[cs-talks] Upcoming Seminars: BUSec (Wed) + Hariri (Thurs) + BUSec (Wed) + IVC (Thurs)
cs at bu.edu
Tue Apr 21 09:50:43 EDT 2015
Two Round MPC from LWE via Multi-Key FHE
Pratyay Mukherjee, Aarhus Universitet and Northeastern University
Wednesday, April 22, 2015 at 10:00pm in Hariri 180
Abstract: We construct a general multiparty computation (MPC) protocol in the common random string (CRS) model with only two rounds of interaction, which is known to be optimal. In the honest-but-curious setting we only rely on the learning with errors (LWE) assumption, and in the fully malicious setting we additionally assume the existence of non-interactive zero knowledge arguments (NIZKs). Previously, Asharov et al. (EUROCRYPT '12) showed how to achieve three rounds based on LWE and NIZKs, while Garg et al. (TCC '14) showed how to achieve the optimal two rounds based on indistinguishability obfuscation, but it was unknown if two rounds were possible under simpler assumptions without obfuscation. Our approach relies on multi-key fully homomorphic encryption (MFHE), introduced by Lopez-Alt et al. (STOC '12), which enables homomorphic computation over data encrypted under dierent keys. We use a recent construction of MFHE based on LWE by Clear and McGoldrick (ePrint '14), and we give a simplied stand-alone exposition of that scheme. We then extend this construction to allow for a one-round distributed decryption of a multi-key ciphertext. Our entire MPC protocol consists of the following two rounds:
1. Each party individually encrypts its input under its own key and broadcasts the ciphertext. All parties can then homomorphically compute a multi-key encryption of the output.
2. Each party broadcasts a partial decryption of the output using its secret key. The partial decryptions can be combined to recover the output in plaintext.
A joint work with Daniel Wichs. Available at http://www.cs.au.dk/~pratyay/2-round-MPC.pdf
Taming Uncertainty, Scale, and Change: A Programming Language Perspective
Suresh Jagannathan, Purdue University
Thursday, April 23, 2015 at 3:00pm in Hariri 180
Abstract: The modern-day software ecosystem is a messy and chaotic one. Among other things, it includes an intricate stack of sophisticated services and components, susceptible to frequent (and often incompatible) upgrades and patches; emerging applications that operate over large, unstructured, and noisy data; and, an ever growing code base replete with latent defects and redundancies. Devising novel techniques to tame this complexity, and improve software resilience, trustworthiness, and expressivity in the process, is a common theme actively being explored by several ongoing DARPA programs. This talk gives an overview of three such efforts - PPAML (Probabilistic Programming Advancing Machine Learning), MUSE (Mining and Understanding Software Enclaves), and BRASS (Building Resource Adaptive Software Systems). These programs have seemingly disparate goals - PPAML seeks to democratize machine learning through the use of probabilistic programming abstractions; MUSE aims to exploit predictive analytics over large software corpora to repair and synthesize programs; and, BRASS is concerned with devising self-adaptive software capable of automatically responding to changes in its operating environment. Despite their outward differences, however, all three programs nonetheless critically rely on common foundational advances in programming language design, analysis, and implementation to realize their vision, and share an overarching goal to revolutionize the way we think about software construction and reliability.
Bio: Suresh Jagannathan joined the Information Innovation Office (I2O) at DARPA as a Program Manager in 2013. He is currently on leave from Purdue University where is a Professor of Computer Science. He has been a visiting faculty scholar at Cambridge University, and prior to joining Purdue, was a Senior Research Scientist at the NEC Research Institute. His interests are in programming languages generally, with specific interests in program verification and analysis, concurrent and distributed systems, functional programming, and compiler design. He received his Ph.D from MIT.
Secure Integrated Circuit (IC) Fabrication Using Obfuscation
Siddharth Garg, NYU Poly
Wednesday, April 29, 2015 at 10:00pm in Hariri 180
Abstract: For economic reasons, the fabrication of digital ICs is increasingly outsourced. This comes at the expense of trust - the untrusted fabrication facility ("foundry") could pirate the intellectual property of the IC designer, or worse, maliciously modify the IC to leak secret information from the chip or sabotage its functionality.
In this talk, I will present my recent work on two defense mechanisms based on hardware obfuscation to secure computer hardware against such attacks. The first is split manufacturing, which enables a designer to partition a digital circuit across multiple chips, fabricate each separately, and "glue" them together after fabrication. Since each foundry only sees a part of the netlist, its ability to infer the design intent is hindered. I will propose a quantitative notion of security for split manufacturing and explore the resulting cost-security trade-offs.
In the second part of the talk, I will discuss another defense mechanism - IC camouflaging. IC camouflaging allows for the Boolean functionality of a gate to be hidden from the attacker. Previous work indicates that if a carefully selected subset of gates in the netlist is camouflaged, an attacker is forced to use a "brute-force search" to decamouflage the circuit. I will present an attack that demonstrates that IC camouflaging is, in fact, less effective than previously thought. I will conclude with some preliminary thoughts on provably secure IC fabrication and how it relates to the foundational work on function obfuscation.
The Design and Use of MIT Sloop Retrieval Engine for Animal Biometrics
Sai Ravela, MIT
Thursday, April 23, 2015 at 4:00 pm in MCS B29
Abstract: Identifying individuals in photographs of animals collected over time is a non-invasive approach for ecological monitoring and conservation. This paper describes the design and use of Sloop (sloop.mit.edu), for animal biometrics incorporating crowd-sourced relevance feedback. Sloop's iterative retrieval strategy using hierarchical and aggregated matching and relevance feedback consistently improves deformation and correspondence-based approaches across several species. Its crowdsourcing strategy is successful in utilizing relevance feedback on a large scale. Sloop is in operational use. The user experience and results are presented here to facilitate the creation of a community-based ecological informatics system for conservation planning.
Bio: Sai Ravela directs the Earth Signals and Systems Group (ESSG) in the Earth, Atmospheric and Planetary Sciences at the Massachusetts Institute of Technology. His primary research interests are in stochastic systems science with application to Earth, Atmospheric and Planetary Sciences. He conducts this research through various projects including Autonomous Observation (caos.mit.edu), Animal Biometrics (sloop.mit.edu), Fluid Imaging (flux.mit.edu), Statistical Inference for Coherent Fluids (stics.mit.edu) and Hurricane Risk(hazmet.mit.edu). Dr. Ravela completed a PostDoc in Atmospheric Science and Stochastic Systems from MIT in 2004, and received a PhD in 2003 in Computer Science from the University of Massachusetts at Amherst, specializing in Computer Vision, Multimedia Retrieval and Robotics. He is the co-founder of Windrisktech LLC, a company that uses Learning and Physics to quantify risk from hurricanes, and E5 Aerospace LLC, that builds novel designs of aircraft systems for autonomous observation.
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