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Introduction to Modern Cryptography

Introduction to Modern Cryptography. Instructor: Amos Fiat Strongly based on presentation and class by Benny Chor School of Computer Science Tel- Aviv Univ. Administrative Details. Grade –exam ( 75% ), homework ( 25% ) . Exam on last class. In class exam. No 2 nd chance.

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Introduction to Modern Cryptography

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  1. Introduction to Modern Cryptography Instructor: Amos Fiat Strongly based on presentation and class by Benny Chor School of Computer Science Tel- Aviv Univ.

  2. Administrative Details • Grade –exam (75% ), homework (25% ). • Exam on last class. In class exam. No 2nd chance. • Homework submission in pairs. • 2-3 “dry’’ assignments. • 1-2 “wet” assignments (in MAPLE). • Office hours: By e-appointment. • E-mail: fiat@cs.tau.ac.il

  3. Course Outline • Encryption • Data integrity • Authentication and identification • Digital signatures • Number theory • Randomness and pseudo-randomness • Cryptographic protocols • Real world security systems • Watermarking, digital rights management, etc.

  4. Prerequisites: Linear Algebra Probability Computational Models “Mathematical Maturity”

  5. Bibliography • Text Book: Cryptography Theory and Practice, D. Stinson, CRC Press, 1996. (should be available at the library) • Recommended: - Handbook of Applied Cryptography Menezes, Van Oorschot, Vanstone (free download at http://www.cacr.math.uwaterloo.ca/hac ) - Applied Cryptography, B. Schneier

  6. Good Crypto Courses on the Web • Hugo Krawczyk course at the Technion. • Ron Rivest course at MIT. • Dan Boneh course at Stanford. • Phil Rogaway Course at UC Davis. • Eli Biham course at the Technion. • Doug Stinson course at Waterloo.

  7. Encryption • Much of Security has little to do with Encryption • Encryption deals with secrecy • Most real security deals with problems of fraud: • Message modifications • Almost invariably, Encryption does not live alone without some form of authentication

  8. Definitions • Encryption function (& algorithm): E • Decryption function (& algorithm): D • Encryption key k1 • Decryption key k2 • Message space (usually binary strings) • For every message m: D k2(Ek1(m)) = m

  9. Communication Model Alice Bob • Two parties – Alice and Bob • Reliable communication line • Shared encryption scheme: E, D, k1, k2 • Goal: send a message m confidentially

  10. Threat Model Alice Bob Eve • 4. Goal: send a message m confidentially

  11. Security Goals Possibilities: • No adversary can determine m • No adversary can determine any information about m • No adversary can determine any meaningful information about m.

  12. Adversarial model • Eve attempts to discover information about m • Eve knows the algorithms E,D • Eve knows the message space • Eve has at least partial information about Ek1(m) • Eve does not know k1, k2

  13. Examples – bad ciphers • Shift cipher • Conclusion – large key space required • Substitution cipher • Large key space, still “easy” to break

  14. Substitution cipher • Example: • plaintext: attack at dawn • ciphertext: waaoq wa vwmk Size of key space: 26!=403291461126605635584000000 ~ 4 x 1028 large enough

  15. Additional definitions • Plaintext – the message prior to encryption (“attack at dawn”, “sell MSFT at 57.5”) • Ciphertext – the message after encryption (“יחלעכ חעכןטאככעכ”,“jhhfoghjklvhgbljhg” ) • Symmetric key – encryption scheme where k1=k2 (classical cryptography)

  16. Perfect Cipher • Plaintext space – {0,1}n • Given a ciphertext C the probability that Dk2(C)=P for any plaintext P is equal to the apriori probability that P is the plaintext. In other words: Pr[plaintext=P|C] = Pr[plaintext=P] • Probabilities are over the key space and the plaintext space.

  17. Example – One Time Pad • Plaintext space - {0,1}n • Key space - {0,1}n • The scheme is symmetric, key k is chosen at random • Ek(P) = C = P  K • Dk(C) = C  K = P

  18. Pros and Cons • Claim: the one time pad is a perfect cipher. • Problem: size of key space. • Theorem (Shannon): A cipher cannot be perfect if its key space is less than the size of its message space. • Why??? Argue in class.

  19. Computational Power • Time • Hardware • Storage • Theoretical – polynomial time • Practical – 264 is feasible, 280 is infeasible

  20. Attack Models • Eavesdropping • Known plaintext • Chosen plaintext • Chosen ciphertext • Adaptive chosen text attacks • Physical access • “Physical” modification of messages

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