Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016
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Tarjan Transcript Final with Timestamps
A.M. Turing Award Oral History Interview with Robert (Bob) Endre Tarjan by Roy Levin San Mateo, California July 12, 2017 Levin: My name is Roy Levin. Today is July 12th, 2017, and I’m in San Mateo, California at the home of Robert Tarjan, where I’ll be interviewing him for the ACM Turing Award Winners project. Good afternoon, Bob, and thanks for spending the time to talk to me today. Tarjan: You’re welcome. Levin: I’d like to start by talking about your early technical interests and where they came from. When do you first recall being interested in what we might call technical things? Tarjan: Well, the first thing I would say in that direction is my mom took me to the public library in Pomona, where I grew up, which opened up a huge world to me. I started reading science fiction books and stories. Originally, I wanted to be the first person on Mars, that was what I was thinking, and I got interested in astronomy, started reading a lot of science stuff. I got to junior high school and I had an amazing math teacher. His name was Mr. Wall. I had him two years, in the eighth and ninth grade. He was teaching the New Math to us before there was such a thing as “New Math.” He taught us Peano’s axioms and things like that. It was a wonderful thing for a kid like me who was really excited about science and mathematics and so on. The other thing that happened was I discovered Scientific American in the public library and started reading Martin Gardner’s columns on mathematical games and was completely fascinated. -
1. Course Information Are Handed Out
6.826—Principles of Computer Systems 2006 6.826—Principles of Computer Systems 2006 course secretary's desk. They normally cover the material discussed in class during the week they 1. Course Information are handed out. Delayed submission of the solutions will be penalized, and no solutions will be accepted after Thursday 5:00PM. Students in the class will be asked to help grade the problem sets. Each week a team of students Staff will work with the TA to grade the week’s problems. This takes about 3-4 hours. Each student will probably only have to do it once during the term. Faculty We will try to return the graded problem sets, with solutions, within a week after their due date. Butler Lampson 32-G924 425-703-5925 [email protected] Policy on collaboration Daniel Jackson 32-G704 8-8471 [email protected] We encourage discussion of the issues in the lectures, readings, and problem sets. However, if Teaching Assistant you collaborate on problem sets, you must tell us who your collaborators are. And in any case, you must write up all solutions on your own. David Shin [email protected] Project Course Secretary During the last half of the course there is a project in which students will work in groups of three Maria Rebelo 32-G715 3-5895 [email protected] or so to apply the methods of the course to their own research projects. Each group will pick a Office Hours real system, preferably one that some member of the group is actually working on but possibly one from a published paper or from someone else’s research, and write: Messrs. -
Single-To-Multi-Theorem Transformations for Non-Interactive Statistical Zero-Knowledge
Single-to-Multi-Theorem Transformations for Non-Interactive Statistical Zero-Knowledge Marc Fischlin Felix Rohrbach Cryptoplexity, Technische Universität Darmstadt, Germany www.cryptoplexity.de [email protected] [email protected] Abstract. Non-interactive zero-knowledge proofs or arguments allow a prover to show validity of a statement without further interaction. For non-trivial statements such protocols require a setup assumption in form of a common random or reference string (CRS). Generally, the CRS can only be used for one statement (single-theorem zero-knowledge) such that a fresh CRS would need to be generated for each proof. Fortunately, Feige, Lapidot and Shamir (FOCS 1990) presented a transformation for any non-interactive zero-knowledge proof system that allows the CRS to be reused any polynomial number of times (multi-theorem zero-knowledge). This FLS transformation, however, is only known to work for either computational zero-knowledge or requires a structured, non-uniform common reference string. In this paper we present FLS-like transformations that work for non-interactive statistical zero-knowledge arguments in the common random string model. They allow to go from single-theorem to multi-theorem zero-knowledge and also preserve soundness, for both properties in the adaptive and non-adaptive case. Our first transformation is based on the general assumption that one-way permutations exist, while our second transformation uses lattice-based assumptions. Additionally, we define different possible soundness notions for non-interactive arguments and discuss their relationships. Keywords. Non-interactive arguments, statistical zero-knowledge, soundness, transformation, one-way permutation, lattices, dual-mode commitments 1 Introduction In a non-interactive proof for a language L the prover P shows validity of some theorem x ∈ L via a proof π based on a common string crs chosen by some external setup procedure. -
1 Introduction
Logic Activities in Europ e y Yuri Gurevich Intro duction During Fall thanks to ONR I had an opp ortunity to visit a fair numb er of West Eu rop ean centers of logic research I tried to learn more ab out logic investigations and appli cations in Europ e with the hop e that my exp erience may b e useful to American researchers This rep ort is concerned only with logic activities related to computer science and Europ e here means usually Western Europ e one can learn only so much in one semester The idea of such a visit may seem ridiculous to some The mo dern world is quickly growing into a global village There is plenty of communication b etween Europ e and the US Many Europ ean researchers visit the US and many American researchers visit Europ e Neither Americans nor Europ eans make secret of their logic research Quite the opp osite is true They advertise their research From ESPRIT rep orts the Bulletin of Europ ean Asso ciation for Theoretical Computer Science the Newsletter of Europ ean Asso ciation for Computer Science Logics publications of Europ ean Foundation for Logic Language and Information publications of particular Europ ean universities etc one can get a go o d idea of what is going on in Europ e and who is doing what Some Europ ean colleagues asked me jokingly if I was on a reconnaissance mission Well sometimes a cow wants to suckle more than the calf wants to suck a Hebrew proverb It is amazing however how dierent computer science is esp ecially theoretical com puter science in Europ e and the US American theoretical -
The Growth of Cryptography
The growth of cryptography Ronald L. Rivest Viterbi Professor of EECS MIT, Cambridge, MA James R. Killian Jr. Faculty Achievement Award Lecture February 8, 2011 Outline Some pre-1976 context Invention of Public-Key Crypto and RSA Early steps The cryptography business Crypto policy Attacks More New Directions What Next? Conclusion and Acknowledgments Outline Some pre-1976 context Invention of Public-Key Crypto and RSA Early steps The cryptography business Crypto policy Attacks More New Directions What Next? Conclusion and Acknowledgments The greatest common divisor of two numbers is easily computed (using “Euclid’s Algorithm”): gcd(12; 30) = 6 Euclid – 300 B.C. There are infinitely many primes: 2, 3, 5, 7, 11, 13, . Euclid – 300 B.C. There are infinitely many primes: 2, 3, 5, 7, 11, 13, . The greatest common divisor of two numbers is easily computed (using “Euclid’s Algorithm”): gcd(12; 30) = 6 Greek Cryptography – The Scytale An unknown period (the circumference of the scytale) is the secret key, shared by sender and receiver. Euler’s Theorem (1736): If gcd(a; n) = 1, then aφ(n) = 1 (mod n) ; where φ(n) = # of x < n such that gcd(x; n) = 1. Pierre de Fermat (1601-1665) Leonhard Euler (1707–1783) Fermat’s Little Theorem (1640): For any prime p and any a, 1 ≤ a < p: ap−1 = 1 (mod p) Pierre de Fermat (1601-1665) Leonhard Euler (1707–1783) Fermat’s Little Theorem (1640): For any prime p and any a, 1 ≤ a < p: ap−1 = 1 (mod p) Euler’s Theorem (1736): If gcd(a; n) = 1, then aφ(n) = 1 (mod n) ; where φ(n) = # of x < n such that gcd(x; n) = 1. -
The RSA Algorithm
The RSA Algorithm Evgeny Milanov 3 June 2009 In 1978, Ron Rivest, Adi Shamir, and Leonard Adleman introduced a cryptographic algorithm, which was essentially to replace the less secure National Bureau of Standards (NBS) algorithm. Most impor- tantly, RSA implements a public-key cryptosystem, as well as digital signatures. RSA is motivated by the published works of Diffie and Hellman from several years before, who described the idea of such an algorithm, but never truly developed it. Introduced at the time when the era of electronic email was expected to soon arise, RSA implemented two important ideas: 1. Public-key encryption. This idea omits the need for a \courier" to deliver keys to recipients over another secure channel before transmitting the originally-intended message. In RSA, encryption keys are public, while the decryption keys are not, so only the person with the correct decryption key can decipher an encrypted message. Everyone has their own encryption and decryption keys. The keys must be made in such a way that the decryption key may not be easily deduced from the public encryption key. 2. Digital signatures. The receiver may need to verify that a transmitted message actually origi- nated from the sender (signature), and didn't just come from there (authentication). This is done using the sender's decryption key, and the signature can later be verified by anyone, using the corresponding public encryption key. Signatures therefore cannot be forged. Also, no signer can later deny having signed the message. This is not only useful for electronic mail, but for other electronic transactions and transmissions, such as fund transfers. -
Jeremiah Blocki
Jeremiah Blocki Current Position (August 2016 to present) Phone: (765) 494-9432 Assistant Professor Office: 1165 Lawson Computer Science Building Computer Science Department Email: [email protected] Purdue University Homepage: https://www.cs.purdue.edu/people/faculty/jblocki/ West Lafayette, IN 47907 Previous Positions (August 2015 - June 2016) (May 2015-August 2015) (June 2014-May 2015) Post-Doctoral Researcher Cryptography Research Fellow Post-Doctoral Fellow Microsoft Research Simons Institute Computer Science Department New England Lab (Summer of Cryptography) Carnegie Mellon University Cambridge, MA UC Berkeley Pittsburgh, PA 15213 Berkeley, CA Education Ph.D. in Computer Science, Carnegie Mellon University, 2014. Advisors: Manuel Blum and Anupam Datta. Committee: Manuel Blum, Anupam Datta, Luis Von Ahn, Ron Rivest Thesis Title: Usable Human Authentication: A Quantitative Treatment B.S. in Computer Science, Carnegie Mellon University, 2009. (3.92 GPA). Senior Research Thesis: Direct Zero-Knowledge Proofs Allen Newell Award for Excellence in Undergraduate Research Research Research Interests Passwords, Usable and Secure Password Management, Human Computable Cryptography, Password Hash- ing, Memory Hard Functions, Differential Privacy, Game Theory and Security Journal Publications 1. Blocki, J., Gandikota, V., Grigorescu, G. and Zhou, S. Relaxed Locally Correctable Codes in Computa- tionally Bounded Channels. IEEE Transactions on Information Theory, 2021. [https://ieeexplore. ieee.org/document/9417090] 2. Harsha, B., Morton, R., Blocki, J., Springer, J. and Dark, M. Bicycle Attacks Consider Harmful: Quantifying the Damage of Widespread Password Length Leakage. Computers & Security, Volume 100, 2021. [https://doi.org/10.1016/j.cose.2020.102068] 3. Chong, I., Proctor, R., Li, N. and Blocki, J. Surviving in the Digital Environment: Does Survival Processing Provide and Additional Memory Benefit to Password Generation Strategies. -
A Library of Graph Algorithms and Supporting Data Structures
Washington University in St. Louis Washington University Open Scholarship All Computer Science and Engineering Research Computer Science and Engineering Report Number: WUCSE-2015-001 2015-01-19 Grafalgo - A Library of Graph Algorithms and Supporting Data Structures Jonathan Turner This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. afalgoGr is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/~jst/doc/grafalgo. While not designed as... Read complete abstract on page 2. Follow this and additional works at: https://openscholarship.wustl.edu/cse_research Part of the Computer Engineering Commons, and the Computer Sciences Commons Recommended Citation Turner, Jonathan, "Grafalgo - A Library of Graph Algorithms and Supporting Data Structures" Report Number: WUCSE-2015-001 (2015). All Computer Science and Engineering Research. https://openscholarship.wustl.edu/cse_research/242 Department of Computer Science & Engineering - Washington University in St. Louis Campus Box 1045 - St. Louis, MO - 63130 - ph: (314) 935-6160. This technical report is available at Washington University Open Scholarship: https://openscholarship.wustl.edu/ cse_research/242 Grafalgo - A Library of Graph Algorithms and Supporting Data Structures Jonathan Turner Complete Abstract: This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. -
The Origins of Computational Complexity
The Origins of Computational Complexity Some influences of Manuel Blum, Alan Cobham, Juris Hartmanis and Michael Rabin Abstract. This paper discusses some of the origins of Computational Complexity. It is shown that they can be traced back to the late 1950’s and early 1960’s. In particular, it is investigated to what extent Manuel Blum, Alan Cobham, Juris Hartmanis, and Michael Rabin contributed each in their own way to the existence of the theory of computational complexity that we know today. 1. Introduction The theory of computational complexity is concerned with the quantitative aspects of computation. An important branch of research in this area focused on measuring the difficulty of computing functions. When studying the computational difficulty of computable functions, abstract models of computation were used to carry out algorithms. The goal of computations on these abstract models was to provide a reasonable approximation of the results that a real computer would produce for a certain computation. These abstract models of computations were usually called “machine models”. In the late 1950’s and early 1960’s, the study of machine models was revived: the blossoming world of practical computing triggered the introduction of many new models and existing models that were previously thought of as computationally equivalent became different with respect to new insights re- garding time and space complexity measures. In order to define the difficulty of functions, computational complexity measures, that were defined for all possible computations and that assigned a complexity to each terminating computation, were proposed. Depending on the specific model that was used to carry out computations, there were many notions of computational complexity. -
RON RIVEST Viterbi Professor of Computer Science, MIT's Department of Electrical Engineering and Computer Science
Feb 1st 10:30 am - noon, Newcomb Hall, South Meeting Room RON RIVEST Viterbi Professor of Computer Science, MIT's Department of Electrical Engineering and Computer Science Security of Voting Systems While running an election sounds simple, it is in fact extremely challenging. Not only are there millions of voters to be authenticated and millions of votes to be carefully collected, count- ed, and stored, there are now millions of "voting machines" containing millions of lines of code to be evaluated for security vulnerabilities. Moreover, voting systems have a unique requirement: the voter must not be given a "receipt" that would allow them to prove how they voted to some- one else---otherwise the voter could be coerced or bribed into voting a certain way. The lack of receipts makes the security of voting system much more challenging than, say, the security of banking systems (where receipts are the norm). We discuss some of the recent trends and innovations in voting systems, as well as some of the new requirements being placed upon voting systems in the U.S., and describe some promising directions for resolving the conflicts inherent in voting system requirements, including some approaches based on cryptography. Professor Rivest is the Viterbi Professor of Computer Science in MIT's Department of Electrical Engineering and Computer Science. He is a member of MIT's Computer Science and Artificial Intelligence Laboratory, and Head of its Center for Information Security and Privacy. Professor Rivest has research interests in cryptography, computer and network security, and algo- rithms. Professor Rivest is an inventor, with Adi Shamir and Len Adleman of the RSA public-key cryp- tosystem, and a co-founder of RSA Data Security. -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration. -
IACR Fellows Ceremony Crypto 2010
IACR Fellows Ceremony Crypto 2010 www.iacr.org IACR Fellows Program (°2002): recognize outstanding IACR members for technical and professional contributions that: Advance the science, technology, and practice of cryptology and related fields; Promote the free exchange of ideas and information about cryptology and related fields; Develop and maintain the professional skill and integrity of individuals in the cryptologic community; Advance the standing of the cryptologic community in the wider scientific and technical world and promote fruitful relationships between the IACR and other scientific and technical organizations. IACR Fellows Selection Committee (2010) Hugo Krawczyk (IBM Research) Ueli Maurer (IBM Zurich) Tatsuaki Okamoto (NTT research), chair Ron Rivest (MIT) Moti Yung (Google Inc and Columbia University) Current IACR Fellows Tom Berson Ueli Maurer G. Robert Jr. Blakley Kevin McCurley Gilles Brassard Ralph Merkle David Chaum Silvio Micali Don Coppersmith Moni Naor Whitfield Diffie Michael O. Rabin Oded Goldreich Ron Rivest Shafi Goldwasser Martin Hellman Adi Shamir Hideki Imai Gustavus (Gus) Simmons Arjen K. Lenstra Jacques Stern James L. Massey New IACR Fellows in 2010 Andrew Clark Ivan Damgård Yvo Desmedt Jean-Jacques Quisquater Andrew Yao Ivan Damgard IACR Fellow, 2010 For fundamental contributions to cryptography, for sustained educational leadership in cryptography, and for service to the IACR. Jean-Jacques Quisquater IACR Fellow, 2010 For basic contributions to cryptographic hardware and to cryptologic education and for