5 Pages

kent___a199714666e6a

Course: PM 1, Fall 2009
School: BU
Rating:
 
 
 
 
 

Word Count: 1385

Document Preview

quant-ph/9711025 Unconditionally DAMTP/97-124 Secure All-Or-Nothing Disclosure of Secrets Adrian Kent Department of Applied Mathematics and Theoretical Physics, University of Cambridge, quant-ph/9711025 v2 20 Nov 1997 Silver Street, Cambridge CB3 9EW, U.K. Abstract Alice has n secrets which she regards as equally valuable. She is willing to sell any of them to Bob, but wants to ensure that if he pays for only...

Register Now

Unformatted Document Excerpt

Coursehero >> Massachusetts >> BU >> PM 1

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
quant-ph/9711025 Unconditionally DAMTP/97-124 Secure All-Or-Nothing Disclosure of Secrets Adrian Kent Department of Applied Mathematics and Theoretical Physics, University of Cambridge, quant-ph/9711025 v2 20 Nov 1997 Silver Street, Cambridge CB3 9EW, U.K. Abstract Alice has n secrets which she regards as equally valuable. She is willing to sell any of them to Bob, but wants to ensure that if he pays for only one secret he cannot obtain any information about the others. Bob would like to buy one of the secrets from Alice, but wants to ensure that Alice can obtain no information about which of her secrets he has obtained. The aim of an all-or-nothing disclosure of secrets cryptographic protocol is to allow Alice and Bob to satisfy these supercially irreconcilable wishes. We show that such a protocol can be carried out securely by using quantum information. The protocol can be modied to implement oblivious transfers in which Bob receives a secret randomly chosen from the n. PACS numbers: 03.65.Bz, 42.50.Dv, 89.70.+c Electronic address: apak@damtp.cam.ac.uk 1. Introduction Carrying out cryptographic tasks using quantum states has the advantage that an attempt to extract information generally irreversibly disturbs a quantum state. Secure protocols for quantum key distribution[1,2] have been known for some time, and secure protocols for quantum bit commitment[3] and multi-party quantum computation[4] are also known. To illustrate another interesting cryptographic task, consider the following situation. Alice has n secrets which she regards as equally valuable: let us say that they are wellresearched predictions of the outlooks for various company stocks. She is willing to sell any of them to Bob, but wants to ensure that if he pays for only one secret he cannot obtain any information about the others. Bob would like to buy one of the secrets from Alice, but wants to ensure that Alice can obtain no information about which of her secrets he has obtained: he is interested in purchasing one of the stocks, and does not want it known which one. What cryptographers refer to as an unconditionally secure all-or-nothing disclosure of secrets protocol[5] allows Alice and Bob to satisfy these apparently irreconcilable wishes. Alice can be sure, with probability arbitrarily close to one, that Bob has obtained arbitrarily little information about any of the secrets other than the one he chose. Bob can be sure, with probability arbitrarily close to one, that Alice has obtained arbitrarily little information as to which secret he has obtained. We show that here that an unconditionally secure all-or-nothing disclosure of secrets protocol can be implemented by the exchange of quantum information. 2. All-or-nothing disclosure of secrets protocol To avoid any possibility of Alice misrepresenting the signicance of her secrets to Bob, let us suppose that they take the form of answers to well-dened questions: What will be the closing price of ABC Corp stock on Friday?, Who were the eight largest donors to the Cimmerian New Democracy Party last year?, What are the factors of (some xed large number) M ?, and so forth. The protocol works by exchange of qubits, for which Alice and Bob x a standard basis |0 , |1 . Bob chooses a positive integer r, and Alice a large positive integer N. Alice rst translates all of her secrets into binary numbers, using some agreed cipher (such as ASCII). She works out which is the longest, and makes all the others the same length, by using some agreed stop code and then adding zeroes. They then carry out a sub-protocol, which will be repeated N times. Alice creates a string of qubits for each secret, redundantly coding each binary 0 and 1 into a sub-string of r qubits, all in state |0 or all in state |1 . She then encodes every qubit in each of the n secret strings, by applying independent random rotations chosen from the list I, U, U 2 , U 3 , where U= 1 2 1 2 1 2 1 2 . (1) She bit commits these rotations to Bob, using a secure quantum bit commitment protocol.[3] She repeats these operations a total of n times. She then sends Bob a block of the n2 encoded strings, in sub-blocks of n, labelled in sequence so that he knows which is string supposed to correspond to which secret. Bob randomly chooses some permutation of {1, . . . , n}. He carries out von Neumann measurements in the |0 , |1 basis on every qubit in the (i)-th string from the i-th subblock, for each i from 1 to n. He then applies independent random unitary operations, chosen from the list I, J, R, J R, where J= 1 0 0 1 , R= 0 1 1 0 , (2) to every one of the measurement qubits, and to every qubit in each of the other strings. He bit commits to Alice the details of these operations: which strings he measured, what the results were, and which operations he applied to each qubit in each string. He then returns all the strings of qubits to Alice, again labelled in sequence. Alice and Bob repeat this part of the protocol N times, making independent random choices each time. Alice then chooses any N 1 of the blocks and asks Bob to unveil his bit commitments for these. She checks that all of the qubits returned to her from these blocks are in states consistent with Bobs claims, and that the measurement statistics Bob claims are consistent with the states she supplied. If Bobs claims fail these tests, she abandons the protocol, having given nothing away. If Bobs claims pass the tests, she accepts that Bob has been following the protocol faithfully, and in particular that he is carrying out measurements on precisely one string from each block or at least that his deviations from the protocol are so slight as to give him negligible illicit information. Her choice of N was such as to give her adequate statistical condence in these beliefs. If Alice is convinced that Bob is following the protocol, she then allows him to choose any one sub-block from the last remaining block. For that sub-block, she unveils all of her bit committed rotations to Bob. If Bob wants to know the i-th secret, he chooses the 1 (i)-th sub-block. He then reads o the secret from his measurement results, being able to distinguish a 0 from a 1 very accurately, despite the fact that half of the qubits are rotated into states orthogonal to his measurement basis, because of the r-fold redundancy of the coding. Alice is unable to tell which secret Bob has obtained, since he does not reveal his random unitary operations on this last block. Whatever states she actually supplied to Bob even if she deviated from the protocol by sending entangled states the qubits returned to her give her no information. 3. Comments The protocol can easily be modied to implement the related cryptographic ...

Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

BU - DCC - 2
BU - DCC - 2
BU - DCC - 2
Edward A. Nardell, MD Associate Professor of Medicine Harvard Medical School Tuberculosis Control Officer Massachusetts Department of Public Health President, International Union Against Tuberculosis and Lung Disease, North American RegionComments
BU - LX - 502
CAS LX 502 Semantics3a. A formalism for meaning (contd) 3.2, 3.6Recap!F1 = Rules for generating and interpreting a small fragment of English.!Syntax: Phrase structure rules! !Reviewed on the next slide Idea: All and only sentences generat
BU - LX - 502
CAS LX 502 Semantics2b. A formalism for meaning 2.5, 3.2, 3.6Truth and meaning!The basis of formal semantics: knowing the meaning of a sentence is knowing under what conditions it is true.!Formal semantics, a.k.a. truth conditional semantics
BU - LX - 502
CAS LX 502 Semantics8a. Sense, reference, intension, extension, modality 5.1-2,3-4;7The topic of the class!Weve spent a fair amount of time talking about how we can build up an understanding of the meanings of sentence (or at least the truth co
BU - LX - 502
Your dog ate my homework.CAS LX 5021a. Introduction What does this sentence mean? Is it true? What is the current status of my homework? What was the prior status of my homework? Your dog will have eaten my homework. Your dog must have eat
Pittsburgh - CS - 2740
University of Pittsburgh CS 2740 Knowledge Representation Professor Milos HauskrechtHandout 2 September 10, 2008Problem assignment 1Due: Wednesday, September 17, 2008LispThe goal of this assignment is to practice your lisp programming skills
Pittsburgh - CS - 441
CS 441 Discrete Mathematics for CS Lecture 11Sets and set operationsMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 441 Discrete mathematics for CSM. HauskrechtCourse administrationHomework 3: Due today Homework 4: Due next week
Pittsburgh - CS - 2740
CS 2740 Knowledge Representation Lecture 4Propositional logicMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 2740 Knowledge RepresentationM. HauskrechtAdministration Homework assignment 1 is out Due next week on Wednesday, Septem
Pittsburgh - CS - 441
CS 441 Discrete Mathematics for CS Lecture 8Methods of ProofMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 441 Discrete mathematics for CSM. HauskrechtCourse administration Homework 1 and Homework 2: Due today Homework 3 out to
Pittsburgh - CS - 1571
CS 1571 Introduction to AI Lecture 13Propositional logicMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 1571 Intro to AIM. HauskrechtAnnouncements Homework assignment 5 is out Midterm exam: Wednesday, October 25, 2006 Course web p
Pittsburgh - CS - 3750
Probabilistic Principal Component Analysis and the E-M algorithmThe Minh Luong CS 3750 October 23, 2007Outline Probabilistic Principal Component Analysis Latent variable models Probabilistic PCA Formulation of PCA model Maximum likelihood est
Pittsburgh - CS - 441
CS 441 Discrete Mathematics for CS Lecture 19Summations, CardinalityMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 441 Discrete mathematics for CSM. HauskrechtCourse administration Homework 5 is due today Homework 6 is out Due o
Pittsburgh - CS - 2740
University of Pittsburgh CS 2740 Knowledge Representation Professor Milos HauskrechtHandout 5 October 1, 2008Problem assignment 4Due: Wednesday, October 8, 2008UnicationThe unication process in FOL aims to nd the most general substitution tha
Pittsburgh - CS - 2740
CS 2740 Knowledge representation Lecture 1Knowledge representationMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 2740 Knowledge representationM. HauskrechtCourse administrationInstructor: Milos Hauskrecht 5329 Sennott Square milo
Pittsburgh - CS - 3750
CS 3750 Machine Learning Lecture 11Monte Carlo inferenceMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 3750 Advanced Machine LearningMarkov chain Monte Carlo Likelihood weighting: samples are generated according to Q and every sampl
Pittsburgh - CS - 2710
CS 2710 Foundations of AI Lecture 8Adversarial searchMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 2710 Foundations of AIGame search Game-playing programs developed by AI researchers since the beginning of the modern AI era Progr
Pittsburgh - CS - 1571
CS 1571 Introduction to AI Lecture 12Adversarial searchMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 1571 Intro to AIM. HauskrechtAnnouncements Homework assignment 4 is out Programming and experiments Simulated annealing + Gen
Pittsburgh - MAY - 2005
FEATUREAN EDITOR ON A MISSION BY JESSICA MESMANSO YOU WANT TOCHANGETHE WORLD?HSome people might say Ive reached a point in my life where Im not afraid. But Ive never been afraid, says Catherine DeAngelis.PHOTOGRAPHY |ere comes Dr. De, h
Pittsburgh - EXP - 1593
Pittsburgh - EXP - 1652
Internet WavesDisruptive Technologies> Cool ToolsDigging Digsby and Tweeting Locally> Database ReviewSmart Search Engines Find Best Facts Page 26Page 19Page 41iJune 2008Vol. 25 I Issue 6The Newspaper for Users and Producers of Elect
Pittsburgh - SIS - 793
MARLA MISEKMirror Image InternetThrough the Looking GlassIike the heroine of Lewis Carroll's Alice's Adventures in Wotiderland, who finds herself in a fantastical place where things are not always as they seem, Intemet users generally have no
Pittsburgh - EXP - 793
MARLA MISEKMirror Image InternetThrough the Looking GlassIike the heroine of Lewis Carroll's Alice's Adventures in Wotiderland, who finds herself in a fantastical place where things are not always as they seem, Intemet users generally have no
Pittsburgh - SIS - 1821
BUILDING COMMUNITY AS A LIBRARY IN A 3D ENVIRONMENTKelly Czarnecki Technology education librarianPublic Library of Charlotte and Mecklenburg County North CarolinaUSA Received January2008It is predicted in a recent reportby GartnerInc that '80% of a
Pittsburgh - EXP - 1821
BUILDING COMMUNITY AS A LIBRARY IN A 3D ENVIRONMENTKelly Czarnecki Technology education librarianPublic Library of Charlotte and Mecklenburg County North CarolinaUSA Received January2008It is predicted in a recent reportby GartnerInc that '80% of a
Pittsburgh - EXP - 325
CLICK FIRST, ASK QUESTIONS LATER: UNDERSTANDING TEEN ONLINE BEHAVIOURJack Goodman CEO Tutoring AustralasiaExamined are how teenagers engage with technology, particularly the internet; what services, sites and programs they find compelling; and how
Pittsburgh - EXP - 335
Pittsburgh - SIS - 1590
Pittsburgh - EXP - 1590
Pittsburgh - SIS - 1834
Social Networking Mixes the Hip with the Proven"THIS YEAR'S EXPLOSIVE GROWTH IN SOCIAL SOFTWARE REMINDS ME OF SHAKESPEARE'S FAMOUS LINE FROM THE TEMPEST, 'WHAT IS PAST IS PROLOGUE."' When Computers in Librariestakes up K. H UVWE the topic of Hip Hig
Pittsburgh - EXP - 1834
Social Networking Mixes the Hip with the Proven"THIS YEAR'S EXPLOSIVE GROWTH IN SOCIAL SOFTWARE REMINDS ME OF SHAKESPEARE'S FAMOUS LINE FROM THE TEMPEST, 'WHAT IS PAST IS PROLOGUE."' When Computers in Librariestakes up K. H UVWE the topic of Hip Hig
Pittsburgh - EXP - 602
Chapter 5Social VideoVideoblogging & YouTuben the past year, viewing and creating video for the Web skyrocketed to the top of many Internet users' lists. The popularity of YouTube, Google Video, and other sharing sites, coupled with the ease of
Pittsburgh - EXP - 116
3 6 I InformationTodayApril 2007www.lntotocfav.coniwww.infotoday.com/linkupYour Personal Guide 1 0 t:he V\#eb :omeA 'del.icio.us' Way to Use Bookmarksregister With del.icio.usby THOMAS PACKThe Folksonomic ApproachEDITED BYLoRAiNF P
Pittsburgh - EXP - 228
practice & researchblogging for beginnersCan the blogging phenomenon offer anything to people with learning disabilities? Yes, says Denise Stokes, who co-ordinates a pioneering group based in CoventryKeywords comrriLinication information techno
Pittsburgh - EXP - 1654
IOWWW.IWR.CO.UK/INFOTECHSOCIAL COMPUTING WITHOUT TEARSReluctant IT departments are playing it safe with social networking, but that could all be about to change, as David Tebbutt explainsfew months ago the IWR blog carried a post about nast\- goi
Pittsburgh - CIDDEFALL - 02
Media IN and FOR the Language Class Presenter: Zsuzsa HorvthIntroductionSponsored by CIDDE Supported by the Robert Henderson Language Media CenterMedia and Technology in the ClassroomRoom with media service: - pick up key (Instructional Media Se
Pittsburgh - TECHWORKSH - 01
Stacks, Buttons, Fields, and Cards in HyperCardCreating New Stacks Find the icon for "Home" or "HyperCard" and double-click on it.If you are on the first card of the Home stack the upper left portion of your screen probably looks something like t
Pittsburgh - TECHWORKSH - 01
1. Basic Hypercard InformationCommands Which Are Used in Almost All Macintosh Programs Command key: (on either side of the Space Bar)+Q +N +O +W +S +Z +X +C +V +PQuit from a program New file (inside Hypercard: "New card") Open file or program (d
Pittsburgh - SUPER - 7
Administrative Issues in Outbreak InvestigationsOR.How to Optimize Your 15 Minutes of FameM. Joan Mallick, R.N., Ph.D.Part AGetting to Know the Media Before an Emergency StrikesBackgroundA The anthrax "outbreak" of 2001 brought theissue
Wisc Stevens Point - ED - 362
Classroom RulesClassroom rules will be set by the students, but guided by the three teachers around five core values: Body Basics, Honesty, Respect, Responsibility, and Caring. Once the students have created rules that they can agree on, the three t
Pittsburgh - LASA - 97
Better Workers, Better Wives: Vocational Education for Poor Women in Turn-of-the-Century Chile1by Elizabeth Quay Hutchison Colby CollegePrepared for delivery at the 1997 Meeting of the Latin American Studies Association, Continental Plaza Hotel,
BU - SPG - 06
NBER WORKING PAPER SERIESABORTION AND SELECTION Elizabeth Oltmans Ananat Jonathan Gruber Phillip B. Levine Douglas Staiger Working Paper 12150 http:/www.nber.org/papers/w12150 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge
BU - PDFFALL - 07
R&D and productivity: Estimating production functions when productivity is endogenousUlrich Doraszelski Harvard University and CEPR Jordi Jaumandreu Universidad Carlos III and CEPRApril 2007 Preliminary and incomplete. Comments very welcome.Abst
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
BU - ELBAZ - 1
Pittsburgh - LASA - 98
How U.S. Students Perceive Cuba: A Current Cultural ExperienceAviva Chomsky History Department Salem State College Salem, MA 01970 978-542-6389 achomsky@salem.mass.eduPrepared for delivery at the 1998 meeting of the Latin American Studies Associa
Pittsburgh - CS - 1550
Outline of this class How to submit your assignment? A few examples Install NachOS for second assignmentusemainsimple.c usestring.c usefork.c useexecvp.c~jrmst106/public/1550Synch.pl1
Pittsburgh - CS - 2750
CS 2750 Machine Learning Lecture 13Multi-way classificationMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 2750 Machine LearningAdministrative announcementsHomework 6 due on Wednesday Plan for the upcoming month: Homework 7 due on
Pittsburgh - CS - 2750
CS 2750 Machine Learning Lecture 12Nave Bayes classifier & Evaluation frameworkMilos Hauskrecht milos@cs.pitt.edu 5329 Sennott SquareCS 2750 Machine LearningGenerative approach to classificationIdea: 1. Represent and learn the distribution p