The BBVA Foundation Recognizes Goldwasser, Micali, Rivest and Shamir for Enabling a Secure Digital Society Thanks to Modern Cryptography
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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. -
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. -
Magic Adversaries Versus Individual Reduction: Science Wins Either Way ?
Magic Adversaries Versus Individual Reduction: Science Wins Either Way ? Yi Deng1;2 1 SKLOIS, Institute of Information Engineering, CAS, Beijing, P.R.China 2 State Key Laboratory of Cryptology, P. O. Box 5159, Beijing ,100878,China [email protected] Abstract. We prove that, assuming there exists an injective one-way function f, at least one of the following statements is true: – (Infinitely-often) Non-uniform public-key encryption and key agreement exist; – The Feige-Shamir protocol instantiated with f is distributional concurrent zero knowledge for a large class of distributions over any OR NP-relations with small distinguishability gap. The questions of whether we can achieve these goals are known to be subject to black-box lim- itations. Our win-win result also establishes an unexpected connection between the complexity of public-key encryption and the round-complexity of concurrent zero knowledge. As the main technical contribution, we introduce a dissection procedure for concurrent ad- versaries, which enables us to transform a magic concurrent adversary that breaks the distribu- tional concurrent zero knowledge of the Feige-Shamir protocol into non-black-box construc- tions of (infinitely-often) public-key encryption and key agreement. This dissection of complex algorithms gives insight into the fundamental gap between the known universal security reductions/simulations, in which a single reduction algorithm or simu- lator works for all adversaries, and the natural security definitions (that are sufficient for almost all cryptographic primitives/protocols), which switch the order of qualifiers and only require that for every adversary there exists an individual reduction or simulator. 1 Introduction The seminal work of Impagliazzo and Rudich [IR89] provides a methodology for studying the lim- itations of black-box reductions. -
Diffie and Hellman Receive 2015 Turing Award Rod Searcey/Stanford University
Diffie and Hellman Receive 2015 Turing Award Rod Searcey/Stanford University. Linda A. Cicero/Stanford News Service. Whitfield Diffie Martin E. Hellman ernment–private sector relations, and attracts billions of Whitfield Diffie, former chief security officer of Sun Mi- dollars in research and development,” said ACM President crosystems, and Martin E. Hellman, professor emeritus Alexander L. Wolf. “In 1976, Diffie and Hellman imagined of electrical engineering at Stanford University, have been a future where people would regularly communicate awarded the 2015 A. M. Turing Award of the Association through electronic networks and be vulnerable to having for Computing Machinery for their critical contributions their communications stolen or altered. Now, after nearly to modern cryptography. forty years, we see that their forecasts were remarkably Citation prescient.” The ability for two parties to use encryption to commu- “Public-key cryptography is fundamental for our indus- nicate privately over an otherwise insecure channel is try,” said Andrei Broder, Google Distinguished Scientist. fundamental for billions of people around the world. On “The ability to protect private data rests on protocols for a daily basis, individuals establish secure online connec- confirming an owner’s identity and for ensuring the integ- tions with banks, e-commerce sites, email servers, and the rity and confidentiality of communications. These widely cloud. Diffie and Hellman’s groundbreaking 1976 paper, used protocols were made possible through the ideas and “New Directions in Cryptography,” introduced the ideas of methods pioneered by Diffie and Hellman.” public-key cryptography and digital signatures, which are Cryptography is a practice that facilitates communi- the foundation for most regularly used security protocols cation between two parties so that the communication on the Internet today. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
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. -
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. -
Party Time for Mathematicians in Heidelberg
Mathematical Communities Marjorie Senechal, Editor eidelberg, one of Germany’s ancient places of Party Time HHlearning, is making a new bid for fame with the Heidelberg Laureate Forum (HLF). Each year, two hundred young researchers from all over the world—one for Mathematicians hundred mathematicians and one hundred computer scientists—are selected by application to attend the one- week event, which is usually held in September. The young in Heidelberg scientists attend lectures by preeminent scholars, all of whom are laureates of the Abel Prize (awarded by the OSMO PEKONEN Norwegian Academy of Science and Letters), the Fields Medal (awarded by the International Mathematical Union), the Nevanlinna Prize (awarded by the International Math- ematical Union and the University of Helsinki, Finland), or the Computing Prize and the Turing Prize (both awarded This column is a forum for discussion of mathematical by the Association for Computing Machinery). communities throughout the world, and through all In 2018, for instance, the following eminences appeared as lecturers at the sixth HLF, which I attended as a science time. Our definition of ‘‘mathematical community’’ is journalist: Sir Michael Atiyah and Gregory Margulis (both Abel laureates and Fields medalists); the Abel laureate the broadest: ‘‘schools’’ of mathematics, circles of Srinivasa S. R. Varadhan; the Fields medalists Caucher Bir- kar, Gerd Faltings, Alessio Figalli, Shigefumi Mori, Bào correspondence, mathematical societies, student Chaˆu Ngoˆ, Wendelin Werner, and Efim Zelmanov; Robert organizations, extracurricular educational activities Endre Tarjan and Leslie G. Valiant (who are both Nevan- linna and Turing laureates); the Nevanlinna laureate (math camps, math museums, math clubs), and more. -
The Mathematics of the RSA Public-Key Cryptosystem Burt Kaliski RSA Laboratories
The Mathematics of the RSA Public-Key Cryptosystem Burt Kaliski RSA Laboratories ABOUT THE AUTHOR: Dr Burt Kaliski is a computer scientist whose involvement with the security industry has been through the company that Ronald Rivest, Adi Shamir and Leonard Adleman started in 1982 to commercialize the RSA encryption algorithm that they had invented. At the time, Kaliski had just started his undergraduate degree at MIT. Professor Rivest was the advisor of his bachelor’s, master’s and doctoral theses, all of which were about cryptography. When Kaliski finished his graduate work, Rivest asked him to consider joining the company, then called RSA Data Security. In 1989, he became employed as the company’s first full-time scientist. He is currently chief scientist at RSA Laboratories and vice president of research for RSA Security. Introduction Number theory may be one of the “purest” branches of mathematics, but it has turned out to be one of the most useful when it comes to computer security. For instance, number theory helps to protect sensitive data such as credit card numbers when you shop online. This is the result of some remarkable mathematics research from the 1970s that is now being applied worldwide. Sensitive data exchanged between a user and a Web site needs to be encrypted to prevent it from being disclosed to or modified by unauthorized parties. The encryption must be done in such a way that decryption is only possible with knowledge of a secret decryption key. The decryption key should only be known by authorized parties. In traditional cryptography, such as was available prior to the 1970s, the encryption and decryption operations are performed with the same key. -
Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016
Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016 HW: = Hugh Williams (Interviewer) LA = Len Adelman (ACM Turing Award Recipient) ?? = inaudible (with timestamp) or [ ] for phonetic HW: My name is Hugh Williams. It is the 18th day of August in 2016 and I’m here in the Lincoln Room of the Law Library at the University of Southern California. I’m here to interview Len Adleman for the Turing Award winners’ project. Hello, Len. LA: Hugh. HW: I’m going to ask you a series of questions about your life. They’ll be divided up roughly into about three parts – your early life, your accomplishments, and some reminiscing that you might like to do with regard to that. Let me begin with your early life and ask you to tell me a bit about your ancestors, where they came from, what they did, say up to the time you were born. LA: Up to the time I was born? HW: Yes, right. LA: Okay. What I know about my ancestors is that my father’s father was born somewhere in modern-day Belarus, the Minsk area, and was Jewish, came to the United States probably in the 1890s. My father was born in 1919 in New Jersey. He grew up in the Depression, hopped freight trains across the country, and came to California. And my mother is sort of an unknown. The only thing we know about my mother’s ancestry is a birth certificate, because my mother was born in 1919 and she was an orphan, and it’s not clear that she ever met her parents.