lecture4

lecture4 - Lecture 4: Hash Functions, Message...

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Lecture 4: Hash Functions, Message Authentication and Key Distribution CS 392/6813: Computer Security Fall 2009 Nitesh Saxena * Adopted from Previous Lectures by Nasir Memon 10/8/2009 Lecture 4: Hash Functions and Key Distribution 2 Course Administration ± HW3 was posted – due next Monday ± HW2 has been graded ± HW2 solution was provided ± Mid-Term on 10/29 ± Closed-books/closed-notes ± In-class ± Would cover lecture material until 10/22
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 3 Outline of Today’s lecture ± Hash Functions ± Properties ± Known Hash Function ± SHA-1 ± Message Authentication using hash fns: HMAC ± “Private Key” Distribution ± “Public Key” Distribution: PKI ± Certification ± Revocation 10/8/2009 Lecture 4: Hash Functions and Key Distribution 4 Cryptographic Hash Functions ± Requirements of cryptographic hash functions: ± Can be applied to data of any length. ± Output is fixed length ± Relatively easy to compute h(x), given x and deterministic ± Infeasible to get x, given h(x). One-wayness property ± Given x, infeasible to find y such that h(x) = h(y). Weak-collision resistance property . ± Infeasible to find any pair x and y such that h(x) = h(y). Strong-collision resistance property .
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 5 Hash Output Length ± How long should be the output (n bits) of a cryptographic hash function? ± To find collision - randomly select messages and check if hash matches any that we know. ± Throwing k balls in N = 2 n bins. How large should k be, before probability of landing two balls in the same becomes greater than ½? ± Birthday paradox - a collision can be found in roughly sqrt(N) = 2 (n/2) trials for an n bit hash ± In a group of 23 )(~ sqrt(365)) people, at least two of them will have the same birthday (with a probability > ½) ± Hence n should be at least 160 10/8/2009 Lecture 4: Hash Functions and Key Distribution 6 Birthday Paradox ± Probability that hash values of k random messages are distinct is (that is, no collisions) is: () 1 1 23 1 / 1 (1 ) / 2 ) / 2 12 1 11 1 1 (as for small , 1 ,as 1 ) 2! 3! = So for at least one collision we have probability of whose va 1 k i k in x x i kk N N ki NN N n xx x ee e e e = −− =   =− =     ≅≅ = + K L lue is above 0.5 when 1.17 kN =
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 7 Generic Hash Function 10/8/2009 Lecture 4: Hash Functions and Key Distribution 8
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 9 10/8/2009 Lecture 4: Hash Functions and Key Distribution 10
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 11 10/8/2009 Lecture 4: Hash Functions and Key Distribution 12
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 13 10/8/2009 Lecture 4: Hash Functions and Key Distribution 14
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 15 10/8/2009 Lecture 4: Hash Functions and Key Distribution 16
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10/8/2009 Lecture 4: Hash Functions and Key Distribution 17 Other Hash Functions ± Many other hash functions ± SHA-2 (SHA-256) ±
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This note was uploaded on 11/18/2009 for the course CS 6813 taught by Professor Saxena during the Fall '09 term at NYU Poly.

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lecture4 - Lecture 4: Hash Functions, Message...

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