Cook-Levin Theorem. SAT is NP-complete
|
|
- Roland Ralf Maxwell
- 5 years ago
- Views:
Transcription
1 Cook-Levin Theorem SAT is NP-complete In other words SAT NP A NP A P SAT 1
2 Consider any A NP NTM N that decides A in polytime n k For any input w Σ * valid tableau of configurations 2
3 Properties of an Accepting Tableau There is exactly one symbol in each cell The first row is the ( legal ) start configuration Every subsequent row is generated legally One of these rows is an accepting configuration 3
4 Proof Idea Given N and w construct a Boolean formula that is satisfiable exactly when N has an accepting tableau on input w 4
5 Constructing the formula Define Boolean formula with variables x ijs for 1 i n k 1 j n k s State Set Tape Alphabet Delimiter Want following semantics: x ijs is T iff cell (i, j) contains symbol s for some valid accepting tableau 5
6 represent valid accepting tableau with a satisfiable Boolean formula Φ cell Φ start Φ move Φ accept where Φ cell exactly one symbol per cell Φ start legal starting configuration Φ move legal moves Φ accept legal accepting configuration 6
7 represent valid accepting tableau with Boolean formula Φcell Φstart Φmove Φaccept 7
8 represent valid tableau with a Boolean formula with components Φ cell exactly one symbol per cell for any pair (i,j) the cell contains at least one symbol the cell contains at most one symbol 8
9 represent valid tableau with a Boolean formula with components Φ cell exactly one symbol per cell Φ start legal starting configuration 9
10 represent valid accepting tableau with a Boolean formula with components Φ cell exactly one symbol per cell Φ start legal starting configuration Φ move legal moves Φ accept legal accepting configuration 10
11 Φ move legal moves represented by legal 2 x 3 windows 11
12 Claim: IF start config is valid and every 2 x 3 window is valid THEN tableau is valid all changes are legal # a b q1 b c # a q2 b c c 12
13 Claim: IF start config is valid and every 2 x 3 window is valid THEN tableau is valid all changes are legal # a b q1 b c # a q2 b c c 13
14 Claim: IF start config is valid and every 2 x 3 window is valid THEN tableau is valid all changes are legal illegal changes are prevented # a b q1 b c # a q2 b c c 14
15 Claim: IF start config is valid and every 2 x 3 window is valid THEN tableau is valid all changes are legal illegal changes are prevented # a b q1 b c # a q2 b c c 15
16 SAT is NP-complete w Σ * w A there is a valid accepting tableau constructed formula is SATISFIABLE Corollary 7.42: 3SAT is NP-complete 16
17 SUBSET-SUM is NP-complete 17
18 HAMPATH is NP-complete 18
19 SAT P P = NP 3SAT P P = NP CLIQUE P P = NP VERTEX-COVER P P = NP HAMPATH P P = NP SUBSET-SUM P P = NP 19
20 HALTTM = { M, w : M is a TM that halts on input w} 3SAT P HALTTM HALTTM is NP-hard However HALTTM is not NP-complete 20
21 NP-hard NP-complete NP P All languages 21
22 If P = NP then you can factor any Define language integer in polytime FACTOR = { x, a, b x, a, b Z FACTOR NP. and x has a factor p Z st a p b} Therefore by assumption, FACTOR P Idea: Do a binary search to determine factor by setting initial interval [1, x ] 22
23 NP-hard NP-complete NP P All languages 23
24 COMPOSITES NP Surprising fact: PRIMES P 24
25 A whirlwind tour through Modern Cryptography! 25
26 Sharing Secrets Steganography vs Cryptography 26
27 Scytale 27
28 Caesar Cipher A B C D E F G H I J K L M Z Y X V U N O P Q R S T A B C D E F G H I J K L M Z Y X V U N O P Q R S T 28
29 Cryptosystem 5 tuple (P, C, K, E, D) P: Set of all plaintext strings C: Set of all ciphertext strings K: Set of all keys called keyspace E: Set of all encryption functions; each indexed by a key E k E D: Set of all decryption functions; each indexed by a key D k D k K p P Dk( Ek (p)) = p 29
30 Shift Ciphers English alphabet represented by Z26 Encryption: p + k mod 26 Decryption: c - k mod 26 30
31 Shift Ciphers 5 tuple (P, C, K, E, D) P = C = Z 26 K = Z 26 E: Set of all encryption functions E k (p)= p + k mod 26 D: Set of all decryption functions D k (c)= c - k mod 26 31
32 Affine Ciphers 5 tuple (P, C, K, E, D) P = C = Z 26 K = Z * 26 x Z 26 E: Set of all encryption functions E a,k (p)= ap + k mod 26 D: Set of all decryption functions D a,k (c)= a -1 (c - k) mod 26 gcd(a, 26) = 1 32
33 How to Break Cryptosystems Cryptanalysis 33
34 Monoalphabet Ciphers Vulnerable to: Frequency analysis Alternative: transposition ciphers 34
35 Symmetric Ciphers shared key cryptosystems State of the art: AES implemented in secure file transfer protocols (HTTPS, SFTP) 35
NP-Completeness. A language B is NP-complete iff B NP. This property means B is NP hard
NP-Completeness A language B is NP-complete iff B NP A NP A P B This property means B is NP hard 1 3SAT is NP-complete 2 Result Idea: B is known to be NP complete Use it to prove NP-Completeness of C IF
More informationClassical Cryptography
Classical Cryptography CSG 252 Fall 2006 Riccardo Pucella Goals of Cryptography Alice wants to send message X to Bob Oscar is on the wire, listening to communications Alice and Bob share a key K Alice
More informationMONOALPHABETIC CIPHERS AND THEIR MATHEMATICS. CIS 400/628 Spring 2005 Introduction to Cryptography
MONOALPHABETIC CIPHERS AND THEIR MATHEMATICS CIS 400/628 Spring 2005 Introduction to Cryptography This is based on Chapter 1 of Lewand and Chapter 1 of Garrett. MONOALPHABETIC SUBSTITUTION CIPHERS These
More informationCS154, Lecture 15: Cook-Levin Theorem SAT, 3SAT
CS154, Lecture 15: Cook-Levin Theorem SAT, 3SAT Definition: A language B is NP-complete if: 1. B NP 2. Every A in NP is poly-time reducible to B That is, A P B When this is true, we say B is NP-hard On
More informationTIME COMPLEXITY AND POLYNOMIAL TIME; NON DETERMINISTIC TURING MACHINES AND NP. THURSDAY Mar 20
TIME COMPLEXITY AND POLYNOMIAL TIME; NON DETERMINISTIC TURING MACHINES AND NP THURSDAY Mar 20 COMPLEXITY THEORY Studies what can and can t be computed under limited resources such as time, space, etc Today:
More informationChapter 7: Time Complexity
Chapter 7: Time Complexity 1 Time complexity Let M be a deterministic Turing machine that halts on all inputs. The running time or time complexity of M is the function f: N N, where f(n) is the maximum
More informationLecture 19: Finish NP-Completeness, conp and Friends
6.045 Lecture 19: Finish NP-Completeness, conp and Friends 1 Polynomial Time Reducibility f : Σ* Σ* is a polynomial time computable function if there is a poly-time Turing machine M that on every input
More informationFinal Exam Math 105: Topics in Mathematics Cryptology, the Science of Secret Writing Rhodes College Tuesday, 30 April :30 11:00 a.m.
Final Exam Math 10: Topics in Mathematics Cryptology, the Science of Secret Writing Rhodes College Tuesday, 0 April 2002 :0 11:00 a.m. Instructions: Please be as neat as possible (use a pencil), and show
More informationLecture 17: Cook-Levin Theorem, NP-Complete Problems
6.045 Lecture 17: Cook-Levin Theorem, NP-Complete Problems 1 Is SAT solvable in O(n) time on a multitape TM? Logic circuits of 6n gates for SAT? If yes, then not only is P=NP, but there would be a dream
More informationCS311 Computational Structures. NP-completeness. Lecture 18. Andrew P. Black Andrew Tolmach. Thursday, 2 December 2010
CS311 Computational Structures NP-completeness Lecture 18 Andrew P. Black Andrew Tolmach 1 Some complexity classes P = Decidable in polynomial time on deterministic TM ( tractable ) NP = Decidable in polynomial
More informationCS154, Lecture 13: P vs NP
CS154, Lecture 13: P vs NP The EXTENDED Church-Turing Thesis Everyone s Intuitive Notion of Efficient Algorithms Polynomial-Time Turing Machines More generally: TM can simulate every reasonable model of
More informationTheory of Computation Time Complexity
Theory of Computation Time Complexity Bow-Yaw Wang Academia Sinica Spring 2012 Bow-Yaw Wang (Academia Sinica) Time Complexity Spring 2012 1 / 59 Time for Deciding a Language Let us consider A = {0 n 1
More informationTime to learn about NP-completeness!
Time to learn about NP-completeness! Harvey Mudd College March 19, 2007 Languages A language is a set of strings Examples The language of strings of all a s with odd length The language of strings with
More informationLecture 12: Block ciphers
Lecture 12: Block ciphers Thomas Johansson T. Johansson (Lund University) 1 / 19 Block ciphers A block cipher encrypts a block of plaintext bits x to a block of ciphertext bits y. The transformation is
More informationCPE 776:DATA SECURITY & CRYPTOGRAPHY. Some Number Theory and Classical Crypto Systems
CPE 776:DATA SECURITY & CRYPTOGRAPHY Some Number Theory and Classical Crypto Systems Dr. Lo ai Tawalbeh Computer Engineering Department Jordan University of Science and Technology Jordan Some Number Theory
More informationThe Class NP. NP is the problems that can be solved in polynomial time by a nondeterministic machine.
The Class NP NP is the problems that can be solved in polynomial time by a nondeterministic machine. NP The time taken by nondeterministic TM is the length of the longest branch. The collection of all
More informationComputability Theory
CS:4330 Theory of Computation Spring 2018 Computability Theory P versus NP and NP-Completeness Haniel Barbosa Readings for this lecture Chapter 7 of [Sipser 1996], 3rd edition. Section 7.4. The P versus
More informationClassical Cryptography
Outline [1] Introduction: Some Simple Cryptosystems The Shift Cipher The Substitution Cipher The Affine Cipher The Vigenère Cipher The Hill Cipher The Permutation Cipher [2] Cryptanalysis
More information22c:135 Theory of Computation. Analyzing an Algorithm. Simplifying Conventions. Example computation. How much time does M1 take to decide A?
Example computation Consider the decidable language A = {0 n 1 n n 0} and the following TM M1 deciding A: M1 = "On input string w: 1. Scan across the tape and reject if a 0 appears after a 1 2. Repeat
More informationUniversity of Regina Department of Mathematics & Statistics Final Examination (April 21, 2009)
Make sure that this examination has 10 numbered pages University of Regina Department of Mathematics & Statistics Final Examination 200910 (April 21, 2009) Mathematics 124 The Art and Science of Secret
More informationInnovation and Cryptoventures. Cryptology. Campbell R. Harvey. Duke University, NBER and Investment Strategy Advisor, Man Group, plc.
Innovation and Cryptoventures Cryptology Campbell R. Harvey Duke University, NBER and Investment Strategy Advisor, Man Group, plc January 20, 2017 Overview Cryptology Cryptography Cryptanalysis Symmetric
More informationCS154, Lecture 17: conp, Oracles again, Space Complexity
CS154, Lecture 17: conp, Oracles again, Space Complexity Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode: Guess string
More informationCS154, Lecture 13: P vs NP
CS154, Lecture 13: P vs NP The EXTENDED Church-Turing Thesis Everyone s Intuitive Notion of Efficient Algorithms Polynomial-Time Turing Machines More generally: TM can simulate every reasonable model of
More informationCryptography. P. Danziger. Transmit...Bob...
10.4 Cryptography P. Danziger 1 Cipher Schemes A cryptographic scheme is an example of a code. The special requirement is that the encoded message be difficult to retrieve without some special piece of
More informationCSCI3381-Cryptography
CSCI3381-Cryptography Lecture 2: Classical Cryptosystems September 3, 2014 This describes some cryptographic systems in use before the advent of computers. All of these methods are quite insecure, from
More information1 Non-deterministic Turing Machine
1 Non-deterministic Turing Machine A nondeterministic Turing machine is a generalization of the standard TM for which every configuration may yield none, or one or more than one next configurations. In
More informationPublic Key Cryptography
Public Key Cryptography Spotlight on Science J. Robert Buchanan Department of Mathematics 2011 What is Cryptography? cryptography: study of methods for sending messages in a form that only be understood
More informationIntroduction to Cryptology. Lecture 2
Introduction to Cryptology Lecture 2 Announcements 2 nd vs. 1 st edition of textbook HW1 due Tuesday 2/9 Readings/quizzes (on Canvas) due Friday 2/12 Agenda Last time Historical ciphers and their cryptanalysis
More informationThe Cook-Levin Theorem
An Exposition Sandip Sinha Anamay Chaturvedi Indian Institute of Science, Bangalore 14th November 14 Introduction Deciding a Language Let L {0, 1} be a language, and let M be a Turing machine. We say M
More informationIntro to Theory of Computation
Intro to Theory of Computation LECTURE 25 Last time Class NP Today Polynomial-time reductions Adam Smith; Sofya Raskhodnikova 4/18/2016 L25.1 The classes P and NP P is the class of languages decidable
More informationan efficient procedure for the decision problem. We illustrate this phenomenon for the Satisfiability problem.
1 More on NP In this set of lecture notes, we examine the class NP in more detail. We give a characterization of NP which justifies the guess and verify paradigm, and study the complexity of solving search
More informationShift Cipher. For 0 i 25, the ith plaintext character is. E.g. k = 3
Shift Cipher For 0 i 25, the ith plaintext character is shifted by some value 0 k 25 (mod 26). E.g. k = 3 a b c d e f g h i j k l m n o p q r s t u v w x y z D E F G H I J K L M N O P Q R S T U V W X Y
More informationData and information security: 2. Classical cryptography
ICS 423: s Data and information security: 2. Classical cryptography UHM ICS 423 Fall 2014 Outline ICS 423: s s and crypto systems ciphers ciphers Breaking ciphers What did we learn? Outline ICS 423: s
More informationDefinition: conp = { L L NP } What does a conp computation look like?
Space Complexity 28 Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode: Guess string y of x k length and the machine accepts
More informationIntroduction to Cryptography CS 355 Lecture 3
Introduction to Cryptography CS 355 Lecture 3 Elementary Number Theory (1) CS 355 Fall 2005/Lecture 3 1 Review of Last Lecture Ciphertext-only attack: Known-plaintext attack: Chosen-plaintext: Chosen-ciphertext:
More informationCandidates must show on each answer book the type of calculator used. Only calculators permitted under UEA Regulations may be used.
UNIVERSITY OF EAST ANGLIA School of Mathematics May/June UG Examination 2010 2011 CRYPTOGRAPHY Time allowed: 2 hours Attempt THREE questions. Candidates must show on each answer book the type of calculator
More informationPublic-Key Cryptosystems CHAPTER 4
Public-Key Cryptosystems CHAPTER 4 Introduction How to distribute the cryptographic keys? Naïve Solution Naïve Solution Give every user P i a separate random key K ij to communicate with every P j. Disadvantage:
More informationTime Complexity. CS60001: Foundations of Computing Science
Time Complexity CS60001: Foundations of Computing Science Professor, Dept. of Computer Sc. & Engg., Measuring Complexity Definition Let M be a deterministic Turing machine that halts on all inputs. The
More informationApplied Computer Science II Chapter 7: Time Complexity. Prof. Dr. Luc De Raedt. Institut für Informatik Albert-Ludwigs Universität Freiburg Germany
Applied Computer Science II Chapter 7: Time Complexity Prof. Dr. Luc De Raedt Institut für Informati Albert-Ludwigs Universität Freiburg Germany Overview Measuring complexity The class P The class NP NP-completeness
More informationconp, Oracles, Space Complexity
conp, Oracles, Space Complexity 1 What s next? A few possibilities CS161 Design and Analysis of Algorithms CS254 Complexity Theory (next year) CS354 Topics in Circuit Complexity For your favorite course
More informationChapter 2 : Time complexity
Dr. Abhijit Das, Chapter 2 : Time complexity In this chapter we study some basic results on the time complexities of computational problems. concentrate our attention mostly on polynomial time complexities,
More informationLecture 16: Time Complexity and P vs NP
6.045 Lecture 16: Time Complexity and P vs NP 1 Time-Bounded Complexity Classes Definition: TIME(t(n)) = { L there is a Turing machine M with time complexity O(t(n)) so that L = L(M) } = { L L is a language
More informationSimple Codes MTH 440
Simple Codes MTH 440 Not all codes are for the purpose of secrecy Morse Code ASCII Zip codes Area codes Library book codes Credit Cards ASCII Code Steganography: Hidden in plain sight (example from http://www.bbc.co.uk/news/10
More informationCISC 4090 Theory of Computation
CISC 4090 Theory of Computation Complexity Professor Daniel Leeds dleeds@fordham.edu JMH 332 Computability Are we guaranteed to get an answer? Complexity How long do we have to wait for an answer? (Ch7)
More information6.045: Automata, Computability, and Complexity (GITCS) Class 15 Nancy Lynch
6.045: Automata, Computability, and Complexity (GITCS) Class 15 Nancy Lynch Today: More Complexity Theory Polynomial-time reducibility, NP-completeness, and the Satisfiability (SAT) problem Topics: Introduction
More information15.1 Proof of the Cook-Levin Theorem: SAT is NP-complete
CS125 Lecture 15 Fall 2016 15.1 Proof of the Cook-Levin Theorem: SAT is NP-complete Already know SAT NP, so only need to show SAT is NP-hard. Let L be any language in NP. Let M be a NTM that decides L
More informationAn Introduction to Cryptography
An Introduction to Cryptography Spotlight on Science J. Robert Buchanan Department of Mathematics Spring 2008 What is Cryptography? cryptography: study of methods for sending messages in a form that only
More informationCODING AND CRYPTOLOGY III CRYPTOLOGY EXERCISES. The questions with a * are extension questions, and will not be included in the assignment.
CODING AND CRYPTOLOGY III CRYPTOLOGY EXERCISES A selection of the following questions will be chosen by the lecturer to form the Cryptology Assignment. The Cryptology Assignment is due by 5pm Sunday 1
More informationFORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY. FLAC (15-453) Spring l. Blum TIME COMPLEXITY AND POLYNOMIAL TIME;
15-453 TIME COMPLEXITY AND POLYNOMIAL TIME; FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY NON DETERMINISTIC TURING MACHINES AND NP THURSDAY Mar 20 COMPLEXITY THEORY Studies what can and can t be computed
More informationMATH3302 Cryptography Problem Set 2
MATH3302 Cryptography Problem Set 2 These questions are based on the material in Section 4: Shannon s Theory, Section 5: Modern Cryptography, Section 6: The Data Encryption Standard, Section 7: International
More informationWritten examination. Tuesday, August 18, 2015, 08:30 a.m.
Advanced Methods of Cryptography Univ.-Prof. Dr. rer. nat. Rudolf Mathar 1 2 3 4 19 20 11 20 70 Written examination Tuesday, August 18, 2015, 08:30 a.m. Name: Matr.-No.: Field of study: Please pay attention
More informationCS5371 Theory of Computation. Lecture 19: Complexity IV (More on NP, NP-Complete)
CS5371 Theory of Computation Lecture 19: Complexity IV (More on NP, NP-Complete) Objectives More discussion on the class NP Cook-Levin Theorem The Class NP revisited Recall that NP is the class of language
More informationComplexity (Pre Lecture)
Complexity (Pre Lecture) Dr. Neil T. Dantam CSCI-561, Colorado School of Mines Fall 2018 Dantam (Mines CSCI-561) Complexity (Pre Lecture) Fall 2018 1 / 70 Why? What can we always compute efficiently? What
More informationCryptography CS 555. Topic 2: Evolution of Classical Cryptography CS555. Topic 2 1
Cryptography CS 555 Topic 2: Evolution of Classical Cryptography Topic 2 1 Lecture Outline Basics of probability Vigenere cipher. Attacks on Vigenere: Kasisky Test and Index of Coincidence Cipher machines:
More informationTHE UNIVERSITY OF CALGARY FACULTY OF SCIENCE DEPARTMENT OF COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS & STATISTICS MIDTERM EXAMINATION 1 FALL 2018
THE UNIVERSITY OF CALGARY FACULTY OF SCIENCE DEPARTMENT OF COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS & STATISTICS MIDTERM EXAMINATION 1 FALL 2018 CPSC 418/MATH 318 L01 October 17, 2018 Time: 50 minutes
More informationBBM402-Lecture 11: The Class NP
BBM402-Lecture 11: The Class NP Lecturer: Lale Özkahya Resources for the presentation: http://ocw.mit.edu/courses/electrical-engineering-andcomputer-science/6-045j-automata-computability-andcomplexity-spring-2011/syllabus/
More informationTheory of Computation. Ch.8 Space Complexity. wherein all branches of its computation halt on all
Definition 8.1 Let M be a deterministic Turing machine, DTM, that halts on all inputs. The space complexity of M is the function f : N N, where f(n) is the maximum number of tape cells that M scans on
More informationLecture 8 - Cryptography and Information Theory
Lecture 8 - Cryptography and Information Theory Jan Bouda FI MU April 22, 2010 Jan Bouda (FI MU) Lecture 8 - Cryptography and Information Theory April 22, 2010 1 / 25 Part I Cryptosystem Jan Bouda (FI
More informationDivision Property: a New Attack Against Block Ciphers
Division Property: a New Attack Against Block Ciphers Christina Boura (joint on-going work with Anne Canteaut) Séminaire du groupe Algèbre et Géometrie, LMV November 24, 2015 1 / 50 Symmetric-key encryption
More informationLecture 20: conp and Friends, Oracles in Complexity Theory
6.045 Lecture 20: conp and Friends, Oracles in Complexity Theory 1 Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode:
More informationNotes. Number Theory: Applications. Notes. Number Theory: Applications. Notes. Hash Functions I
Number Theory: Applications Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry Fall 2007 Computer Science & Engineering 235 Introduction to Discrete Mathematics Sections 3.4 3.7 of Rosen cse235@cse.unl.edu
More informationReview. CS311H: Discrete Mathematics. Number Theory. Computing GCDs. Insight Behind Euclid s Algorithm. Using this Theorem. Euclidian Algorithm
Review CS311H: Discrete Mathematics Number Theory Instructor: Işıl Dillig What does it mean for two ints a, b to be congruent mod m? What is the Division theorem? If a b and a c, does it mean b c? What
More informationCS 320, Fall Dr. Geri Georg, Instructor 320 NP 1
NP CS 320, Fall 2017 Dr. Geri Georg, Instructor georg@colostate.edu 320 NP 1 NP Complete A class of problems where: No polynomial time algorithm has been discovered No proof that one doesn t exist 320
More information10 Modular Arithmetic and Cryptography
10 Modular Arithmetic and Cryptography 10.1 Encryption and Decryption Encryption is used to send messages secretly. The sender has a message or plaintext. Encryption by the sender takes the plaintext and
More informationCS 3719 (Theory of Computation and Algorithms) Lectures 23-32
CS 3719 (Theory of Computation and Algorithms) Lectures 23-32 Antonina Kolokolova March 2011 1 Scaling down to complexity In real life, we are interested whether a problem can be solved efficiently; just
More informationLecture 9 Julie Staub Avi Dalal Abheek Anand Gelareh Taban. 1 Introduction. 2 Background. CMSC 858K Advanced Topics in Cryptography February 24, 2004
CMSC 858K Advanced Topics in Cryptography February 24, 2004 Lecturer: Jonathan Katz Lecture 9 Scribe(s): Julie Staub Avi Dalal Abheek Anand Gelareh Taban 1 Introduction In previous lectures, we constructed
More informationCryptography. Lecture 2: Perfect Secrecy and its Limitations. Gil Segev
Cryptography Lecture 2: Perfect Secrecy and its Limitations Gil Segev Last Week Symmetric-key encryption (KeyGen, Enc, Dec) Historical ciphers that are completely broken The basic principles of modern
More informationDefinition: For a positive integer n, if 0<a<n and gcd(a,n)=1, a is relatively prime to n. Ahmet Burak Can Hacettepe University
Number Theory, Public Key Cryptography, RSA Ahmet Burak Can Hacettepe University abc@hacettepe.edu.tr The Euler Phi Function For a positive integer n, if 0
More informationNumber Theory: Applications. Number Theory Applications. Hash Functions II. Hash Functions III. Pseudorandom Numbers
Number Theory: Applications Number Theory Applications Computer Science & Engineering 235: Discrete Mathematics Christopher M. Bourke cbourke@cse.unl.edu Results from Number Theory have many applications
More informationNumber Theory and Algebra: A Brief Introduction
Number Theory and Algebra: A Brief Introduction Indian Statistical Institute Kolkata May 15, 2017 Elementary Number Theory: Modular Arithmetic Definition Let n be a positive integer and a and b two integers.
More informationCHAPTER 12 CRYPTOGRAPHY OF A GRAY LEVEL IMAGE USING A MODIFIED HILL CIPHER
177 CHAPTER 12 CRYPTOGRAPHY OF A GRAY LEVEL IMAGE USING A MODIFIED HILL CIPHER 178 12.1 Introduction The study of cryptography of gray level images [110, 112, 118] by using block ciphers has gained considerable
More informationCPSC 467b: Cryptography and Computer Security
CPSC 467b: Cryptography and Computer Security Michael J. Fischer Lecture 3 January 22, 2013 CPSC 467b, Lecture 3 1/35 Perfect secrecy Caesar cipher Loss of perfection Classical ciphers One-time pad Affine
More informationCryptography. pieces from work by Gordon Royle
Cryptography pieces from work by Gordon Royle The set-up Cryptography is the mathematics of devising secure communication systems, whereas cryptanalysis is the mathematics of breaking such systems. We
More information6.5.3 An NP-complete domino game
26 Chapter 6. Complexity Theory 3SAT NP. We know from Theorem 6.5.7 that this is true. A P 3SAT, for every language A NP. Hence, we have to show this for languages A such as kcolor, HC, SOS, NPrim, KS,
More informationLemma 1.2. (1) If p is prime, then ϕ(p) = p 1. (2) If p q are two primes, then ϕ(pq) = (p 1)(q 1).
1 Background 1.1 The group of units MAT 3343, APPLIED ALGEBRA, FALL 2003 Handout 3: The RSA Cryptosystem Peter Selinger Let (R, +, ) be a ring. Then R forms an abelian group under addition. R does not
More informationSol: First, calculate the number of integers which are relative prime with = (1 1 7 ) (1 1 3 ) = = 2268
ò{çd@àt ø 2005.0.3. Suppose the plaintext alphabets include a z, A Z, 0 9, and the space character, therefore, we work on 63 instead of 26 for an affine cipher. How many keys are possible? What if we add
More informationSolution to Midterm Examination
YALE UNIVERSITY DEPARTMENT OF COMPUTER SCIENCE CPSC 467a: Cryptography and Computer Security Handout #13 Xueyuan Su November 4, 2008 Instructions: Solution to Midterm Examination This is a closed book
More informationCSE 135: Introduction to Theory of Computation NP-completeness
CSE 135: Introduction to Theory of Computation NP-completeness Sungjin Im University of California, Merced 04-15-2014 Significance of the question if P? NP Perhaps you have heard of (some of) the following
More informationFORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY
15-453 FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY THURSDAY APRIL 3 REVIEW for Midterm TUESDAY April 8 Definition: A Turing Machine is a 7-tuple T = (Q, Σ, Γ, δ, q, q accept, q reject ), where: Q is a
More informationA Large Block Cipher using an Iterative Method and the Modular Arithmetic Inverse of a key Matrix
A Large Block Cipher using an Iterative Method and the Modular Arithmetic Inverse of a key Matrix S. Udaya Kumar V. U. K. Sastry A. Vinaya babu Abstract In this paper, we have developed a block cipher
More informationCryptography and Network Security Prof. D. Mukhopadhyay Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur
Cryptography and Network Security Prof. D. Mukhopadhyay Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur Module No. # 01 Lecture No. # 08 Shannon s Theory (Contd.)
More informationCS 6505, Complexity and Algorithms Week 7: NP Completeness
CS 6505, Complexity and Algorithms Week 7: NP Completeness Reductions We have seen some problems in P and NP, and we ve talked about space complexity. The Space Hierarchy Theorem showed us that there are
More informationTutorial on Quantum Computing. Vwani P. Roychowdhury. Lecture 1: Introduction
Tutorial on Quantum Computing Vwani P. Roychowdhury Lecture 1: Introduction 1 & ) &! # Fundamentals Qubits A single qubit is a two state system, such as a two level atom we denote two orthogonal states
More informationThe Dead Cryptographers Society Problem
The Dead Cryptographers Society Problem André Luiz Barbosa http://www.andrebarbosa.eti.br Non-commercial projects: SimuPLC PLC Simulator & LCE Electric Commands Language Abstract. This paper defines The
More information2.1 Plaintext, encryption algorithm, secret key, ciphertext, decryption algorithm.
CHAPTER 2 CLASSICAL ENCRYPTION TECHNIQUES ANSWERS TO QUESTIONS 2.1 Plaintext, encryption algorithm, secret key, ciphertext, decryption algorithm. 2.2 Permutation and substitution. 2.3 One key for symmetric
More informationCHALMERS GÖTEBORGS UNIVERSITET. TDA352 (Chalmers) - DIT250 (GU) 11 April 2017, 8:30-12:30
CHALMERS GÖTEBORGS UNIVERSITET CRYPTOGRAPHY TDA35 (Chalmers) - DIT50 (GU) 11 April 017, 8:30-1:30 No extra material is allowed during the exam except for pens and a simple calculator (not smartphones).
More informationFinish K-Complexity, Start Time Complexity
6.045 Finish K-Complexity, Start Time Complexity 1 Kolmogorov Complexity Definition: The shortest description of x, denoted as d(x), is the lexicographically shortest string such that M(w) halts
More informationPublic-key Cryptography and elliptic curves
Public-key Cryptography and elliptic curves Dan Nichols University of Massachusetts Amherst nichols@math.umass.edu WINRS Research Symposium Brown University March 4, 2017 Cryptography basics Cryptography
More informationMath 412: Number Theory Lecture 13 Applications of
Math 412: Number Theory Lecture 13 Applications of Gexin Yu gyu@wm.edu College of William and Mary Partition of integers A partition λ of the positive integer n is a non increasing sequence of positive
More informationComplexity Theory VU , SS The Polynomial Hierarchy. Reinhard Pichler
Complexity Theory Complexity Theory VU 181.142, SS 2018 6. The Polynomial Hierarchy Reinhard Pichler Institut für Informationssysteme Arbeitsbereich DBAI Technische Universität Wien 15 May, 2018 Reinhard
More informationOutline. Complexity Theory EXACT TSP. The Class DP. Definition. Problem EXACT TSP. Complexity of EXACT TSP. Proposition VU 181.
Complexity Theory Complexity Theory Outline Complexity Theory VU 181.142, SS 2018 6. The Polynomial Hierarchy Reinhard Pichler Institut für Informationssysteme Arbeitsbereich DBAI Technische Universität
More informationIntroduction to Modern Cryptography. Benny Chor
Introduction to Modern Cryptography Benny Chor RSA Public Key Encryption Factoring Algorithms Lecture 7 Tel-Aviv University Revised March 1st, 2008 Reminder: The Prime Number Theorem Let π(x) denote the
More informationChapter 2 Classical Cryptosystems
Chapter 2 Classical Cryptosystems Note We will use the convention that plaintext will be lowercase and ciphertext will be in all capitals. 2.1 Shift Ciphers The idea of the Caesar cipher: To encrypt, shift
More informationCryptography and Security Midterm Exam
Cryptography and Security Midterm Exam Serge Vaudenay 23.11.2017 duration: 1h45 no documents allowed, except one 2-sided sheet of handwritten notes a pocket calculator is allowed communication devices
More informationWinter 2008 Introduction to Modern Cryptography Benny Chor and Rani Hod. Assignment #2
0368.3049.01 Winter 2008 Introduction to Modern Cryptography Benny Chor and Rani Hod Assignment #2 Published Sunday, February 17, 2008 and very slightly revised Feb. 18. Due Tues., March 4, in Rani Hod
More informationCSE 105 THEORY OF COMPUTATION
CSE 105 THEORY OF COMPUTATION Spring 2016 http://cseweb.ucsd.edu/classes/sp16/cse105-ab/ Today's learning goals Sipser Ch 7.2, 7.3 Distinguish between polynomial and exponential DTIME Define nondeterministic
More informationCSE 105 Theory of Computation
CSE 105 Theory of Computation http://www.jflap.org/jflaptmp/ Professor Jeanne Ferrante 1 Today s Agenda P and NP (7.2, 7.3) Next class: Review Reminders and announcements: CAPE & TA evals are open: Please
More information17.1 Binary Codes Normal numbers we use are in base 10, which are called decimal numbers. Each digit can be 10 possible numbers: 0, 1, 2, 9.
( c ) E p s t e i n, C a r t e r, B o l l i n g e r, A u r i s p a C h a p t e r 17: I n f o r m a t i o n S c i e n c e P a g e 1 CHAPTER 17: Information Science 17.1 Binary Codes Normal numbers we use
More informationCHAPTER 5 A BLOCK CIPHER INVOLVING A KEY APPLIED ON BOTH THE SIDES OF THE PLAINTEXT
82 CHAPTER 5 A BLOCK CIPHER INVOLVING A KEY APPLIED ON BOTH THE SIDES OF THE PLAINTEXT 83 5.1 Introduction In a pioneering paper, Hill [5] developed a block cipher by using the modular arithmetic inverse
More informationSpace Complexity. The space complexity of a program is how much memory it uses.
Space Complexity The space complexity of a program is how much memory it uses. Measuring Space When we compute the space used by a TM, we do not count the input (think of input as readonly). We say that
More information