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CMSC 414 Computer and Network Security Lecture 3

CMSC 414 Computer and Network Security Lecture 3. Jonathan Katz. Attacking the Vigenere cipher. Let p i (for i=0, …, 25) denote the frequency of letter i in English-language text Known that Σ p i 2 ≈ 0.065

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CMSC 414 Computer and Network Security Lecture 3

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  1. CMSC 414Computer and Network SecurityLecture 3 Jonathan Katz

  2. Attacking the Vigenere cipher • Let pi (for i=0, …, 25) denote the frequency of letter i in English-language text • Known that Σ pi2 ≈ 0.065 • For each candidate period t, compute frequencies {qi} of letters in the sequence c0, ct, c2t, … • For the correct value of t, we expect Σ qi2 ≈ 0.065 • For incorrect values of t, we expect Σ qi2 ≈ 1/26 • Once we have the period, can use frequency analysis as in the case of the shift cipher

  3. Moral of the story? • Don’t use “simple” schemes • Don’t use schemes that you design yourself • Use schemes that other people have already designed and analyzed…

  4. A fundamental problem • Wouldn’t it be nice if we could somehow prove that an encryption scheme is secure? • But before that…we haven’t even defined what “secure” means!

  5. Modern cryptography • Proofs • We won’t do proofs in this course, but we will state known results • Definitions • Assumptions

  6. Defining security • Why is a good definition important? • If you don’t know what you want, how can you possibly know whether you’ve achieved it? • Forces you to think about what you really want • What is essential and what is extraneous • Allows comparison of schemes • May be multiple valid ways to define security • Allows others to use schemes; allows analysis of larger systems built using components • Allows for (the possibility of) proofs…

  7. Security definitions • Two components • The threat model • The “security guarantees” or, looking at it from the other side, what counts as a successful attack • Crucial to understand these issues before crypto can be successfully deployed! • Make sure the stated threat model matches your application environment • Make sure the security guarantees are what you need

  8. Security guarantee for encryption? • So how would you define encryption? • Adversary unable to recover the key • Necessary, but meaningless on its own… • Adversary unable to recover entire plaintext • Good, but not enough • Adversary unable to determine any information at all about the plaintext • How to formalize? • Can we achieve it?

  9. Defining secrecy (take 1) • Even an adversary running for an unbounded amount of time learns nothing about the message from the ciphertext • (Except the length) • Perfect secrecy (Shannon) • Formally, for all distributions over the message space, all m, and all c: Pr[M=m | C=c] = Pr[M=m]

  10. Leaking the message length • In general, encryption leaks the length of the message • Possible to (partly) address this using padding • Inefficient • Generally not done • Does not mean that length is unimportant! • In some cases, leaking length can ruin security

  11. The one-time pad • Scheme • Proof of security

  12. Properties of the one-time pad? • Achieves perfect secrecy • No eavesdropper (no matter how powerful) can determine any information whatsoever about the plaintext • Limited use in practice… • Long key length • Can only be used once (hence the name!) • Insecure against known-plaintext attacks • These are inherent limitations of perfect secrecy

  13. Computational secrecy • We can overcome the limitations of perfect secrecy by (slightly) relaxing the definition • Instead of requiring total secrecy against unbounded adversaries, require secrecy against bounded adversaries except with some small probability • E.g., secrecy for 100 years, except with probability 2-80 • How to define formally?

  14. A simpler characterization • Perfect secrecy is equivalent to the following, simpler definition: • Given a ciphertext C which is known to be an encryption of either m0 or m1, no adversary can guess correctly which message was encrypted with probability better than ½ • Relax this to give computational security! • Is this definition too strong? Why not?

  15. The take-home message • Weakening the definition slightly allows us to construct much more efficient schemes! • However, we will need to make assumptions • Strictly speaking, no longer 100% absolutely guaranteed to be secure • Security of encryption now depends on security of building blocks (which are analyzed extensively, and are believed to be secure) • Given enough time and/or resources, the scheme can be broken

  16. PRNGs • A pseudorandom (number) generator (PRNG) is a deterministic function that takes as input a seed and outputs a string • To be useful, the output must be longer than the seed • If seed chosen at random, output of the PRNG should “look random” (i.e., be pseudorandom) to any efficient distinguishing algorithm • Even when the algorithm knows G! (Kerchoffs’s rule)

  17. PRGs: a picture y{0,1}l chosen uniformly at random y ?? World 0 World 1 (poly-time) x {0,1}n chosen uniformly at random G(x) Far from identical, but Adv can’t tell them apart

  18. Notes • Required notion of pseudorandomness is very strong – must be indistinguishable from random for all efficient algorithms • General-purpose PRNGs (rand( ), java.random) not sufficient for crypto • Pseudorandomness of the PRNG depends on the seed being chosen “at random” • True randomness very difficult to obtain • In practice: randomness from physical processes and/or user behavior

  19. A computationally secure scheme • The pseudo-one-time pad… • Theorem: If G is a pseudorandom generator, then this encryption scheme is secure (in the computational sense defined earlier) • Which drawback(s) of the one-time pad does this address?

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