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A Course in Cryptography

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A Course in Cryptography a Course in Cryptography rafael pass abhi shelat c 2007 Pass/shelat All rights reserved Printed online 11 11 11 11 11 15 14 13 12 11 10 9 First edition: June 2007 Second edition: September 2008 Contents Contents i List of Algorithms and Protocols v List of Definitions vi Preface vii Notation ix 1 Introduction 1 1.1 Classical Cryptography: Hidden Writing . 1 1.2 Modern Cryptography: Provable Security . 5 1.3 Shannon’s Treatment of Provable Secrecy . 9 1.4 Overview of the Course . 16 2 Computational Hardness 19 2.1 Efficient Computation and Efficient Adversaries . 19 2.2 One-Way Functions . 23 2.3 Multiplication, Primes, and the Factoring Assumption . 25 2.4 Weak One-way Functions . 28 2.5 Hardness Amplification . 30 2.6 Collections of One-Way Functions . 34 2.7 Basic Computational Number Theory . 35 2.8 Factoring-based Collection . 43 2.9 Discrete Logarithm-based Collection . 43 2.10 RSA collection . 45 2.11 One-way Permutations . 46 2.12 Trapdoor Permutations . 47 2.13 A Universal One Way Function . 48 i II CONTENTS 3 Indistinguishability & Pseudo-Randomness 51 3.1 Computational Indistinguihability . 52 3.2 Pseudo-randomness . 57 3.3 Pseudo-random generators . 60 3.4 Hard-Core Bits from Any OWF . 65 3.5 Secure Encryption . 71 3.6 An Encryption Scheme with Short Keys . 72 3.7 Multi-message Secure Encryption . 73 3.8 Pseudorandom Functions . 74 3.9 Construction of Multi-message Secure Encryption . 78 3.10 Public Key Encryption . 80 3.11 El-Gamal Public Key Encryption scheme . 83 3.12 A Note on Complexity Assumptions . 84 4 Knowledge 87 4.1 When Does a Message Convey Knowledge . 87 4.2 A Knowledge-Based Notion of Secure Encryption . 88 4.3 Zero-Knowledge Interactions . 90 4.4 Interactive Protocols . 91 4.5 Interactive Proofs . 93 4.6 Zero-Knowledge Proofs . 97 4.7 Zero-knowledge proofs for NP . 100 4.8 Proof of knowledge . 105 4.9 Applications of Zero-knowledge . 105 5 Authentication 107 5.1 Message Authentication . 107 5.2 Message Authentication Codes . 108 5.3 Digital Signature Schemes . 109 5.4 A One-Time Digital Signature Scheme for 0, 1 n . 110 { } 5.5 Collision-Resistant Hash Functions . 112 5.6 A One-Time Digital Signature Scheme for 0, 1 . 116 { }∗ 5.7 *Signing Many Messages . 118 5.8 Intuition for Constructing Efficient Digital Signature . 120 5.9 Zero-knowledge Authentication . 121 6 Computing on Secret Inputs 123 6.1 Secret Sharing . 123 6.2 Secure Computation . 125 6.3 Yao Circuit Evaluation . 126 III 7 Composability 135 7.1 Composition of Encryption Schemes . 135 7.2 Composition of Zero-knowledge Proofs* . 142 7.3 Composition Beyond Zero-Knowledge Proofs . 144 8 *More on Randomness and Pseudorandomness 145 8.1 A Negative Result for Learning . 145 8.2 Derandomization . 145 8.3 Imperfect Randomness and Extractors . 147 A Basic Probability 151 B Basic Complexity Classes 155 List of Algorithms and Protocols 2.5 A (f, y) where y 0, 1 n ..................... 32 0 ∈ { } 2.13 funiversal(y): A Universal One-way Function . 49 3.4 (y) .................................. 69 B 3.4 (y) for the General case . 70 B 3.6 Encryption Scheme for n-bit message . 72 3.9 Many-message Encryption Scheme . 78 3.10 1-Bit Secure Public Key Encryption . 82 3.11 El-Gamal Secure Public Key Encryption . 84 4.5 Protocol for Graph Non-Isomorphism . 94 4.5 Protocol for Graph Isomorphism . 96 4.6 Simulator for Graph Isomorphism . 99 4.7 Zero-Knowledge for Graph 3-Coloring . 102 4.7 Simulator for Graph 3-Coloring . 103 5.2 MAC Scheme . 108 5.4 One-Time Digital Signature Scheme . 110 5.5 Collision Resistant Hash Function . 115 5.6 One-time Digital Signature for 0, 1 . 117 { }∗ 6.1 Shamir Secret Sharing Protocol . 124 6.3 A Special Encryption Scheme . 128 6.3 Oblivious Transfer Protocol . 132 6.3 Honest-but-Curious Secure Computation . 132 v VI LIST OF DEFINITIONS 7.2 ZK Protocol that is not Concurrently Secure . 143 List of Definitions 1.1 Private-key Encryption . 3 1.3 Shannon secrecy . 10 1.3 Perfect Secrecy . 10 2.1 Efficient Private-key Encryption . 22 2.2 Worst-case One-way Function . 23 2.6 Collection of OWFs . 34 2.11 One-way permutation . 46 2.12 Trapdoor Permutations . 47 3.1 Computational Indistinguishability . 54 3.2 Pseudo-random Ensembles . 57 3.3 Pseudo-random Generator . 60 3.3 Hard-core Predicate . 61 3.5 Secure Encryption . 71 3.7 Multi-message Secure Encryption . 73 3.8 Oracle Indistinguishability . 75 3.8 Pseudo-random Function . 76 3.10 Public Key Encryption Scheme . 80 3.10 Secure Public Key Encryption . 81 4.2 Zero-Knowledge Encryption . 88 4.5 Interactive Proof . 93 4.5 Interactive Proof with Efficient Provers . 96 4.7 Commitment . 101 5.3 Security of Digital Signatures . 110 Preface We would like to thank the students of CS 687 (Stephen Chong, Michael Clarkson, Michael George, Lucja Kot, Vikram Krishnaprasad, Huijia Lin, Jed Liu, Ashwin Machanavajjhala, Tudor Marian, Thanh Nguyen, Ariel Rabkin, Tom Roeder, Wei-lung Tseng, Muthuramakrishnan Venkitasubramaniam and Parvathinathan Venkitasubramaniam) for scribing the original lecture notes which served as a starting point for these notes. In particular, we are very grateful to Muthu for compiling these original sets of notes. RAFAEL PASS Ithaca, NY ABHI SHELAT Charlottesville, VA August 2007 vii Notation Algorithms Let A denote an algorithm. We write A( ) to denote an algorithm with one · input and A( , ) for two inputs. In general, the output of a (randomized) · · algorithm is described by a probability distribution; we let A(x) denotes the probability distribution associated with the output of A on input x. An algo- rithm is said to be deterministic if the probability distribution is concentrated on a single element. Experiments We denote by x S the experiment of sampling an element x from a proba- ← bility distribution S. If F is a finite set, then x F denotes the experiment of ← sampling uniformly from the set F . We use semicolon to describe the ordered sequences of event that make up an experiment, e.g., x S;(y, z) A(x) ← ← Probabilities If p(., .) denotes a predicate, then Pr[x S;(y, z) A(x): p(y, z)] ← ← is the probability that the predicate p(y, z) is true after the ordered sequence of events (x S;(y, z) A(x)). The notation x S;(y, z) A(x): ← ← { ← ← (y, z) denotes the probability distribution over y, z generated by the ex- } { } periment x S;(y, z) A(x). ← ← ix Chapter 1 Introduction The word cryptography stems from the Greek words krypt´os—meaning “hidden”— and gr´afein—meaning “ to write”. Indeed, the classical cryptographic prob- lem, which dates back millenia, considers the task of using “hidden writing” to secure, or conceal communication between two parties. 1.1 Classical Cryptography: Hidden Writing Consider two parties, Alice and Bob. Alice wants to privately send messages (called plaintexts) to Bob over an insecure channel. By an insecure channel, we here refer to an “open” and tappable channel; in particular, Alice and Bob would like their privacy to be maintained even in face of an adversary Eve (for eavesdropper) who listens to all messages sent on the channel. How can this be achieved? A possible solution Before starting their communication, Alice and Bob agree on some “secret code” that they will later use to communicate. A secret code consists of a key, an algorithm, Enc, to encrypt (scramble) plaintext mes- sages into ciphertexts and an algorithm Dec to decrypt (or descramble) cipher- texts into plaintext messages. Both the encryption and decryption algorithms require the key to perform their task. Alice can now use the key to encrypt a message, and the send the cipher- text to Bob. Bob, upon receiving a ciphertext, uses the key to decrypt the ciphertext and retrieve the orignal message. 1 2 INTRODUCTION ? Eve ③ c Alice Bob ② ④ ① c = Enck(m) k k m = Deck(c) Gen Figure 1.1: Illustration of the steps involved in private-key encryption. First, a key k must be generated by the Gen algorithm and privately given to Alice and Bob. In the picture, this is illustrated with a green “land-line.” Later, Al- ice encodes the message m into a ciphertext c and sends it over the insecure channel—in this case, over the airwaves. Bob receives the encoded message and decodes it using the key k to recover the original message m. The eaves- dropper Eve does not learn anything about m except perhaps its length. 1.1.1 Private-Key Encryption To formalize the above task, we must consider an additional algorithm, Gen, called the key-generation algorithm; this algorithm is executed by Alice and Bob to generate the key k which they use to encrypt and decrypt messages. A first question that needs to be addressed is what information needs to be “public”—i.e., known to everyone—and what needs to be “private”—i.e., kept secret. In the classical approach—security by obscurity—all of the above algorithms, Gen, Enc, Dec, and the generated key k were kept private; the idea was of course that the less information we give to the adversary, the harder it is to break the scheme. A design principle formulated by Kerchoff in 1884— known as Kerchoff’s principle—instead stipulates that the only thing that one should assume to be private is the key k; everything else (i.e., Gen, Encand Dec) should be assumed to be public! Why should we do this? Designs of en- cryption algorithms are often eventually leaked, and when this happens the effects to privacy could be disastrous.
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