- talks - lists.cs.princeton.edu

James Bartusek will present his MSE thesis talk "Obfuscating Simple Functionalities" on Monday, May 6, 2019 at 2:30pm in CS 105
by Nicki Mahler 03 May '19

03 May '19

James Bartusek will present his MSE thesis talk "Obfuscating Simple Functionalities" on Monday, May 6, 2019 at 2:30pm in CS 105. The members of his committee are Mark Zhandry (adviser) and Zeev Dvir. Everyone is invited to attend his talk. His abstract follows below. Title: Obfuscating Simple Functionalities Abstract: Program obfuscation is the study of how to securely hide secrets within computer programs. An obfuscator is a compiler that takes as input a computer program P and scrambles it to produce a new program P' that maintains the functionality of P but hides as much as possible about how P is implemented. While constructing a secure and efficient obfuscator that works for any program P appears out of reach with current techniques, there has been a long line of research constructing secure and efficient obfuscators that work for certain simple classes of programs. In this thesis, we continue this line of research and improve on existing work in various ways. In one direction, we present novel obfuscation constructions that are simple, efficient, and secure under standard assumptions. We focus on obfuscating conjunction functions, and construct one obfuscator that is secure under the LPN (learning parity with noise) assumption and another that is secure information theoretically. In another direction, we consider additional security properties that may be useful in the context of obfuscation, such as encrypted inputs and non-malleability. In particular, we give a construction of obfuscation with encrypted inputs that can be compiled into a public-key function-private hidden vector encryption scheme, resolving an open problem of Boneh, Raghunathan, and Segev (Asiacrypt 2013). In addition, we give a standard model construction of point function obfuscation that is provably non-malleable under a large class of mauling functions.

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Rob Harrison will present his FPO "Scalable, Network-wide Telemetry with Programmable Switches" on Tuesday, May 14, 2019 at 2pm in CS 402.
by Nicki Mahler 03 May '19

03 May '19

Rob Harrison will present his FPO "Scalable, Network-wide Telemetry with Programmable Switches" on Tuesday, May 14, 2019 at 2pm in CS 402. The members of his committee are as follows: Jennifer Rexford (adviser), Readers: Nick Feamster and Nate Foster (Cornell University); Nonreaders: David Walker and Kyle Jamieson A copy of his thesis, is available upon request. Everyone is invited to attend his/her talk. The talk title and abstract follow below: Managing modern networks requires collecting and analyzing network traffic from distributed switches in real time, i.e., performing network-wide telemetry. Telemetry systems must be flexible and fine-grained to support myriad queries about the security, performance, and reliability of networks. Yet, they must also scale as the number of queries, link speeds, and the size of the networks increase. Realizing these goals requires balancing the division of labor between high-speed, but resource constrained, network switches and general purpose CPUs to support flexible telemetry at scale. First, we present Sonata, a flexible and scalable network telemetry system that uses the compute resources of both stream-processing servers and a single Protocol Independent Switch Architecture (PISA) switch. PISA switches offer both high-speed processing and limited programmability. We show how to execute Sonata’s high-level queries at line rate by first compiling them to PISA primitives. Next, we model the resource constraints of PISA switches to solve an optimization problem that minimizes the load on the stream processor by executing portions of queries directly in the switch. Sonata can support a wide range of monitoring queries and reduces the stream processor’s workload by orders of magnitude over existing telemetry systems. Second, we present Herd, a system for implementing a subset of Sonata queries distributed across several switches. Herd determines network-wide heavy hitters, i.e., flows that consist of many more packets than most others, by counting flows at the switches, without maintaining per-flow state, and probabilistically reporting to a central coordinator. Based on these reports, the coordinator adapts parameters at each switch based on the spatial locality of the flows. Simulations using packet traces show that our prototype can detect network-wide heavy hitters accurately with 17% savings in communication overhead and 38% savings in switch state compared to existing approaches. We then present an algorithm to tune system parameters in order to maximize detection accuracy under switch memory and bandwidth constraints. Together, Sonata and Herd provide network operators the ability to execute a set of network-wide telemetry queries from a single interface that combines the strengths of both programmable data planes and general-purpose CPUs.

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Fwd: EE Seminar - May 9, 2019, 10:00 am, E-Quad B327 - Ted K. Woodward, Ph.D. Facebook, Inc.
by Jennifer Rexford 03 May '19

03 May '19

> > From: "Lori A. Bailey" <lbailey(a)princeton.edu> > Subject: EE Seminar - May 9, 2019, 10:00 am, E-Quad B327 - Ted K. Woodward, Ph.D. Facebook, Inc. > Date: May 3, 2019 at 2:34:19 PM EDT > To: ee-seminar(a)princeton.edu > Reply-To: "Lori A. Bailey" <lbailey(a)princeton.edu> > > > > Department of Electrical Engineering > Seminar > > > > Speaker: Ted K. Woodward, Ph.D. > Facebook, Inc. > Title: Facebook Connectivity: challenges and progress in bringing more people to a faster Internet > Date: Thursday, May 9, 2019 > Time: 10:00 am > Room: E-Quad, Room B327 > Host: Prof. Kaushik Sengupta > > Abstract: The Facebook connectivity organization works to stimulate global broadband connectivity. I will summarize some of the many challenges associated with the task and describe some of the work the group is doing to make progress toward the goal. > > For more information visit: http://connectivity.fb.com/ <http://connectivity.fb.com/> > > Bio: Ted K. Woodward, Ph.D. manages the Connectivity Labs group at Facebook, a program-centric organization focused on early stage activity in support of the larger Facebook Connectivity organization. Before joining the Connectivity team at Facebook, from 2015 to 2018 Dr. Woodward was a Program Manager in the Strategic Technologies Office of the Defense Advanced Research Projects Agency (DARPA), where he led programs in Communications, Networking, and RF systems. Before that, he spent more than 25 years in diverse communication and networking research, development, and product companies including Telcordia Technologies and follow-on entities, Bell Laboratories Research, Ciena Corporation, and Internet Photonics, Inc., which he co-founded. >

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EE Seminar - May 9, 2019, 10:00 am, E-Quad B327 - Ted K. Woodward, Ph.D. Facebook, Inc.
by Emily Lawrence 03 May '19

03 May '19

Department of Electrical Engineering Seminar Speaker: Ted K. Woodward, Ph.D., Facebook, Inc. Title: Facebook Connectivity: challenges and progress in bringing more people to a faster Internet Date: Thursday, May 9, 2019 Time: 10:00 am Room: E-Quad, Room B327 Host: Prof. Kaushik Sengupta Abstract: The Facebook connectivity organization works to stimulate global broadband connectivity. I will summarize some of the many challenges associated with the task and describe some of the work the group is doing to make progress toward the goal. For more information visit: http://connectivity.fb.com/ Bio: Ted K. Woodward, Ph.D. manages the Connectivity Labs group at Facebook, a program-centric organization focused on early stage activity in support of the larger Facebook Connectivity organization. Before joining the Connectivity team at Facebook, from 2015 to 2018 Dr. Woodward was a Program Manager in the Strategic Technologies Office of the Defense Advanced Research Projects Agency (DARPA), where he led programs in Communications, Networking, and RF systems. Before that, he spent more than 25 years in diverse communication and networking research, development, and product companies including Telcordia Technologies and follow-on entities, Bell Laboratories Research, Ciena Corporation, and Internet Photonics, Inc., which he co-founded.

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LOCATION CHANGE-Michael Uhlar and Sathya Gunasekar today at 12:30 in CS 302
by Emily Lawrence 03 May '19

03 May '19

**Please note, the location of this talk has changed to room CS 302. Michael Uhlar and Sathya Gunasekar from Facebook Friday, May 3 at 12:30pm Computer Science - 302 https://www.cs.princeton.edu/events/25851 CacheLib - Unifying & Abstracting HW for caching @ Facebook In order to operate with high efficiency, Facebook’s infrastructure relies on caching in many different backend services. These services place very different demands on their caches, e.g., in terms of working set sizes, access patterns, and throughput requirements. Historically, each service used a different cache implementation, leading to inefficiency, duplicated code and effort. CacheLib is an embedded caching engine, which addresses this requirement with a unified API for building a cache implementation across many HW mediums. CacheLib transparently combines volatile and non-volatile storage in a single caching abstraction. To meet the varied demands, CacheLib successfully provides a flexible, high-performance solution for many different services at Facebook. In this talk, we describe CacheLib’s design, challenges, and several lessons learned.

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Farhan Damani will present his General Exam "Inferring cognitive learning rules from behavior with probabilistic models" on Thursday, May 9, 2019 at 1pm in CS 401.
by Nicki Mahler 03 May '19

03 May '19

Farhan Damani will present his General Exam " Inferring cognitive learning rules from behavior with probabilistic models" on Thursday, May 9, 2019 at 1pm in CS 401. The members of his committee are as follows: Ryan Adams (adviser), Jonathan Pillow, and Tom Griffiths Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Title: Inferring cognitive learning rules from behavior with probabilistic models Abstract: High-throughput behavioral neuroscience presents an exciting opportunity to investigate the dynamics of learning during decision making. We describe a probabilistic model that captures a learner's underlying time-dependent decision making strategy while learning a forced choice discrimination task. Through priors that explicitly characterize how learner's update their knowledge state, our approach presents the opportunity to infer an evolving decision-making strategy despite observing only a single sequence of decisions. Importantly, our model is probabilistic, which means we can reason about a learner's competence, learning rate, and preference for simpler models using the marginal likelihood. We apply our method to large-scale behavioral datasets and discover personalized learning rules explaining vast differences in the learning dynamics across learners while also finding shared explanations for simpler models and skill-specific learning rates. Reading list: Textbook: Koller, D., Friedman, N., & Bach, F. (2009). Probabilistic graphical models: principles and techniques . MIT press 1. Hoffman, M. D., Blei, D. M., Wang, C., & Paisley, J. (2013). Stochastic variational inference. The Journal of Machine Learning Research , 14 (1), 1303-1347. 2. Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., & Blei, D. M. (2017). Automatic differentiation variational inference. The Journal of Machine Learning Research , 18 (1), 430-474. 3. Kingma, D. P., & Welling, M. (2013). Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 . 4. Archer, E., Park, I. M., Buesing, L., Cunningham, J., & Paninski, L. (2015). Black box variational inference for state space models. arXiv preprint arXiv:1511.07367 . 5. Johnson, M., Duvenaud, D. K., Wiltschko, A., Adams, R. P., & Datta, S. R. (2016). Composing graphical models with neural networks for structured representations and fast inference. In Advances in neural information processing systems (pp. 2946-2954). 6. Krishnan, R. G., Shalit, U., & Sontag, D. (2017, February). Structured inference networks for nonlinear state space models. In Thirty-First AAAI Conference on Artificial Intelligence 7. Smith, A. C., Frank, L. M., Wirth, S., Yanike, M., Hu, D., Kubota, Y., ... & Brown, E. N. (2004). Dynamic analysis of learning in behavioral experiments. Journal of Neuroscience , 24 (2), 447-461. 8. Bak, J. H., Choi, J. Y., Akrami, A., Witten, I., & Pillow, J. W. (2016). Adaptive optimal training of animal behavior. In Advances in neural information processing systems (pp. 1947-1955) 9. Paninski, L., Ahmadian, Y., Ferreira, D. G., Koyama, S., Rad, K. R., Vidne, M., ... & Wu, W. (2010). A new look at state-space models for neural data. Journal of computational neuroscience , 29 (1-2), 107-126. 10. Prerau, M. J., Smith, A. C., Eden, U. T., Kubota, Y., Yanike, M., Suzuki, W., ... & Brown, E. N. (2009). Characterizing learning by simultaneous analysis of continuous and binary measures of performance. Journal of neurophysiology , 102 (5), 3060-3072.

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Austin Hounsel will present his General Exam "Disinfotron: Early and Progressive Detection of Online Disinformation" on Thursday, May 9th at 7:30am in CS 402
by Nicki Mahler 03 May '19

03 May '19

Austin Hounsel will present his General Exam " Disinfotron: Early and Progressive Detection of Online Disinformation" on Thursday, May 9th at 7:30am in CS 402. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Committee : Nick Feamster, Jonathan Mayer, and Kyle Jamieson Title : Disinfotron: Early and Progressive Detection of Online Disinformation Abstrac t: Online disinformation is a serious and growing threat to the integrity of public discourse, democratic governance, and commerce. Disinformation is not new, but the Internet has made it cheaper, easier, and more effective. Although major online platforms are deploying systems to counter disinformation, existing approaches largely rely on user moderation and manual analysis. The scalability challenges and delays associated with these approaches significantly undermine their efficacy; by the time a platform takes action, disinformation has already spread and achieved its intended effect. This paper presents a new approach to detecting disinformation: Disinfotron, an automated early warning system that progressively detects new disinformation campaigns at key stages of the deployment lifecycle. Drawing inspiration from previous work that detects malware distribution, phishing, and scams from network-level and application-level features, we demonstrate the feasibility of detecting disinformation campaigns before they can spread, and in some cases before they can even launch. Disinfotron uses domain, certificate, and hosting features to classify websites as either disinformation, news, or lacking news content. Our results demonstrate that Disinfotron is fast, accurate, and scalable. Reading list : * Textbook: * Kurose, J. F., & Ross, K. W. (2016). Computer networking: A top-down approach . Boston, MA: Pearson. * Papers: * Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of economic perspectives , 31(2), 211-36. * Pérez-Rosas, V., Kleinberg, B., Lefevre, A., & Mihalcea, R. (2018, August). Automatic Detection of Fake News. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 3391-3401). * Baly, R., Karadzhov, G., Alexandrov, D., Glass, J., & Nakov, P. (2018). Predicting factuality of reporting and bias of news media sources. arXiv preprint arXiv:1810.01765. * Ratkiewicz, J., Conover, M. D., Meiss, M., Gonçalves, B., Flammini, A., & Menczer, F. M. (2011, July). Detecting and tracking political abuse in social media. In Fifth international AAAI conference on weblogs and social media . * Ma, J., Saul, L. K., Savage, S., & Voelker, G. M. (2009, June). Identifying suspicious URLs: an application of large-scale online learning. In Proceedings of the 26th annual international conference on machine learning (pp. 681-688). ACM. * Ramachandran, A., & Feamster, N. (2006, September). Understanding the network-level behavior of spammers. In ACM SIGCOMM Computer Communication Review (Vol. 36, No. 4, pp. 291-302). ACM. * Hao, S., Kantchelian, A., Miller, B., Paxson, V., & Feamster, N. (2016, October). PREDATOR: proactive recognition and elimination of domain abuse at time-of-registration. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (pp. 1568-1579). ACM. * Hao, S., Syed, N. A., Feamster, N., Gray, A. G., & Krasser, S. (2009, August). Detecting Spammers with SNARE: Spatio-temporal Network-level Automatic Reputation Engine. In USENIX security symposium (Vol. 9). * Thomas, K., Grier, C., Ma, J., Paxson, V., & Song, D. (2011, May). Design and evaluation of a real-time url spam filtering service. In 2011 IEEE symposium on security and privacy (pp. 447-462). IEEE. * Grier, C., Thomas, K., Paxson, V., & Zhang, M. (2010, October). @ spam: the underground on 140 characters or less. In Proceedings of the 17th ACM conference on Computer and communications security (pp. 27-37). ACM.

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Michael Uhlar and Sathya Gunasekar TODAY at 12:30
by Emily C. Lawrence 03 May '19

03 May '19

Michael Uhlar and Sathya Gunasekar from Facebook Friday, May 3 at 12:30pm Computer Science - Room 104 (large auditorium) [ https://www.cs.princeton.edu/events/25851 | https://www.cs.princeton.edu/events/25851 ] CacheLib - Unifying & Abstracting HW for caching @ Facebook In order to operate with high efficiency, Facebook’s infrastructure relies on caching in many different backend services. These services place very different demands on their caches, e.g., in terms of working set sizes, access patterns, and throughput requirements. Historically, each service used a different cache implementation, leading to inefficiency, duplicated code and effort. CacheLib is an embedded caching engine, which addresses this requirement with a unified API for building a cache implementation across many HW mediums. CacheLib transparently combines volatile and non-volatile storage in a single caching abstraction. To meet the varied demands, CacheLib successfully provides a flexible, high-performance solution for many different services at Facebook. In this talk, we describe CacheLib’s design, challenges, and several lessons learned.

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Qinshi Wang will present his General Exam "Decision procedures useful in separation-logic proofs of functional correctness" on Thursday, May 9, 2019 at 3:30pm in Friend 203.
by Nicki Mahler 02 May '19

02 May '19

Qinshi Wang will present his General Exam "Decision procedures useful in separation-logic proofs of functional correctness" on Thursday, May 9, 2019 at 3:30pm in Friend 203. The members of his committee are as follows: Andrew Appel (adviser), Zak Kincaid, and Aarti Gupta. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Research talk title: Decision procedures useful in separation-logic proofs of functional correctness Abstract: VST has been used successfully to verify C programs with rich specifications. However, proofs in Verifiable C require substantial human work, which prevents applications in larger programs. We have improved VST’s proof automation in two ways. The first is term inference in existential variables, heap lemmas and function calls. The second is an automatic prover that solves relations on lists. Our list/array theory contains list concatenations, which occur frequently in array content specifications, and are undecidable in general. But we show a decidable fragment, in which relations between different positions in the same list are prohibited. We show this fragment covers many useful verification goals found in existing VST verifications. Reading list: 1. Bradley, Aaron R., and Zohar Manna. The calculus of computation: decision procedures with applications to verification. Springer Science & Business Media, 2007. 2. Pierce, Benjamin C., et al. "Software foundations." Volumes 1 & 2. [ https://softwarefoundations.cis.upenn.edu/ | Webpage: https://softwarefoundations.cis.upenn.edu/ ] (2010). 3. Bradley, Aaron R. "Safety analysis of systems." Chapter 2. PhD diss., Stanford University, 2007. 4. Habermehl, Peter, Radu Iosif, and Tomáš Vojnar. "What else is decidable about integer arrays?." International Conference on Foundations of Software Science and Computational Structures. Springer, Berlin, Heidelberg, 2008. 5. Lothaire, Monsieur, and M. Lothaire. Algebraic combinatorics on words. Chapter 12. Cambridge university press, 2002. 6. Furia, Carlo A. "What’s Decidable About Sequences?." International Symposium on Automated Technology for Verification and Analysis. Springer, Berlin, Heidelberg, 2010. 7. Le, Xuan-Bach, and Aquinas Hobor. "Logical reasoning for disjoint permissions." European Symposium on Programming. Springer, Cham, 2018. 8. Jacobs, Bart, et al. "VeriFast: A powerful, sound, predictable, fast verifier for C and Java." NASA Formal Methods Symposium. Springer, Berlin, Heidelberg, 2011. 9. Calcagno, Cristiano, et al. "Compositional shape analysis by means of bi-abduction." ACM SIGPLAN Notices. Vol. 44. No. 1. ACM, 2009. 10. Brotherston, James, Nikos Gorogiannis, and Max Kanovich. "Biabduction (and related problems) in array separation logic." International Conference on Automated Deduction. Springer, Cham, 2017. 11. Appel, Andrew W. "VeriSmall: verified smallfoot shape analysis." International Conference on Certified Programs and Proofs. Springer, Berlin, Heidelberg, 2011.

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TODAY at 4:30pm in B205 - Asu Ozdaglar, MIT
by Emily Lawrence 02 May '19

02 May '19

EE SEMINAR Speaker: Prof. Asu Ozdaglar, Massachusetts Institute of Technology Title: Network Games Day: Thursday, May 2, 2019 Time: 4:30 pm Room: B205 Engineering Quadrangle Host: Ozge Akmandor Abstract: In many social and economic settings, decisions of individuals are affected by the actions of their friends, colleagues, and peers. Examples include adoption of new products and innovations, opinion formation and social learning, public good provision, financial exchanges and international trade. Network games have emerged as a powerful framework to study these settings with particular focus on how the underlying patterns of interactions, governed by a network, affect the economic outcomes. For tractability reasons, much of the work in this area studied games with special structure (e.g., quadratic cost functions, scalar non-negative strategies) or special properties (e.g., games of strategic complements or substitutes). In this talk, we will present a unified framework based on a variational inequality reformulation of the Nash equilibrium to study equilibrium properties of network games including existence and uniqueness, convergence of the best response dynamics and comparative statics. Our framework extends the literature in multiple dimensions, covering games with general strategic interactions and multidimensional and constrained strategy sets. In the second part of the talk, we will present a new class of infinite populations games, graphon games, that can capture heterogenous local interactions. We will show how graphon games can approximate strategic behavior and allow design of intervention policies for sampled network games that are robust to stochastic variations. This is joint work with Francesca Parise. Bio: Asu Ozdaglar received the B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1996, and the S.M. and the Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1998 and 2003, respectively. She is the Distinguished Professor of Engineering in the Electrical Engineering and Computer Science (EECS) Department at the Massachusetts Institute of Technology. She is also the department head of EECS. Her research expertise includes optimization theory, with emphasis on nonlinear programming and convex analysis, game theory, with applications in communication, social, and economic networks, distributed optimization and control, and network analysis with special emphasis on contagious processes, systemic risk and dynamic control. Professor Ozdaglar is the recipient of a Microsoft fellowship, the MIT Graduate Student Council Teaching award, the NSF Career award, the 2008 Donald P. Eckman award of the American Automatic Control Council, the Class of 1943 Career Development Chair, the inaugural Steven and Renee Innovation Fellowship, and the 2014 Spira teaching award. She served on the Board of Governors of the Control System Society in 2010 and was an associate editor for IEEE Transactions on Automatic Control. She was the inaugural area co-editor for the area entitled "Games, Information and Networks" in the journal Operations Research .She is the co-author of the book entitled "Convex Analysis and Optimization" (Athena Scientific, 2003). This seminar is supported with funds from the Bede Liu Fund for Excellence in Engineering.

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