of medical image analysis, computer vision and machine learning. He is working on the design and development of content-based image and video retrieval and 2D/3D medical image analysis including detection, segmentation, registration and tracking. He has already published over 20 peer-reviewed articles. For detailed information, please visit http://www.eden.rutgers.edu/~linyang/.
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Efficient Comparison of 3D Models for Shape Retrieval 16 Mar 2009
Speaker: Ameesh Makadia, Google ResearchTime: Monday, March 16, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Philippos Mordohai
Abstract:
The ability to perform fast and accurate retrieval from a database of 3D models is becoming a growing necessity as the number of models in circulation is rapidly increasing. Most search engines, built around text-based search, fail to leverage shape content, which often leads to search results of limited success and applicability. In this work we explore the problem of retrieval from large databases of 3D models
that are queried by example models.
At the core of this retrieval task is the fundamental challenge of defining and evaluating similarity between 3D shapes. I will present a method for comparing models that is based on a visual representation. Specifically, we will consider collections of rendered images from numerous viewpoints surrounding the model. While rendered images provide sufficiently discriminating information, similarity computation requires consideration of all possible rotational alignments between models. The main novelty is in the realization that the comparison of visual representations can be expressed as a correlation of spherical functions, and we will show how evaluation can be performed efficiently using techniques from spherical signal processing. Qualitative and quantitative retrieval results will be shown on a large web dataset of over 1 million 3D models.
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Property Verification of an Electronic Payment System: EP2 2 Mar 2009
Speaker: Temesghen Kahsai, Dep. of Computer Science, Swansea University, UKTime: Monday, March 2, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: David Naumann
Abstract:
The EP2 system is an electronic payment system and it stands for 'EFT/POS 2000' short for 'Electronic Fund Transfer / Point of Service 2000', is a joint project established by a number of (mainly Swiss) financial institutes in order to define the infrastructure for credit, debit and electronic purse terminals in Switzerland (www.eftpos2000.ch). The system consists of seven autonomous entities and they are centered around an EP2 Terminal. These entities communicate with the Terminal and, to a certain extent, with one another via XML-messages in a fixed format. Each component is a reactive system defined by a number of use cases. The EP2 Specification consists of 12 documents, each of which describe the different components or some aspect common to the components.
In this talk I will show the modeling of the EP2 specification in the formal specification language CSP-CASL [2]. CSP-CASL allows to formalize computational system in a combined algebraic / process algebraic notation. In [1] we have developed a proof method for various refinement notions of CSP-CASL. Using such proof method we verify the refinement of the different level of the EP2 specification. We also verify properties such as deadlock and livelock freedom using an interactive theorem prover.
References:
[1] T. Kahsai and M. Roggenbach. "Property preserving refinement for CSP-CASL". In A.Corradini and U. Montanari. Recent Trends in Algebraic Development Techniques. Springer-Verlang. To appear.
[2] M. Roggenbach. "CSP-CASL -- A new integration of process algebra and algebraic specification" Theoretical Computer Science, 354:42-71. 2006
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Controlling Sensors through Physics: some Ideas for the well-founded Control of Mobile Sensor Networks 23 Feb 2009
Speaker: Simon Dobson, UCD Dublin IETime: Monday, Feb 23, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Dominic Duggan
Abstract:
Mobile sensors are an attractive proposition for environmental sensing, but pose significant engineering problems. Not least amongst these is the need to match the behaviour of the sensor platform to the physical environment in which it operates. We present initial work on using models of physical processes to generate models for autonomic control, and speculate that these can be used to improve the confidence we can place in sensed data.
Bio:
Simon Dobson has a research career spanning over fifteen years in academia, government and industry. His research centres around adaptive pervasive computing and novel programming techniques, addressing both theory and practice and being supported by an extensive record of published work (including papers in CACM, TAAS, JPDC, EHCI and ECOOP) and primary authorship on grants worth over EUR 3M (and further involvements grants worth over EUR 28M) feeding around EUR 1.5M directly into his own current research programme. His expertise is widely recognised internationally: he serves on the steering or programme committees of many international conferences and workshops including PMCJ, PERVASIVE, AN, ICAC, ICOST, ECOOP, SAPIR, MUCS and MPAC; is a reviewer for journals including ACM Transactions on Autonomous and Adaptive Systems, SOFTWARE - Practice and Experience, and IEEE Communications; has been an invited editor for special issues of Computer Networks, IJIPT and JNSM; and participates in a number of EU strategic workshops and working groups. He is National Director for the European Research Consortium for Informatics and Mathematics, a board member of the Autonomic Communication Forum (at which he chairs the semantics working group), and a member of the IBEC/ICT Ireland standing committee on academic/industrial research and development. As a co-founder and CEO of a research-led start-up company he has experience in steering basic research to commercialisation. He holds a BSc and DPhil in computer science, is a Chartered Engineer and Chartered IT Professional, and member of the BCS, IEEE and ACM.
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Efficient Image Search and Retrieval using Compact Binary Codes 9 Feb 2009
Speaker: Rob Fergus, NYUTime: Monday, Feb 9, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Philippos Mordohai
Abstract:
The vast majority of information on the Internet is in visual form, yet we currently lack effective methods for searching images or videos. Existing strategies rely mainly on textual cues which give impoverished and often misleading descriptions of the visual content. A key part of the challenge is that the search needs to be highly efficient due to the scale of the problem: Google's Image Search indexes around 10 billion images, while YouTube holds petabytes of video data and receives 10 hours of new content each minute.
In my talk I will describe methods for efficiently searching Internet-sized image databases. Using machine learning techniques, we represent each image with a compact binary code, at most a few hundred *bits* in length, which preserves the original neighborhood structure of images in the database. Our scheme is able to perform real-time search on millions of images using a standard PC, obtaining a retrieval performance comparable with that of more complex descriptors, despite being many orders of magnitude faster.
Joint work with: Antonio Torralba (MIT), Yair Weiss (Hebrew University).
Bio:
Rob Fergus is currently an Assistant Professor of Computer Science at the Courant Institute of Mathematical Sciences, New York University. Originally from the UK, Fergus did his undergraduate degree in Electrical Engineering at the University of Cambridge. He then did a Masters in Electrical Engineering with Prof. Pietro Perona at Caltech, before completing a PhD with Prof. Andrew Zisserman at the University of Oxford. Before coming to NYU, Fergus spent two years as a post-doc in the Computer Science and Artificial Intelligence Lab (CSAIL) at MIT, working with Prof. William Freeman. In 2003, he and his co-authors were awarded the CVPR Best Paper Prize. In 2005, his PhD thesis won the prize for the best Computer Science thesis in the UK.
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Developing Secure Software - Builders vs. Breakers 2 Feb 2009
Speaker: Boaz Gelbord, Wireless GenerationTime: Monday, Feb 2, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Wendy Hui Wang
Abstract:
What is the best way to produce secure code - through Building or Breaking? The Building school holds that secure software can only result from security-trained developers who incorporate security principles into their coding. On the other hand, many software shops are built around a Breaking model - build software as fast as possible and then try to have experts break it at some point in the software development lifecycle.
In this talk we examine this issue in the wider context of enterprise security risk management and by looking at particular web application vulnerabilities. Topics we will cover include: - An overview of enterprise security risks
- Compliance driven security measures
- The commoditization of network security and increased importance of application security risk
- Resource allocation
- Specific challenges of securing web applications
- Analysis of vulnerability lists like the OWASP Top 10 and CWE/SANS Top 25
Bio:
Dr. Boaz Gelbord is the Executive Director of Information Security at Wireless Generation, a New York based educational technology company and a leading provider of assessment tools in thousands of classrooms across the country.
Boaz began his career as a cryptologist at KPN Royal Dutch Telecom, where he led numerous security projects and authored 12 patents relating to information security. His work on privacy enhancing technologies at KPN earned several international awards and led to his designation as one of "Europe's Tech Stars" by the Wall Street Journal Europe. Boaz was appointed as an independent expert to the eEurope 2005 Advisory Group, a high level committee that advised the European Commission on Internet policy. He was also an appointed expert in several ETSI (European Telecommunications Standards Institute) Specialist Task Forces, including the Secure Algorithm Group of Experts that standardized the GSM and UMTS encryption algorithms. Boaz taught information security for several years as an Associate Professor at the University of Leiden in the Netherlands.
Boaz was one of the founders of the European Network and Information Security Agency, the official EU body responsible for information security where he headed the Security Technologies Unit. Boaz has
chaired the program and steering committees of several leading international security conferences, including being the co-Chairman of the Steering Committee of the ISSE 2005 conference, Europe's largest
independent information security conference.
Boaz was also the first Director of Information Security at the New School in New York City where he introduced and implemented a comprehensive information security program. He holds a BSc in mathematics from the University of Calgary, an MSc in mathematics from the University of Toronto, and a PhD in mathematics from the Technion in Israel. He hold the CISA and CISSP certifications and is a frequently invited keynote speaker on information security and privacy issues. In the past he has presented keynote addresses at ITU, CEN, ETSI, and East West Institute conferences.
Boaz blogs on information security at www.boazgelbord.com
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Controlling Timing Channels in Multithreaded Programs 25 Nov 2008
Speaker: Alejandro RussoChalmers University of Technology, Gothenburg, Sweden
Time: Monday, Dec 1, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Dave Naumann
Abstract:
The problem of controlling information flow in multithreaded programs remains an important open challenge.A major difficulty for tracking information flow in concurrent programs is due to the internal timing covert channel. Information is leaked via this channel when secrets affect the timing behavior of a thread, which, via the scheduler, affects the interleaving of public events. This channel is particularly dangerous because, in contrast to external timing, the attacker does not need to observe the actual execution time of programs. This talk introduces a novel treatment of the interaction between threads and the scheduler. As a result, a permissive security specification and a compositional security type system are obtained. The type system guarantees security for a wide class of schedulers and provides a flexible treatment of dynamic thread creation and synchronization. The approach relies on the modification of the scheduler in the run-time environment. In some scenarios, the modification of the run-time environment might not be an acceptable requirement. For such scenarios, we briefly present two transformations that eliminate the need for modifying the scheduler while avoiding internal timing leaks. The first transformation is given for programs running under cooperative schedulers. It states that threads must not yield control inside of computations that branch on secrets. The second transformation closes internal timing channel when the scheduler is preemptive and behaves as round-robin. It spawns dedicated threads, whenever computation may affect secrets, and carefully synchronizes them.
Talk based on Alejandro Russo's PhD thesis available at http://www.cs.chalmers.se/~russo/russothesis.pdf
Talk based on Alejandro Russo's PhD thesis available at http://www.cs.chalmers.se/~russo/russothesis.pdf
Short Bio:
Alejandro Russo is a PhD Student under the supervision of Andrei Safelfeld at the Chalmers University of Technology in Sweden. Alejandro will defend his PhD thesis this year on November 13th. Prior to establishing in Chalmers, Alejandro spent a few months as a research assistant at the Stevens Institute of Technology in USA. Before that, He obtained the degree of Licentiate in Computer Science (five years degree equivalent to master) at the National University of Rosario in Argentina.
Alejandro main research area is language-based security, while programming languages and computer security are his general research interests. He has been working with preservation of confidentiality of data in concurrent languages as well as the design of libraries to guarantee security policies in functional languages.
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Authenticated Communication in Dynamic Federated Systems 23 Nov 2008
Speaker: Nelly FazioDepartment of Computer Science
City University of New York
City College and Graduate Center
Time: Monday, Nov 24, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Wendy Hui Wang
Abstract:
System F6 is a DARPA program to increase the value and flexibility of future satellite missions. To this aim, the F6 initiative suggests replacing the monolithic architecture of current spacecrafts with a cluster of small specialized satellites. Realizing this vision of a collaborating federation of small satellites requires developing a number of novel wireless communication and distributed computing technologies.
In this talk, I will focus on the problem of authenticated communication between the cluster of satellites and external (e.g., other spacecrafts, the ground station, etc.). Our approach extends the conventional threshold signature paradigm by additionally supporting membership changes to the federated system: While traditional systems split the signature key only among an a priori fixed group, our scheme allows evolving membership by repeatedly and securely (re)distributing key shares from the old cluster to the new set of agents. This is realized without resorting to system re-initialization nor relying on a central trusted dealer.
Biography:
Nelly Fazio joined the Department of Computer Science at the City College and the Graduate Center of the City University of New York as an Assistant Professor in September 2008. Since then, she is also a member of the research Center for Algorithms and Interactive Scientific Software (CAISS) at City College. Before joining CUNY, she was a visiting research scientist in the Security group at IBM T.J. Watson Research center, working on security issues of decentralized environments such as mobile ad-hoc networks (MANETs) and sensor networks. Prior to that, she was a postdoctoral researcher in the Content Protection group at IBM Almaden Research Center, where she conducted research on advanced cryptographic key management and tracing technologies.
In this talk, I will focus on the problem of authenticated communication between the cluster of satellites and external (e.g., other spacecrafts, the ground station, etc.). Our approach extends the conventional threshold signature paradigm by additionally supporting membership changes to the federated system: While traditional systems split the signature key only among an a priori fixed group, our scheme allows evolving membership by repeatedly and securely (re)distributing key shares from the old cluster to the new set of agents. This is realized without resorting to system re-initialization nor relying on a central trusted dealer.
Biography:
Nelly Fazio joined the Department of Computer Science at the City College and the Graduate Center of the City University of New York as an Assistant Professor in September 2008. Since then, she is also a member of the research Center for Algorithms and Interactive Scientific Software (CAISS) at City College. Before joining CUNY, she was a visiting research scientist in the Security group at IBM T.J. Watson Research center, working on security issues of decentralized environments such as mobile ad-hoc networks (MANETs) and sensor networks. Prior to that, she was a postdoctoral researcher in the Content Protection group at IBM Almaden Research Center, where she conducted research on advanced cryptographic key management and tracing technologies.
Dr. Fazio's research interests are in cryptography and information security, with a focus on digital content protection. She earned her M.Sc.('03) and Ph.D.('06) in Computer Science from New York University. During her studies, she also conducted research at Stanford University, Ecole Normale Superieure (France) and Aarhus University (Denmark). In 2003, she was awarded the NYU CIMS Sandra Bleistein prize, for "notable achievement by a woman in Applied Mathematics or Computer Science." Her Ph.D. thesis was nominated with honorable mention for the NYU J. Fabri prize, awarded yearly for the "most outstanding dissertation in Computer Science."
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Socially-Aware Recommendations in Collaborative Tagging Sites 23 Nov 2008
Speaker: Sihem Amer-YahiaSenior Research Scientist, Yahoo! Research - NYC
Time: Monday, Nov 17, 2PM
Location: Babbio 221, Stevens Institute of Technology
Host: Wendy Hui Wang
Abstract:
Collaborative tagging sites constitute a unique opportunity for leveraging implicit and explicit social ties in search and recommendations. This talk describes our work in the context of Royal Jelly, a platform for socially-aware recommendations in collaborative tagging sites. The key aspects of RJ are search over recommendations, topic derivation from tags, efficient recommendation algorithms and diversity in recommendations. We describe some of our solutions in that space and an overview of the challenges ahead.
Bio:
Sihem Amer-Yahia is a Senior Research Scientist at Yahoo! Research in NYC. Her interests are at the intersection of databases, search and recommendations in social content sites. Before that, she spent 7 years at AT&T Labs in NJ, working on XML query optimization and XML full-text search. Sihem is an editor of the XML full-text language documents recommended by the W3C. This year, she is on the editorial board of the Springer Encyclopedia of Database Systems as an editor of the XML entry, she also edited the Data Engineering Bulletin special issue on databases, search and recommendations and she is chairing the database track of CIKM 2008.
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PhotoSketch: Photo-Centric Urban 3D Modeling Tool 6 Nov 2008
Prof. George Wolberg
Department of Computer Science
City College of New York
New York, NY 10031
Monday, Nov 10, 2PM
Babbio 221, Stevens Institute of Technology
Department of Computer Science
City College of New York
New York, NY 10031
Monday, Nov 10, 2PM
Babbio 221, Stevens Institute of Technology
Abstract:
Geospatial navigation tools such as Google Earth and Microsoft Virtual Earth are exceedingly popular applications for exploring massive datasets. Their explosive growth provides impetus for photorealistic 3D modeling of urban scenes. Although laser range scanners are traditional sources for detailed 3D models of existing structures, they are prohibitively expensive and generate heavyweight models that are not appropriate for the streaming data that these navigation applications leverage. Instead, lightweight models as produced by photogrammetry tools are better suited for this domain. Unfortunately, photogrammetry requires skilled users for manual camera calibration and complex modeling processes. This makes laser scanning and photogrammetry unsuitable for average consumers equipped with ordinary cameras.
This talk presents the virtues of combining computer vision techniques and photogrammetry to simplify the 3D modeling workflow. The contribution of this work is that it merges the benefits of automatic feature extraction, multiview geometry, an intuitive sketching interface, and dynamic texture mapping to produce lightweight photorealistic 3D models of buildings. Dynamic texture mapping is key to our interactive photo-centric 3D modeling tool whereby the models are edited to best match the projected images. We present results from experiments in urban scenes.
Bio:
Dr. George Wolberg is Professor of Computer Science at the City College of New York / CUNY. He received the B.S. and M.S. degrees in Electrical Engineering from Cooper Union in 1985, and the Ph.D. degree in Computer Science from Columbia University in 1990. He has published widely in image processing, computer graphics, and computer vision journals and conferences, and holds five U.S. patents. He is the author of "Digital Image Warping," (IEEE Computer Society Press, 1990), the first comprehensive monograph on warping and morphing. Prof. Wolberg is the recipient of the Mayor's Award for Excellence in Science and Technology (awarded by Mayor Giuliani in 2000), a CCNY Outstanding Teaching Award, and an NSF Presidential Young Investigator Award. He is a Senior Member of the Institute of Electrical and Electronic Engineers. His research interests include image processing, computer graphics, and computer vision.
Geospatial navigation tools such as Google Earth and Microsoft Virtual Earth are exceedingly popular applications for exploring massive datasets. Their explosive growth provides impetus for photorealistic 3D modeling of urban scenes. Although laser range scanners are traditional sources for detailed 3D models of existing structures, they are prohibitively expensive and generate heavyweight models that are not appropriate for the streaming data that these navigation applications leverage. Instead, lightweight models as produced by photogrammetry tools are better suited for this domain. Unfortunately, photogrammetry requires skilled users for manual camera calibration and complex modeling processes. This makes laser scanning and photogrammetry unsuitable for average consumers equipped with ordinary cameras.
This talk presents the virtues of combining computer vision techniques and photogrammetry to simplify the 3D modeling workflow. The contribution of this work is that it merges the benefits of automatic feature extraction, multiview geometry, an intuitive sketching interface, and dynamic texture mapping to produce lightweight photorealistic 3D models of buildings. Dynamic texture mapping is key to our interactive photo-centric 3D modeling tool whereby the models are edited to best match the projected images. We present results from experiments in urban scenes.
Bio:
Dr. George Wolberg is Professor of Computer Science at the City College of New York / CUNY. He received the B.S. and M.S. degrees in Electrical Engineering from Cooper Union in 1985, and the Ph.D. degree in Computer Science from Columbia University in 1990. He has published widely in image processing, computer graphics, and computer vision journals and conferences, and holds five U.S. patents. He is the author of "Digital Image Warping," (IEEE Computer Society Press, 1990), the first comprehensive monograph on warping and morphing. Prof. Wolberg is the recipient of the Mayor's Award for Excellence in Science and Technology (awarded by Mayor Giuliani in 2000), a CCNY Outstanding Teaching Award, and an NSF Presidential Young Investigator Award. He is a Senior Member of the Institute of Electrical and Electronic Engineers. His research interests include image processing, computer graphics, and computer vision.
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Secure Detection of Policy Conflicts in a Multi-Organizational Collaborative Environment 30 Oct 2008
Prof. Basit ShafiqRutgers University
Monday, Nov 3, 2PM
Babbio 221, Stevens Institute of Technology
Abstract
In a collaborative environment, it is often the case that multiple autonomous organizations work together to accomplish a task. However, each collaborating organization may have its own predefined set of business policies, where some of them may be sensitive in nature. For example, as a policy, each organization taking part in the collaboration may have a negative list of organizations that are not allowed to do certain jobs due to conflict of interest or a similar reason. The challenge is to identify organizations capable of accomplishing the task without disclosing the sensitive policies to others and at the same time ensuring adherence to them. While this problem can be trivially solved if one assumes that there exists a trusted entity which has the knowledge of all the policies, we propose an approach that does not rely on a trusted third party. Our proposed approach essentially is capable of detecting policy conflicts, by employing commutative encryption. Through formal proof and analysis, we demonstrate that our approach is both secure and efficient.
BiographyDr. Basit Shafiq is a Research Assistant professor at the Center for Information Management, Integration and Connectivity (CIMIC), Rutgers University. He received his Ph. D. and M.S. in Electrical and Computer Engineering from Purdue University. His research interests include information systems security and privacy, access-control management in distributed systems, Web services composition and verification, ontologies, and distributed multimedia systems. His research work resulted in several publications in well-renowned journals, including, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information and System Security, IEEE Transactions on Multimedia, IEEE Computer, IEEE Communications Magazine, and Journal on Information and Computer Systems. Dr. Shafiq is actively involved in the development of a prototype decision support system for emergency management. This prototype focuses on providing an information sharing environment and a collaboration framework among the various government agencies and private organizations involved in emergency management activities. The research and development work of this project is sponsored by NSF and SAP Labs.
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Scaling up Cognitive Radio 25 Oct 2008
Prof. Joe Mitola,Stevens Institute of Technology
Monday, Oct 27, 2pm - 3pm
Babbio 221, Stevens Institute of Technology
Abstract
Cognitive radio technology improves spectrum efficiency via radio etiquettes in which a cognitive radio detects and avoids legacy radios as well as finding and using unoccupied spectrum dynamically. As the complexity of these air interfaces continues to increase, so does the cost of maintaining the related signal processing software. This talk presents results from an investigation into the application of Cartesian genetic programming to evolve signal processing software for signal detection, in lieu of writing the signal processing code manually. The software engineering process includes the reverse engineering of existing software via cognitive linguistics and topological space modeling of the existing and evolving code to achieve the consistency of code modularization needed for genetic programming in lieu of software engineering. Although at an early stage, this approach to software maintenance has some potentially interesting characteristics.
Bio
Dr. Joe Mitola is Distinguished Professor in the Charles V. Schafer School of Engineering and Science and in the School of Systems and Enterprises at Stevens Institute of Technology where his research interests include software defined and cognitive radio and the scaling up of cognition technologies to the enterprise level. Previously, Dr. Mitola was Chief Scientist of the DoD Federally Funded R&D Center of The MITRE Corporation; special assistant to the Director, DARPA; program manager at DARPA; and Chief Scientist of Electronic Systems of E-Systems (now Raytheon). He holds the BS in EE from Northeastern University, the MSE from the Johns Hopkins University; and the Licentiate and Doctorate in Teleinformatics from KTH, The Royal Institute of Technology, Stockholm.
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Computational Aided Engineering Work and Strategy at Honda R&D 22 Oct 2008
Thomas Ramsay
Honda R&D Americas, Inc.
Vehicle Research Division
Oct 23, 2008, 2PM-3PM
Babbio Room 110
Host: Quynh Dinh (quynh@cs.stevens.edu)
Honda R&D Americas, Inc.
Vehicle Research Division
Oct 23, 2008, 2PM-3PM
Babbio Room 110
Host: Quynh Dinh (quynh@cs.stevens.edu)
Abstract:
With the continual increase in computer speed and the shrinking of the business development cycle, computer aided engineering (CAE) has become more and more prominent and more useful in the automotive industry. From pedestrian safety to bumper performance to interior comfort to fuel economy, computational solutions are helping to evaluate and optimize more and more automotive designs. This talkwill outline the work at Honda R&D Americas in the area of advanced CAE, with special emphasis on computational fluid dynamics (CFD) modeling.
Biography:
Mr. Tom Ramsay is currently a senior engineer at Honda R&D Americas, Inc. in the Vehicle Research Division, where he is the technicalleader of computational fluid dynamics for most passenger cars and light trucks developed for the North American market. Before working at Honda R&D, Tom worked at Battelle Memorial Institute in the National Security Division where he did anti-armor research, munitions design and development, and counter-explosive and counter-narcotic research.
Tom received a Bachelor of Science and Masters of Science in Aeronautical Engineering, both from The Ohio State University in 1989 and 1993, respectively. Tom is active in AIAA and is currently serving as Chair of the Columbus Section and is a member of the Fluid Dynamics Technical Committee. Tom is also a member of SAE and belongs to the Vehicle Aerodynamics Forum Committee, Vehicle Configuration Committee, and the Motorsports Engineering Conference Committee. His interests lie in the areas of aerodynamics, fluid dynamics, physics, and mathematics and include wide ranging topics such as automotive aerodynamics, applied computational geometry, the physics and mathematics of sports, numerical and experimental correlation, and race car aerodynamics.
Tom received a Bachelor of Science and Masters of Science in Aeronautical Engineering, both from The Ohio State University in 1989 and 1993, respectively. Tom is active in AIAA and is currently serving as Chair of the Columbus Section and is a member of the Fluid Dynamics Technical Committee. Tom is also a member of SAE and belongs to the Vehicle Aerodynamics Forum Committee, Vehicle Configuration Committee, and the Motorsports Engineering Conference Committee. His interests lie in the areas of aerodynamics, fluid dynamics, physics, and mathematics and include wide ranging topics such as automotive aerodynamics, applied computational geometry, the physics and mathematics of sports, numerical and experimental correlation, and race car aerodynamics.
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The Role Mining Problem - A Formal Perspective 17 Oct 2008
Prof. Jaideep Vaidya
Rutgers University
Monday, Oct 20, 2pm - 3pm
Babbio 221, Stevens Institute of Technology
Abstract:
Role based access control is well accepted as the standard best practice for access control within applications and organizations. Role engineering, the task of defining roles and associating permissions to them, is essential to realize the full benefits of the role-based access control paradigm. The essential question is how to devise a complete and correct set of roles -- this depends on how you define goodness/interestingness (when is a role good/interesting?) We define the role mining problem (RMP) as the problem of discovering an optimal set of roles from existing user permissions. In addition to the above basic RMP, we introduce two different variations of the RMP, called the delta-approx RMP and the Minimal Noise RMP that have pragmatic implications. Our main contribution is to formally define RMP, analyze its theoretical bounds, and present heuristic solutions to find the optimal set of roles based on subset enumeration. We place this in the framework of matrix decomposition which is applicable to many other domains including text mining.
Bio:
Dr. Jaideep Vaidya is an Assistant Professor at Rutgers University. He received his Masters and Ph.D. at Purdue University and his Bachelors degree at the University of Mumbai. His research interests are in Data Mining, Privacy, Security, and Information Sharing. He has published over 30 papers in international conferences and archival journals, and has received two best paper awards from the premier conferences in data mining and databases. He is also the recipient of a NSF Career Award and is a member of the ACM, and the IEEE Computer Society.
Rutgers University
Monday, Oct 20, 2pm - 3pm
Babbio 221, Stevens Institute of Technology
Abstract:
Role based access control is well accepted as the standard best practice for access control within applications and organizations. Role engineering, the task of defining roles and associating permissions to them, is essential to realize the full benefits of the role-based access control paradigm. The essential question is how to devise a complete and correct set of roles -- this depends on how you define goodness/interestingness (when is a role good/interesting?) We define the role mining problem (RMP) as the problem of discovering an optimal set of roles from existing user permissions. In addition to the above basic RMP, we introduce two different variations of the RMP, called the delta-approx RMP and the Minimal Noise RMP that have pragmatic implications. Our main contribution is to formally define RMP, analyze its theoretical bounds, and present heuristic solutions to find the optimal set of roles based on subset enumeration. We place this in the framework of matrix decomposition which is applicable to many other domains including text mining.
Bio:
Dr. Jaideep Vaidya is an Assistant Professor at Rutgers University. He received his Masters and Ph.D. at Purdue University and his Bachelors degree at the University of Mumbai. His research interests are in Data Mining, Privacy, Security, and Information Sharing. He has published over 30 papers in international conferences and archival journals, and has received two best paper awards from the premier conferences in data mining and databases. He is also the recipient of a NSF Career Award and is a member of the ACM, and the IEEE Computer Society.
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Keystroke Authentication and Human-Behavior Driven Bot Detection 11 Oct 2008
Prof. Danfeng YaoRutgers University
Wednesday, Oct 15, 2008, 3PM-4PM
Babbio Room 110
Abstract:
Most of existing botnet detection solutions focuses on using the characteristic behaviors of botnets to identify malicious activities. We argue that there are intrinsic and fundamental differences between how human or a bot uses and reacts to a computer, which can be leveraged to distinguish human from bots and to detect infected hosts. We take the first step in formalizing and utilizing the human-centric anomaly detection approach to tackle botnet problems, namely, how to ensure a person's computer is not being stealthily used by a malicious bot.
We present our design and implementation of a remote authentication framework called TUBA thatcollects, extracts features, analyzes, andclassifies a computer owner's characteristic keystroke patterns. We collect keystroke data from a group of 20 human users on a set of carefully selected strings. We systematically carry out series of experiments to evaluate the performance of TUBA in classification under both human impersonations and simulated bot attacks by injecting fake keyboard events. Based on our studies, we find that high-dimensional keystroke dynamics features are a robust identification metric for behavior-based authentication. We also discover that certain keyboard event sequences are easy for human to complete, however, are extremely difficult for a bot (i.e., a program) to mimic due to the way a keyboard device and its driver are currently configured.
This is joint work with Deian Stefan (Cooper Union).
We present our design and implementation of a remote authentication framework called TUBA thatcollects, extracts features, analyzes, andclassifies a computer owner's characteristic keystroke patterns. We collect keystroke data from a group of 20 human users on a set of carefully selected strings. We systematically carry out series of experiments to evaluate the performance of TUBA in classification under both human impersonations and simulated bot attacks by injecting fake keyboard events. Based on our studies, we find that high-dimensional keystroke dynamics features are a robust identification metric for behavior-based authentication. We also discover that certain keyboard event sequences are easy for human to complete, however, are extremely difficult for a bot (i.e., a program) to mimic due to the way a keyboard device and its driver are currently configured.
This is joint work with Deian Stefan (Cooper Union).
Biography:
Danfeng Yao is an assistant professor in the Department of Computer Science at Rutgers University, New Brunswick. She received her Computer Science Ph.D. degree from Brown University. Her research interests are in information security and applied cryptography. Danfeng has more than 20 publications on security and applied cryptography. She won the Best Student Paper Award in ICICS 2006, and the Award for Technological Innovation from Brown in 2006. Danfeng has two U.S. patents pending for her work on identity management. She has interned in the Trusted Systems Lab at HP Labs, and visited CERIAS at Purdue University as a visiting scholar. She has been the reviewer for many security journals and recently served as a PC member in IFIP Trust Management '09, CollaborateCom '08, ACM Symposium on Applied Computing '08, International Conference on Security and Management '08, Workshop on Web 2.0 Trust '08.
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Optical Filtering Directly in the Scene 30 Sep 2008
Prof. Yves Jean (www.lehman.edu/faculty/yves)
City University of NY, Lehman College
Monday, Oct 6, 2:00PM
Babbio 221, Stevens Institute of Technology
City University of NY, Lehman College
Monday, Oct 6, 2:00PM
Babbio 221, Stevens Institute of Technology
Abstract:
Computer vision researchers have long sought algorithms for scene interpretation built upon detecting features in images that relate toscene composition. Yet much of the rich scene information is lost in the image formation process. A more powerful scheme would apply feature detection directly in the scene, measuring scene phenomena before the degradation and distortion of image formation. We will present a novel projector-camera system (along with new calibration techniques) that performs filter convolution in the actual 3D scene. The system produces an orthographic projection of filter images into the scene as controlled illumination. The projected filters are subjected to surface reflectance (BRDF) and scene composition; and the filter response is captured by camera pixels. Our results show that the class of finite-impulse response (FIR) filters is supported by this technique.
Bio:
Yves Jean is an Associate Professor of Computer Science at Lehman College. His research interests include Computer Vision and Computer Graphics. He has a PhD in Computer Science from the Georgia Institute of Technology (GVU Group) and a BS in Electrical Engineering from
Columbia University.
Columbia University.
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Fast Exact and Heuristic Methods for Role Minimization Problems 24 Sep 2008
Dr. William Horne,Secure Systems Lab, HP Labs, Princeton, NJ
Monday, September 29, 2:00PM
Babbio 221, Stevens Institute of Technology
Abstract:
We describe several new bottom-up approaches to problems in roleengineering for Role-Based Access Control (RBAC). The salient problems are all NP-complete, even to approximate, yet we find that in instances that arise in practice, these problems can be solved in minutes. We first consider role minimization, the process of finding a smallest collection of roles (a role is viewed as a collection of permissions) that can be used to implement a pre-existing user-to-permission relation. We introduce fast graph reductions that allow recovery of the optimum solution from the solution to a problem on a smaller input graph. These reductions either completely solve the problems on which we have tried them, or reduce the problem enough that we then find the the optimum solution with an exponential (in the worst case) method. We introduce lower bounds that are sharp for seven of nine test cases and are within 3% on the other two. We introduce and test a new approximation method that on average yields 2% more roles than the optimum, but is faster than our reduction method. We next consider the related problem of minimizing the number of connections between roles and users or permissions, and we develop effective heuristic methods for this problem as well. Finally, we propose a way to use a solution to the role minimization problem in order to implement a system in which users are assigned to groups of users (possibly overlapping, so a user may be part of several groups), which are granted roles, which confer permissions.
This paper appeared at SACMAT'08.
Biograph
Dr. Horne is a Research Manager in the Secure Systems Lab of HP Labs. He currently manages several research projects involving systems and network security and risk analytics. His research interests include systems security, cryptography, privacy, and tamper-resistant software. Prior to joining HP in 2002, he held research positions at InterTrust's STAR Lab and NEC Research Institute.
We describe several new bottom-up approaches to problems in roleengineering for Role-Based Access Control (RBAC). The salient problems are all NP-complete, even to approximate, yet we find that in instances that arise in practice, these problems can be solved in minutes. We first consider role minimization, the process of finding a smallest collection of roles (a role is viewed as a collection of permissions) that can be used to implement a pre-existing user-to-permission relation. We introduce fast graph reductions that allow recovery of the optimum solution from the solution to a problem on a smaller input graph. These reductions either completely solve the problems on which we have tried them, or reduce the problem enough that we then find the the optimum solution with an exponential (in the worst case) method. We introduce lower bounds that are sharp for seven of nine test cases and are within 3% on the other two. We introduce and test a new approximation method that on average yields 2% more roles than the optimum, but is faster than our reduction method. We next consider the related problem of minimizing the number of connections between roles and users or permissions, and we develop effective heuristic methods for this problem as well. Finally, we propose a way to use a solution to the role minimization problem in order to implement a system in which users are assigned to groups of users (possibly overlapping, so a user may be part of several groups), which are granted roles, which confer permissions.
This paper appeared at SACMAT'08.
Biograph
Dr. Horne is a Research Manager in the Secure Systems Lab of HP Labs. He currently manages several research projects involving systems and network security and risk analytics. His research interests include systems security, cryptography, privacy, and tamper-resistant software. Prior to joining HP in 2002, he held research positions at InterTrust's STAR Lab and NEC Research Institute.
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Remote Data Checking 21 Sep 2008
Prof. Reza Curtmola
New Jersey Institute of Technology, NJ
New Jersey Institute of Technology, NJ
Monday, September 22, 2008, 2:00PM
Babbio Room 221
Stevens Institute of Technology
Stevens Institute of Technology
Abstract:
Faced with cost and regulatory considerations, many companies are outsourcing the storage of their data to third parties. Outsourcing data storage achieves economies of scale for the management of storage and avoids the large initial investment to set up data enters. Recently, many such online archival systems have emerged from within the research and industrial communities.
In storage oursourcing, a client sends data to a server, which is required by contract to provide persistent archival of the data. Since the server is not trusted and may misbehave, the client typically retains a small piece of metadata which is used to verify the authenticity of the data upon its retrieval. The problem is that by the time data is retrieved, it might be already too late to recover lost or damaged data. Current systems lack a basic guarantee: Proving data possession upon a user's request (usually before data retrieval).
In this presentation we introduce a model for remote data checking which allows a client that has stored data at an untrusted server toverify that the server possesses the original data. We present provably-secure schemes that have low (or even constant) overhead at the server and and minimize network communication by transmitting a small, constant, amount of data for every challenge/response. The constructs use novel homomorphic verification tags, which allow checking data possession without retrieving the data from the server and without having the server access the entire data. This revolutionizes the ability of users to outsource large data sets by providing a previously-unattainable degree of performance and scalability in verifying the health of external data repositories.
Biography:
Reza Curtmola is an Assistant Professor in Computer Science at the New Jersey Institute of Technology, Newark, NJ. Previously, he was a post doctoral research associate at Purdue University. Reza holds a Ph.D. in Computer Science from The Johns Hopkins University. His research focuses on applied cryptography and network security. More information can be found at http://www.cs.njit.edu/~crix.
In storage oursourcing, a client sends data to a server, which is required by contract to provide persistent archival of the data. Since the server is not trusted and may misbehave, the client typically retains a small piece of metadata which is used to verify the authenticity of the data upon its retrieval. The problem is that by the time data is retrieved, it might be already too late to recover lost or damaged data. Current systems lack a basic guarantee: Proving data possession upon a user's request (usually before data retrieval).
In this presentation we introduce a model for remote data checking which allows a client that has stored data at an untrusted server toverify that the server possesses the original data. We present provably-secure schemes that have low (or even constant) overhead at the server and and minimize network communication by transmitting a small, constant, amount of data for every challenge/response. The constructs use novel homomorphic verification tags, which allow checking data possession without retrieving the data from the server and without having the server access the entire data. This revolutionizes the ability of users to outsource large data sets by providing a previously-unattainable degree of performance and scalability in verifying the health of external data repositories.
Biography:
Reza Curtmola is an Assistant Professor in Computer Science at the New Jersey Institute of Technology, Newark, NJ. Previously, he was a post doctoral research associate at Purdue University. Reza holds a Ph.D. in Computer Science from The Johns Hopkins University. His research focuses on applied cryptography and network security. More information can be found at http://www.cs.njit.edu/~crix.
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Internet Situation Awareness: The Global View 9 Sep 2008
Prof. Norbert Pohlmann
if(is) – Institute for Internet Security, University of Applied Sciences
Gelsenkirchen, Germany
if(is) – Institute for Internet Security, University of Applied Sciences
Gelsenkirchen, Germany
Monday, September 15, 2008, 2:00PM
Babbio Room 221
Stevens Institute of Technology
Abstract:
Our vision is to generate a multidisciplinary continuous situation-awareness in a Private-Public-Partnership to provide all relevant stakeholders with their individual global view of the Internet. To generate this "Internet Situation Awareness" input from all relevant sources has to be used such as from different technical sensor networks, general global data, statistics, and information from the partners. All this information will be analyze and reports will be generated for the different stakeholder. This brings the different stakeholder in the position to make better decisions. Notice: I would like to show some results of Internet Research activities and our
Internet Analysis System, which is developed in the Institute for Internet Security. And I explain the idea of Internet Situation Awareness.
Biography:
Norbert Pohlmann studied Electrical Engineering, specialized in Computer Science, and has written his doctoral thesis on "Possibilities and Limitations of Firewall Systems" (1997-2001). From 1985 to 1988 he was employed as a research engineer in the Telematics Laboratory at Aachen University of Applied Sciences and worked on numerous research and development projects relating to the integration of security mechanisms into communications systems. In 1988 Norbert Pohlmann founded together with Professor Dr, Christoph Ruland the KryptoKom system house in Aachen. In July 1999, KryptoKom GmbH merged with Utimaco Safeware AG, Germany. Between 1999 and 2003 Norbert Pohlmann was a member of the Utimaco Safeware AG management board. Since September 1st 2003 Norbert Pohlmann is Professor in the Computer Science Department and since January 2005 he is director of the Institute for Internet Security at the University of Applied Sciences Gelsenkirchen. As an expert for IT security Norbert Pohlmann has played an active role in cryptography and secure applications since 1985. He is a founding member of the TeleTrusT association, which is devoted to the establishment of trusted IT networks, and has been a member of its board since 1994 and chairman of the board since April 1998. Numerous publications, lectures and seminars on the subject of information security testify to his expertise and commitment to this subject. In 1997 Norbert Pohlmann won the city of Aachen's Prize for Innovation and Technology. Norbert Pohlmann is one of the initiators of the "Information Security Solutions Europe" (ISSE) and the chairman of the ISSE program committee of the ISSE conference.
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Data Integration with Uncertainty 4 Sep 2008
Dr. Xin (Luna) Dong
AT&T Research, Florham Park, NJ
Monday, Sept 8, 2008, 2:00 PM,
Babbio Room 221
Stevens Institute of Technology
AT&T Research, Florham Park, NJ
Monday, Sept 8, 2008, 2:00 PM,
Babbio Room 221
Stevens Institute of Technology
Abstract
Many data management applications, such as managing enterprise data, scientific data, personal data, and integrating data on the web, need to manage a multitude of data sources. These data sets can be highly heterogeneous, describing the same domain using different schemas. To enable data sharing across heterogeneous sources, data integration systems specify a mediated schema, which provides an integrated and virtual view of the disparate sources, and build schema mappings from the source schemas to the mediated schema. Despite recent progress, setting up and maintaining a data integration application still requires significant upfront effort and expertise in creating a mediated schema and semantic mappings between the schemas.
We posit that data integration systems need to handle uncertainty on the semantics of data and do so in a principled fashion. This can be because there are too many schema mappings to be created and maintained, or because in some domains (e.g., bioinformatics) it is not clear what the mappings should be. For this purpose, we propose the new concepts of probabilistic schema mappings, probabilistic mediated schemas, and probabilistic functional dependencies. We analyze their formal foundations and describe how to automatically create them from data sources and use them in answering user's queries. Based on these concepts, we have built the first completely self-configuring data integration system. Our experiments show that the system can produce high-quality answers with no human intervention.
Biography
Dr. Luna Xin Dong is currently a researcher in the Data Management Department at AT&T Research, Florham Park, NJ. She received her Ph.D. in Computer Science and Engineering at University of Washington in 2007. Her research interests include data integration, data cleaning, Web search, personal information management, community information management, enterprise data management, Web-service discovery and composition, and XML query optimization.
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