Verifiable Random Functions
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Reproducibility and Pseudo-Determinism in Log-Space
Reproducibility and Pseudo-determinism in Log-Space by Ofer Grossman S.B., Massachusetts Institute of Technology (2017) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering and Computer Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY May 2020 c Massachusetts Institute of Technology 2020. All rights reserved. Author...................................................................... Department of Electrical Engineering and Computer Science May 15, 2020 Certified by.................................................................. Shafi Goldwasser RSA Professor of Electrical Engineering and Computer Science Thesis Supervisor Accepted by................................................................. Leslie A. Kolodziejski Professor of Electrical Engineering and Computer Science Chair, Department Committee on Graduate Students 2 Reproducibility and Pseudo-determinism in Log-Space by Ofer Grossman Submitted to the Department of Electrical Engineering and Computer Science on May 15, 2020, in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering and Computer Science Abstract Acuriouspropertyofrandomizedlog-spacesearchalgorithmsisthattheiroutputsareoften longer than their workspace. This leads to the question: how can we reproduce the results of a randomized log space computation without storing the output or randomness verbatim? Running the algorithm again with new -
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing 234 Able Quantity
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing 234 able quantity. Only a limited number of previous works which can provide a natural and interpretable guide- [29, 34, 35] have investigated the question of how to line for selecting proper privacy parameters by system select a proper value of ǫ, but these approaches ei- designers and researchers. Furthermore, we extend our ther require complicated economic models or lack the analysis on unbounded DP to bounded DP and the ap- analysis of adversaries with arbitrary auxiliary informa- proximate (ǫ, δ)-DP. tion (see Section 2.3 for more details). Our work is in- Impact of Auxiliary Information. The conjecture spired by the interpretation of differential privacy via that auxiliary information can influence the design of hypothesis testing, initially introduced by Wasserman DP mechanisms has been made in prior work [8, 28, 32, and Zhou [27, 30, 60]. However, this interpretation has 33, 39, 65]. We therefore investigate the adversary’s ca- not been systematically investigated before in the con- pability based on hypothesis testing under three types text of our research objective, i.e., reasoning about the of auxiliary information: the prior distribution of the in- choice of the privacy parameter ǫ (see Section 2.4 for put record, the correlation across records, and the corre- more details). lation across time. Our analysis demonstrates that the We consider hypothesis testing [2, 45, 61] as the tool auxiliary information indeed influences the appropriate used by the adversary to infer sensitive information of selection of ǫ. The results suggest that, when possible an individual record (e.g., the presence or absence of and available, the practitioners of DP should explicitly a record in the database for unbounded DP) from the incorporate adversary’s auxiliary information into the outputs of privacy mechanisms. -
Fault-Tolerant Distributed Computing in Full-Information Networks
Fault-Tolerant Distributed Computing in Full-Information Networks Shafi Goldwasser∗ Elan Pavlov Vinod Vaikuntanathan∗ CSAIL, MIT MIT CSAIL, MIT Cambridge MA, USA Cambridge MA, USA Cambridge MA, USA December 15, 2006 Abstract In this paper, we use random-selection protocols in the full-information model to solve classical problems in distributed computing. Our main results are the following: • An O(log n)-round randomized Byzantine Agreement (BA) protocol in a synchronous full-information n network tolerating t < 3+ faulty players (for any constant > 0). As such, our protocol is asymp- totically optimal in terms of fault-tolerance. • An O(1)-round randomized BA protocol in a synchronous full-information network tolerating t = n O( (log n)1.58 ) faulty players. • A compiler that converts any randomized protocol Πin designed to tolerate t fail-stop faults, where the n source of randomness of Πin is an SV-source, into a protocol Πout that tolerates min(t, 3 ) Byzantine ∗ faults. If the round-complexity of Πin is r, that of Πout is O(r log n). Central to our results is the development of a new tool, “audited protocols”. Informally “auditing” is a transformation that converts any protocol that assumes built-in broadcast channels into one that achieves a slightly weaker guarantee, without assuming broadcast channels. We regard this as a tool of independent interest, which could potentially find applications in the design of simple and modular randomized distributed algorithms. ∗Supported by NSF grants CNS-0430450 and CCF0514167. 1 1 Introduction The problem of how n players, some of who may be faulty, can make a common random selection in a set, has received much attention. -
2008 Annual Report
2008 Annual Report NATIONAL ACADEMY OF ENGINEERING ENGINEERING THE FUTURE 1 Letter from the President 3 In Service to the Nation 3 Mission Statement 4 Program Reports 4 Engineering Education 4 Center for the Advancement of Scholarship on Engineering Education 6 Technological Literacy 6 Public Understanding of Engineering Developing Effective Messages Media Relations Public Relations Grand Challenges for Engineering 8 Center for Engineering, Ethics, and Society 9 Diversity in the Engineering Workforce Engineer Girl! Website Engineer Your Life Project Engineering Equity Extension Service 10 Frontiers of Engineering Armstrong Endowment for Young Engineers-Gilbreth Lectures 12 Engineering and Health Care 14 Technology and Peace Building 14 Technology for a Quieter America 15 America’s Energy Future 16 Terrorism and the Electric Power-Delivery System 16 U.S.-China Cooperation on Electricity from Renewables 17 U.S.-China Symposium on Science and Technology Strategic Policy 17 Offshoring of Engineering 18 Gathering Storm Still Frames the Policy Debate 20 2008 NAE Awards Recipients 22 2008 New Members and Foreign Associates 24 2008 NAE Anniversary Members 28 2008 Private Contributions 28 Einstein Society 28 Heritage Society 29 Golden Bridge Society 29 Catalyst Society 30 Rosette Society 30 Challenge Society 30 Charter Society 31 Other Individual Donors 34 The Presidents’ Circle 34 Corporations, Foundations, and Other Organizations 35 National Academy of Engineering Fund Financial Report 37 Report of Independent Certified Public Accountants 41 Notes to Financial Statements 53 Officers 53 Councillors 54 Staff 54 NAE Publications Letter from the President Engineering is critical to meeting the fundamental challenges facing the U.S. economy in the 21st century. -
Concurrent Non-Malleable Zero Knowledge Proofs
Concurrent Non-Malleable Zero Knowledge Proofs Huijia Lin?, Rafael Pass??, Wei-Lung Dustin Tseng???, and Muthuramakrishnan Venkitasubramaniam Cornell University, {huijia,rafael,wdtseng,vmuthu}@cs.cornell.edu Abstract. Concurrent non-malleable zero-knowledge (NMZK) consid- ers the concurrent execution of zero-knowledge protocols in a setting where the attacker can simultaneously corrupt multiple provers and ver- ifiers. Barak, Prabhakaran and Sahai (FOCS’06) recently provided the first construction of a concurrent NMZK protocol without any set-up assumptions. Their protocol, however, is only computationally sound (a.k.a., a concurrent NMZK argument). In this work we present the first construction of a concurrent NMZK proof without any set-up assump- tions. Our protocol requires poly(n) rounds assuming one-way functions, or O~(log n) rounds assuming collision-resistant hash functions. As an additional contribution, we improve the round complexity of con- current NMZK arguments based on one-way functions (from poly(n) to O~(log n)), and achieve a near linear (instead of cubic) security reduc- tions. Taken together, our results close the gap between concurrent ZK protocols and concurrent NMZK protocols (in terms of feasibility, round complexity, hardness assumptions, and tightness of the security reduc- tion). 1 Introduction Zero-knowledge (ZK) interactive proofs [GMR89] are fundamental constructs that allow the Prover to convince the Verifier of the validity of a mathematical statement x 2 L, while providing zero additional knowledge to the Verifier. Con- current ZK, first introduced and achieved by Dwork, Naor and Sahai [DNS04], considers the execution of zero-knowledge protocols in an asynchronous and con- current setting. -
Digital Communication Systems 2.2 Optimal Source Coding
Digital Communication Systems EES 452 Asst. Prof. Dr. Prapun Suksompong [email protected] 2. Source Coding 2.2 Optimal Source Coding: Huffman Coding: Origin, Recipe, MATLAB Implementation 1 Examples of Prefix Codes Nonsingular Fixed-Length Code Shannon–Fano code Huffman Code 2 Prof. Robert Fano (1917-2016) Shannon Award (1976 ) Shannon–Fano Code Proposed in Shannon’s “A Mathematical Theory of Communication” in 1948 The method was attributed to Fano, who later published it as a technical report. Fano, R.M. (1949). “The transmission of information”. Technical Report No. 65. Cambridge (Mass.), USA: Research Laboratory of Electronics at MIT. Should not be confused with Shannon coding, the coding method used to prove Shannon's noiseless coding theorem, or with Shannon–Fano–Elias coding (also known as Elias coding), the precursor to arithmetic coding. 3 Claude E. Shannon Award Claude E. Shannon (1972) Elwyn R. Berlekamp (1993) Sergio Verdu (2007) David S. Slepian (1974) Aaron D. Wyner (1994) Robert M. Gray (2008) Robert M. Fano (1976) G. David Forney, Jr. (1995) Jorma Rissanen (2009) Peter Elias (1977) Imre Csiszár (1996) Te Sun Han (2010) Mark S. Pinsker (1978) Jacob Ziv (1997) Shlomo Shamai (Shitz) (2011) Jacob Wolfowitz (1979) Neil J. A. Sloane (1998) Abbas El Gamal (2012) W. Wesley Peterson (1981) Tadao Kasami (1999) Katalin Marton (2013) Irving S. Reed (1982) Thomas Kailath (2000) János Körner (2014) Robert G. Gallager (1983) Jack KeilWolf (2001) Arthur Robert Calderbank (2015) Solomon W. Golomb (1985) Toby Berger (2002) Alexander S. Holevo (2016) William L. Root (1986) Lloyd R. Welch (2003) David Tse (2017) James L. -
FOCS 2005 Program SUNDAY October 23, 2005
FOCS 2005 Program SUNDAY October 23, 2005 Talks in Grand Ballroom, 17th floor Session 1: 8:50am – 10:10am Chair: Eva´ Tardos 8:50 Agnostically Learning Halfspaces Adam Kalai, Adam Klivans, Yishay Mansour and Rocco Servedio 9:10 Noise stability of functions with low influences: invari- ance and optimality The 46th Annual IEEE Symposium on Elchanan Mossel, Ryan O’Donnell and Krzysztof Foundations of Computer Science Oleszkiewicz October 22-25, 2005 Omni William Penn Hotel, 9:30 Every decision tree has an influential variable Pittsburgh, PA Ryan O’Donnell, Michael Saks, Oded Schramm and Rocco Servedio Sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing 9:50 Lower Bounds for the Noisy Broadcast Problem In cooperation with ACM SIGACT Navin Goyal, Guy Kindler and Michael Saks Break 10:10am – 10:30am FOCS ’05 gratefully acknowledges financial support from Microsoft Research, Yahoo! Research, and the CMU Aladdin center Session 2: 10:30am – 12:10pm Chair: Satish Rao SATURDAY October 22, 2005 10:30 The Unique Games Conjecture, Integrality Gap for Cut Problems and Embeddability of Negative Type Metrics Tutorials held at CMU University Center into `1 [Best paper award] Reception at Omni William Penn Hotel, Monongahela Room, Subhash Khot and Nisheeth Vishnoi 17th floor 10:50 The Closest Substring problem with small distances Tutorial 1: 1:30pm – 3:30pm Daniel Marx (McConomy Auditorium) Chair: Irit Dinur 11:10 Fitting tree metrics: Hierarchical clustering and Phy- logeny Subhash Khot Nir Ailon and Moses Charikar On the Unique Games Conjecture 11:30 Metric Embeddings with Relaxed Guarantees Break 3:30pm – 4:00pm Ittai Abraham, Yair Bartal, T-H. -
An Economic Analysis of Privacy Protection and Statistical Accuracy As Social Choices
An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices John M. Abowd and Ian M. Schmutte August 15, 2018 Forthcoming in American Economic Review Abowd: U.S. Census Bureau HQ 8H120, 4600 Silver Hill Rd., Washington, DC 20233, and Cornell University, (email: [email protected]); Schmutte: Department of Eco- nomics, University of Georgia, B408 Amos Hall, Athens, GA 30602 (email: [email protected]). Abowd and Schmutte acknowledge the support of Alfred P. Sloan Foundation Grant G-2015-13903 and NSF Grant SES-1131848. Abowd acknowledges direct support from NSF Grants BCS-0941226, TC-1012593. Any opinions and conclusions are those of the authors and do not represent the views of the Census Bureau, NSF, or the Sloan Foundation. We thank the Center for Labor Economics at UC–Berkeley and Isaac Newton Institute for Mathematical Sciences, Cambridge (EPSRC grant no. EP/K032208/1) for support and hospitality. We are extremely grateful for very valuable com- ments and guidance from the editor, Pinelopi Goldberg, and six anonymous referees. We acknowl- edge helpful comments from Robin Bachman, Nick Bloom, Larry Blume, David Card, Michael Castro, Jennifer Childs, Melissa Creech, Cynthia Dwork, Casey Eggleston, John Eltinge, Stephen Fienberg, Mark Kutzbach, Ron Jarmin, Christa Jones, Dan Kifer, Ashwin Machanavajjhala, Frank McSherry, Gerome Miklau, Kobbi Nissim, Paul Oyer, Mallesh Pai, Jerry Reiter, Eric Slud, Adam Smith, Bruce Spencer, Sara Sullivan, Salil Vadhan, Lars Vilhuber, Glen Weyl, and Nellie Zhao along with seminar and conference participants at the U.S. Census Bureau, Cornell, CREST, George Ma- son, Georgetown, Microsoft Research–NYC, University of Washington Evans School, and SOLE. -
The Limits of Post-Selection Generalization
The Limits of Post-Selection Generalization Kobbi Nissim∗ Adam Smithy Thomas Steinke Georgetown University Boston University IBM Research – Almaden [email protected] [email protected] [email protected] Uri Stemmerz Jonathan Ullmanx Ben-Gurion University Northeastern University [email protected] [email protected] Abstract While statistics and machine learning offers numerous methods for ensuring gener- alization, these methods often fail in the presence of post selection—the common practice in which the choice of analysis depends on previous interactions with the same dataset. A recent line of work has introduced powerful, general purpose algorithms that ensure a property called post hoc generalization (Cummings et al., COLT’16), which says that no person when given the output of the algorithm should be able to find any statistic for which the data differs significantly from the population it came from. In this work we show several limitations on the power of algorithms satisfying post hoc generalization. First, we show a tight lower bound on the error of any algorithm that satisfies post hoc generalization and answers adaptively chosen statistical queries, showing a strong barrier to progress in post selection data analysis. Second, we show that post hoc generalization is not closed under composition, despite many examples of such algorithms exhibiting strong composition properties. 1 Introduction Consider a dataset X consisting of n independent samples from some unknown population P. How can we ensure that the conclusions drawn from X generalize to the population P? Despite decades of research in statistics and machine learning on methods for ensuring generalization, there is an increased recognition that many scientific findings do not generalize, with some even declaring this to be a “statistical crisis in science” [14]. -
The Computational Complexity of Nash Equilibria in Concisely Represented Games∗
The Computational Complexity of Nash Equilibria in Concisely Represented Games¤ Grant R. Schoenebeck y Salil P. Vadhanz August 26, 2009 Abstract Games may be represented in many di®erent ways, and di®erent representations of games a®ect the complexity of problems associated with games, such as ¯nding a Nash equilibrium. The traditional method of representing a game is to explicitly list all the payo®s, but this incurs an exponential blowup as the number of agents grows. We study two models of concisely represented games: circuit games, where the payo®s are computed by a given boolean circuit, and graph games, where each agent's payo® is a function of only the strategies played by its neighbors in a given graph. For these two models, we study the complexity of four questions: determining if a given strategy is a Nash equilibrium, ¯nding a Nash equilibrium, determining if there exists a pure Nash equilibrium, and determining if there exists a Nash equilibrium in which the payo®s to a player meet some given guarantees. In many cases, we obtain tight results, showing that the problems are complete for various complexity classes. 1 Introduction In recent years, there has been a surge of interest at the interface between computer science and game theory. On one hand, game theory and its notions of equilibria provide a rich framework for modeling the behavior of sel¯sh agents in the kinds of distributed or networked environments that often arise in computer science and o®er mechanisms to achieve e±cient and desirable global outcomes in spite of the sel¯sh behavior. -
Race in the Age of Obama Making America More Competitive
american academy of arts & sciences summer 2011 www.amacad.org Bulletin vol. lxiv, no. 4 Race in the Age of Obama Gerald Early, Jeffrey B. Ferguson, Korina Jocson, and David A. Hollinger Making America More Competitive, Innovative, and Healthy Harvey V. Fineberg, Cherry A. Murray, and Charles M. Vest ALSO: Social Science and the Alternative Energy Future Philanthropy in Public Education Commission on the Humanities and Social Sciences Reflections: John Lithgow Breaking the Code Around the Country Upcoming Events Induction Weekend–Cambridge September 30– Welcome Reception for New Members October 1–Induction Ceremony October 2– Symposium: American Institutions and a Civil Society Partial List of Speakers: David Souter (Supreme Court of the United States), Maj. Gen. Gregg Martin (United States Army War College), and David M. Kennedy (Stanford University) OCTOBER NOVEMBER 25th 12th Stated Meeting–Stanford Stated Meeting–Chicago in collaboration with the Chicago Humanities Perspectives on the Future of Nuclear Power Festival after Fukushima WikiLeaks and the First Amendment Introduction: Scott D. Sagan (Stanford Introduction: John A. Katzenellenbogen University) (University of Illinois at Urbana-Champaign) Speakers: Wael Al Assad (League of Arab Speakers: Geoffrey R. Stone (University of States) and Jayantha Dhanapala (Pugwash Chicago Law School), Richard A. Posner (U.S. Conferences on Science and World Affairs) Court of Appeals for the Seventh Circuit), 27th Judith Miller (formerly of The New York Times), Stated Meeting–Berkeley and Gabriel Schoenfeld (Hudson Institute; Healing the Troubled American Economy Witherspoon Institute) Introduction: Robert J. Birgeneau (Univer- DECEMBER sity of California, Berkeley) 7th Speakers: Christina Romer (University of Stated Meeting–Stanford California, Berkeley) and David H. -
Calibrating Noise to Sensitivity in Private Data Analysis
Calibrating Noise to Sensitivity in Private Data Analysis Cynthia Dwork1, Frank McSherry1, Kobbi Nissim2, and Adam Smith3? 1 Microsoft Research, Silicon Valley. {dwork,mcsherry}@microsoft.com 2 Ben-Gurion University. [email protected] 3 Weizmann Institute of Science. [email protected] Abstract. We continue a line of research initiated in [10, 11] on privacy- preserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function f mapping databases to reals, the so-called true answer is the result of applying f to the database. To protect privacy, the true answer is perturbed by the addition of random noise generated according to a carefully chosen distribution, and this response, the true answer plus noise, is returned to the user. Previous work focused on the case of noisy sums, in which f = P i g(xi), where xi denotes the ith row of the database and g maps database rows to [0, 1]. We extend the study to general functions f, proving that privacy can be preserved by calibrating the standard devi- ation of the noise according to the sensitivity of the function f. Roughly speaking, this is the amount that any single argument to f can change its output. The new analysis shows that for several particular applications substantially less noise is needed than was previously understood to be the case. The first step is a very clean characterization of privacy in terms of indistinguishability of transcripts. Additionally, we obtain separation re- sults showing the increased value of interactive sanitization mechanisms over non-interactive.