- talks - lists.cs.princeton.edu

Colloquium Speaker Kevin Fu Thurs Oct 10 4:30pm Friend Center 006
by Nicole E. Wagenblast 10 Oct '13

10 Oct '13

Medical Device Cyber Security: The First 164 Years Kevin Fu , University of Michigan Thursday, October 10- 4:30pm Friend Center 006 The U.S. Institute of Medicine commissioned my 2011 report on the role of trustworthy software in the context of the "510(k)" U.S. medical device regulations. More recently, the U.S. Food and Drug Administration has released draft guidance on cybersecurity for medical device manufacturing. This talk will provide a glimpse into the risks, benefits, and regulatory issues for medical device cybersecurity and innovation of trustworthy medical device software. Today, it would be difficult to find medical device technology that does not critically depend on computer software. The technology enables patients to lead more normal and healthy lives. However, medical devices that rely on software (e.g., drug infusion pumps, linear accelerators) continue to injure or kill patients in preventable ways---despite the lessons learned from the tragic radiation incidents of the Therac-25 era. The lack of trustworthy medical device software leads to shortfalls in properties such as safety, effectiveness, dependability, reliability, usability, security, and privacy. Come learn a bit about the science, technology, and policy that shapes medical device software. Kevin Fu is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan where he directs the Archimedes Center for Medical Device Security and the SPQR group. His research investigates how to achieve trustworthy computing on embedded devices with application to health care, commerce, and communication. His most recent contributions appear in computer science and medical conferences and journals such as USENIX Security and IEEE Security and Privacy. Kevin received his PhD in EECS from the MIT. Fu received a Sloan Research Fellowship, NSF CAREER award, Fed100 Award, and best paper awards from various academic silos of computing. The research is featured in critical articles by the NYT, WSJ, and NPR. Kevin was named MIT Technology Review TR35 Innovator of the Year for work on medical device security. Kevin has testified in Congress on health matters and has written commissioned work for the Institute of Medicine of the National Academies. He served as a visiting scientist at the Food & Drug Administration, the Beth Israel Deaconess Medical Center of Harvard Medical School, Microsoft Research, and MIT CSAIL. Previous employers include Bellcore, Cisco Systems, HP Labs, and Holland Community Hospital. He is a member of the ACM Committee on Computers and Public Policy and the NIST Information Security and Privacy Advisory Board. Kevin also holds a certificate of achievement in artisanal bread making from the French Culinary Institute.

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A Chaney general exam
by Melissa M. Lawson 08 Oct '13

08 Oct '13

Allison Chaney will present her research seminar/general exam on Tuesday October 15 at 2PM in Room 301 (note room). The members of her committee are: David Blei (advisor), Rebecca Fiebrink, and Andrea LaPaugh. Everyone is invited to attend her talk, and those faculty wishing to remain for the oral exam following are welcome to do so. Her abstract and reading list follow below. ----- Original Message ----- Abstract Each of us are faced with the problem of selecting which books to read and movies to watch. Traditionally, we ask our trusted friends for recommendations, but algorithmic recommendation models make those choices even easier, saving us time and effort by steering us towards media we are more likely to enjoy. The downside to most probabilistic recommendations is that for some people, part of the appeal of reading or consuming other media is in creating shared experiences with friends. I present a model that incorporates social network information into recommendation models, reintroducing the social aspect to recommendation; this approach also has the potential to improve overall recommendations. This model discovers the latent trust that exists between users in a network and allows us to consider which users are more trustworthy than others, providing us insight into the social network's dynamics. Papers 1. D. Blei, A. Ng, and M. Jordan. Latent Dirichlet allocation . Journal of Machine Learning Research , 3:993–1022, January 2003. http://www.cs.princeton.edu/~blei/papers/BleiNgJordan2003.pdf 2. C. Wang and D. Blei. Collaborative topic modeling for recommending scientific articles. Knowledge Discovery and Data Mining , 2011. http://www.cs.cmu.edu/~chongw/papers/WangBlei2011.pdf 3. P. Gopalan, Scalable Recommendation with Poisson Factorization (forthcoming, supplied on request) 4. S. Purushotham, Y. Liu, and C.-C. J. Kuo. Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems . International Conference on Machine Learning, 2012. http://icml.cc/2012/papers/407.pdf 5. M. Hao, Y. Haixuan, M. R. Lyu , I. King. SoRec: Social Recommendation Using Probabilistic Matrix Factorization . Proceedings of the 17th ACM conference on Information and knowledge management , pg. 931–940, October 2008. http://appsrv.cse.cuhk.edu.hk/~hma/Paper_CIKM08_SoRec_Hao.pdf 6. H. Shan and A. Banerjee, Generalized Probabilistic Matrix Factorizations for Collaborative Filtering http://www-users.cs.umn.edu/~shan/icdm10_gpmf.pdf 7. Y. Koren, R. Bell, and C. Volinsky. Matrix Factorization Techniques for Recommender Systems . Computer , 42:30–37, August 2009. http://www2.research.att.com/~volinsky/papers/ieeecomputer.pdf 8. J. Herlocker, J. Konstan, L. Terveen, and J. Riedl. Evaluating Collaborative Filtering Recommender Systems . ACM Transactions on Information Systems , 2004. http://dl.acm.org/citation.cfm?doid=963770.963772 9. M. Hoffman, D. Blei, J. Paisley, and C. Wang. Stochastic variational inference . Journal of Machine Learning Research , 2013. http://www.cs.princeton.edu/~blei/papers/HoffmanBleiWangPaisley2013.pdf Selected Sections of Textbooks 1. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach , Prentice Hall Series in Artificial Intelligence, 2003: Chapters: 3.1-3.5, 4.1, 5, 8.1-8.3, 13.1-13.5, 14, 15, 18, 21 2. Bishop, C. M., Pattern Recognition and Machine Learning , Springer , 2006 : Chapters 1, 2, 3.1-3.3, 4.1-4.3, 8, 9, 10, 11.1-11.3, 12.1-12.2, 13, 14.1, 14.3 3. A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin. Bayesian Data Analysi s, Taylor & Francis, 1995: chapters 5, 6, 11 4. Spall, J. C., Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control , Wiley, 2003: Ch 2 5. J. Lazar, J. Feng, and H. Hochheiser. Research Methods in Human-Computer Interaction. John Wiley & Sons, 2010: Chapters 2,3,10-12 6. R ecommender Systems Handbook, Springer , 2010. Chapter 8: Evaluating Recommendation Systems by G. Shani and A. Gunawardana.

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A Bell FPO
by Melissa M. Lawson 03 Oct '13

03 Oct '13

Ana Bell will present her FPO on Friday October 11 at 9AM in Room 402. The members of her committee are: Olga Troyanskaya, advisor; Mona Singh and Andrea LaPaugh, readers; Tom Funkhouser and Kai Li, nonreaders. A copy of her thesis, "Integrating Genomic Data to Build Networks for Proteins and Small Molecules", is on display in Room 310. Everyone is invited to attend her talk.

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Colloquium Speaker Kevin Fu, Thurs Oct 10, 4:30pm, Friend 006
by Nicole E. Wagenblast 02 Oct '13

02 Oct '13

Medical Device Cyber Security: The First 164 Years Kevin Fu , University of Michigan Thursday, October 10, 4:30pm Friend Center, 006 The U.S. Institute of Medicine commissioned my 2011 report on the role of trustworthy software in the context of the "510(k)" U.S. medical device regulations. More recently, the U.S. Food and Drug Administration has released draft guidance on cybersecurity for medical device manufacturing. This talk will provide a glimpse into the risks, benefits, and regulatory issues for medical device cybersecurity and innovation of trustworthy medical device software Today, it would be difficult to find medical device technology that does not critically depend on computer software. The technology enables patients to lead more normal and healthy lives. However, medical devices that rely on software (e.g., drug infusion pumps, linear accelerators) continue to injure or kill patients in preventable ways---despite the lessons learned from the tragic radiation incidents of the Therac-25 era. The lack of trustworthy medical device software leads to shortfalls in properties such as safety, effectiveness, dependability, reliability, usability, security, and privacy. Come learn a bit about the science, technology, and policy that shapes medical device software. Kevin Fu is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan where he directs the Archimedes Center for Medical Device Security and the SPQR group. His research investigates how to achieve trustworthy computing on embedded devices with application to health care, commerce, and communication. His most recent contributions appear in computer science and medical conferences and journals such as USENIX Security and IEEE Security and Privacy. Kevin received his PhD in EECS from the MIT. Fu received a Sloan Research Fellowship, NSF CAREER award, Fed100 Award, and best paper awards from various academic silos of computing. The research is featured in critical articles by the NYT, WSJ, and NPR. Kevin was named MIT Technology Review TR35 Innovator of the Year for work on medical device security. Kevin has testified in Congress on health matters and has written commissioned work for the Institute of Medicine of the National Academies. He served as a visiting scientist at the Food & Drug Administration, the Beth Israel Deaconess Medical Center of Harvard Medical School, Microsoft Research, and MIT CSAIL. Previous employers include Bellcore, Cisco Systems, HP Labs, and Holland Community Hospital. He is a member of the ACM Committee on Computers and Public Policy and the NIST Information Security and Privacy Advisory Board. Kevin also holds a certificate of achievement in artisanal bread making from the French Culinary Institute.

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Colloquium Speaker Rajiv Gandhi Wed Oct 2nd 4:30pm
by Nicole E. Wagenblast 01 Oct '13

01 Oct '13

>From Potential to Promise - Developing Scholars, one Eureka moment at a time Rajiv Gandhi , Rutgers University, Camden Wednesday, October 2, 4:30pm Computer Science 105 In this talk, I will tell the story of our work with some truly remarkable undergraduate students at Rutgers-Camden, who despite many odds have achieved success that is unprecedented for the Camden campus. I will discuss the various challenges that we faced and some ideas that have worked very well (and some that have not) for us. We have been applying some of these ideas in our work with high school students and students at other institutions. This talk should be of interest to all faculty and students. Dr. Rajiv Gandhi is an Associate Professor of Computer Science at the Rutgers University-Camden. He received his Ph.D. in Computer Science from the University of Maryland, College Park in 2003. He worked as a software engineer at Qualcomm from 1994-96. His research interests lie in the broad area of theoretical computer science. Specifically, he is interested in approximation and randomized algorithms, distributed algorithms, and graph theory. He has published papers in these areas in leading journals and conferences. He has been the recipient of several teaching excellence awards -- at Rutgers-Camden and at other universities. He was also the recipient of the Chancellor's award for Civic Engagement at Rutgers-Camden in 2013. He was a Fulbright Fellow from Jan-June 2011, during which he worked with students in Mumbai. Since 2009, he has also been working with high school students as part of the Program in Discrete Mathematics and Computer Science.

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Colloquium Speaker: Amit Sahai, Wed. Sept. 25 4:30pm
by Nicole E. Wagenblast 24 Sep '13

24 Sep '13

How to Encrypt Software Amit Sahai , UCLA Wednesday, September 25, 4:30pm Computer Science 105 The goal of secure program obfuscation is to make a program “unintelligible” while preserving its functionality. For decades, program obfuscation for general programs has remained an art, with all public general-purpose obfuscation methods known to be broken. In this talk, we will describe new developments this year that for the first time provide a mathematical approach to the problem of general-purpose program obfuscation, where extracting secrets from the obfuscated program requires solving mathematical problems that currently take hundreds of years to solve on the world's fastest computing systems. We will also discuss the implications of these developments. This talk is based on joint works with Sanjam Garg, Craig Gentry, Shai Halevi, Mariana Raykova, and Brent Waters. Professor Amit Sahai received his Ph.D. in Computer Science from MIT in 2000. From 2000 to 2004, he was on the faculty at Princeton University; in 2004 he joined UCLA, where he currently holds the position of Professor of Computer Science. His research interests are in security and cryptography, and theoretical computer science more broadly. He has published more than 100 original technical research papers at venues such as the ACM Symposium on Theory of Computing (STOC), CRYPTO, and the Journal of the ACM. He has given a number of invited talks at institutions such as MIT, Stanford, and Berkeley, including the 2004 Distinguished Cryptographer Lecture Series at NTT Labs, Japan. Professor Sahai is the recipient of numerous honors; he was named an Alfred P. Sloan Foundation Research Fellow in 2002, received an Okawa Research Grant Award in 2007, a Xerox Foundation Faculty Award in 2010, a Google Faculty Research Award in 2010, and the 2013 Pazy Memorial Award.

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Talk: Ashutosh Saxena - Monday 12:30 CS 402
by Nicole E. Wagenblast 23 Sep '13

23 Sep '13

Date: Monday, September 23, 2013 Time: 12:30-13:30 Room: CS 402 Title: How should a robot perceive the world? Speaker: Ashutosh Saxena Abstract: In order to perform assistive tasks, a robot should perceive a functional understanding of the environment. This comprises learning how the objects in the environment could be used (i.e., their affordances). In this talk, I will discuss what types of object representations could be useful. One challenge is to model the object's context with each other and with (hidden) humans. Our learning algorithm will be Infinite Latent CRFs (ILCRFs) that allow modeling the data with different plausible graph structures. Unlike CRFs, where the graph structure is fixed, ILCRFs learn distributions over possible graph structures in an unsupervised manner. We then show that our idea of modeling environments using object affordances and hidden humans is not only useful for robot manipulation tasks such as arranging a disorganized house, haptic manipulation, unloading items from a dishwasher, but also in significantly improving standard robotic tasks such as scene segmentation, 3D object detection, human activity detection and anticipation, and task and path planning. Bio: Ashutosh Saxena is an assistant professor in computer science department at Cornell University. His research interests include machine learning and robotics perception, especially in the domain of personal robotics. He received his MS in 2006 and Ph.D. in 2009 from Stanford University, and his B.Tech. in 2004 from Indian Institute of Technology (IIT) Kanpur. He is a recipient of National Talent Scholar award in India, Google Faculty award, Alfred P. Sloan Fellowship, Microsoft Faculty Fellowship, and NSF Career award. In the past, Ashutosh developed Make3D (http://make3d.cs.cornell.edu), an algorithm that converts a single photograph into a 3D model. Tens of thousands of users used this technology to convert their pictures to 3D. He has also developed algorithms that enable robots (such as STAIR, POLAR, see http://pr.cs.cornell.edu) to perform household chores such as unload items from a dishwasher, place items in a fridge, etc. His work has received substantial amount of attention in popular press, including the front-page of New York Times, BBC, ABC, New Scientist, Discovery Science, and Wired Magazine. He has won best paper awards in 3DRR, IEEE ACE and RSS, and was named a co-chair of the IEEE technical committee on robot learning. -- Best, Jianxiong Xiao Assistant Professor Department of Computer Science Princeton University http://vision.princeton.edu

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Talk: Sharon Goldberg Thurs 9/19 4:30pm
by Nicole E. Wagenblast 19 Sep '13

19 Sep '13

Should we secure routing with the RPKI Sharon Goldberg , Boston University Thursday, September 19, 4:30-5:30pm Computer Science, 402 In this talk I will overview the benefits and risks of adopting the Resource Public Key Infrastructure (RPKI), a new centralized security infrastructure for interdomain routing that has recently been standardized by the IETF. On one hand, I argue that the RPKI is one of the most effective ways to limit attacks on interdomain routing; more so, in fact, than more advanced cryptographic solutions that require more drastic changes to router hardware and protocol messages. On the other hand, I discuss how state-sponsored actors and malicious attackers can exploit the RPKI's centralized architecture to launch new attacks that can cause serious harm to the Internet's routing system. I conclude by discussing open problems that should be solved before the RPKI is widely adopted. Based on works with Robert Lychev, Pete Hummon, Jennifer Rexford, and Michael Schapira that appeared at SIGCOMM'10 and SIGCOMM'13, and work in progress with Kyle Brogle, Danny Cooper, Ethan Heilman, and Leonid Reyzin. Sharon Goldberg is an Assistant Professor in the Department of Computer Science at Boston University. Her research focuses on finding practical solutions to problems in network security. She received her Ph.D. from Princeton University in 2009, her B.A.Sc. from the University of Toronto in 2003, and has worked as a researcher at IBM, Cisco, and Microsoft, and a telecommunication engineer at Bell Canada and Hydro One Networks.

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Thurs 9/19 12pm Talk: Younghwan Go, Gaining Control of Cellular Traffic Accounting by Spurious TCP Retransmission
by Nicole E. Wagenblast 19 Sep '13

19 Sep '13

Gaining Control of Cellular Traffic Accounting by Spurious TCP Retransmission Younghwan Go , Korea Advanced Institute of Science and Technology Thursday, September 19, 12pm Computer Science 402 Packet retransmission is a fundamental TCP feature that ensures reliable data transfer between two end nodes. Interestingly, when it comes to cellular data accounting, TCP retransmission creates an important policy issue. Cellular ISPs might argue that all retransmitted IP packets should be accounted for billing since they consume the resources of their infrastructures. On the other hand, the service subscribers might want to pay only for the application data by taking out the amount for retransmission. Regardless of the policies, however, we find that TCP retransmission can be easily abused to manipulate the current practice of cellular traffic accounting. In this work, we investigate the TCP retransmission accounting policies of 12 cellular ISPs in the world and report the accounting vulnerabilities with TCP retransmission attacks. First, we find that cellular data accounting policies vary from ISP to ISP. While the majority of cellular ISPs blindly account for every IP packet, some ISPs intentionally remove the retransmission packets from the user bill for fairness. Second, we show that it is easy to launch the “usage-inflation” attack on the ISPs that blindly account for every IP packet. In our experiments, we could inflate the usage up to the monthly limit only within 9 minutes of the attack completely without the knowledge of the subscriber. For those ISPs that do not account for retransmission, we successfully launch the “free-riding” attack by tunneling the payload under fake TCP headers that look like retransmission. To counter the attacks, we argue that the ISPs should consider ignoring TCP retransmission for billing while detecting the tunneling attacks by deep packet inspection. We implement and evaluate Abacus, a light-weight accounting system that reliably detects “free-riding” attacks even in the 10 Gbps links. Younghwan Go is currently a Ph.D. student at KAIST. His research interests are networked and distributed systems, network security and mobile network. He received a M.S. degree in Electrical Engineering and Information Security from KAIST in 2013. Previously, he received a Bachelor's degree in Electrical Engineering from KAIST in 2011. Nicole Wagenblast Computer Science Department Princeton University 35 Olden Street Princeton, NJ 08540 609-258-4624

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Colloquium Speaker Yoram Moses
by Nicole E. Wagenblast 06 Sep '13

06 Sep '13

The Knowledge of Preconditions principle Yoram Moses , Technion Monday, September 9, 4:30pm Computer Science 105 This talk will present a simple principle relating knowledge and action in distributed systems: If some condition must be true when a given action is taken, then this condition must be known when the action is taken. This yields a number of fundamental connections between knowledge and multi-party coordination. In particular, the talk will illustrate how these can provide insight into the interplay between time, communication and coordination in networks and distributed systems. The talk will be self-contained, intended for a general CS audience. The latter part of the talk is based on joint work with Ido Ben Zvi. No familiarity with the subject will be assumed. Yoram Moses is the Israel Pollack Academic Chair at the Technion. He is a recipient of the Godel Prize 1997 and the Dijkstra Award in 2009.

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