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Going Down HILL: More Efficient Pseudorandom Generators from Any One-way Function

Going Down HILL: More Efficient Pseudorandom Generators from Any One-way Function. Omer Reingold. &. Joint with Iftach Haitner and Salil Vadhan. One Way Functions. One Way Functions (OWF): f:{0,1} n  {0,1} n Easy to compute hard to invert (even on average).

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Going Down HILL: More Efficient Pseudorandom Generators from Any One-way Function

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  1. Going Down HILL: More Efficient Pseudorandom Generators from Any One-way Function Omer Reingold & Joint with Iftach Haitner and Salil Vadhan

  2. One Way Functions One Way Functions (OWF): f:{0,1}n {0,1}n • Easy to compute hard to invert (even on average). • The most basic, unstructured form of cryptographic hardness [IL89 …]

  3. Pseudorandom Generators Eff. computable function G:{0,1}s {0,1}m • Stretching (m >s) • Output is computationally indistinguishable from uniform. • Central in cryptography, implies pseudorandom functions [GGM86], pseudorandom permutations [LR88], bit-commitments [Naor91], … x G(x)

  4. Håstad, Imagliazzo, Levin and Luby 89 Theorem Existence of OWFs Existence of PRGs • Hardness vs. Randomness in purest cryptographic form • Centerpiece in basing Cryptography on OWFs • Introduced key concepts and techniques (Pseudoentropy, Leftover Hash Lemma, …). • inefficient and quite complex

  5. Efficiency For this talk efficiency (and security) of construction is measured by PRG’s seed length s (as function of n) • [HILL89] O(n10), [HILL89,Holens06] O(n8), [HHR06a] O(n7), HereO(n4) • From exponentially hard OWFs: [Holens06] O(n5), [HHR06b] O(n2), Here reprove O(n2)

  6. Simplicity With years, [HILL] became simpler • But mainly because we got used to it (tools and techniques became “standard”). • [HILL99,Holens06] additional abstractions and more modularity (+ Holenstein's Uniform Hard-Core Lemma) • Here simpler. • Construction non-adaptive thus derive “OWFs in NC1 PRGs in NC0 ” (via [AIK06])

  7. False Entropy Generator • Loosely, the most basic object in HILL is: Gfe(x,g,i)=f(x),g,g(x)1..i (think of g as matrix multiplication). Lemma Let k=log|f-1(f(x))|, then when i=k+log n then g,g(x)1..i is pseudorandom (even conditioned on f(x)). • Intuition: first k-clog n bits are statistically close to uniform (Leftover Hash Lemma) and next (c+1)log n bits are pseudorandom (GL Hard-Core Function).

  8. False Entropy Generator (II) Gfe(x,g,i)=f(x),g,g(x)1..i Lemma: For the variable Gfe(x,g,i)(with random inputs)  = pseudoentropy – real entropy > (log n)/n Reason:w.p1/n over choice of i (when i=k+log n) the output Gfe(x,g,i) is indistinguishable from distribution with entropy |x|+|g|+log n (whereas real entropy |x|+|g|) • Disadvantages:rather small, value of real entropy unknown, pseudoentropy < entropy of input

  9. Our Building Block • Simply do not truncate: Gnb(x,g)=f(x),g,g(x) • Nonsense: Gnb(x,g) is invertible and therefore has no pseudoentropy! • Well yes but: Gnb(x,g) does have psudoentropy from the point of view of an online distinguisher (getting one bit at a time).

  10. Next-Bit Pseudoentropy • X has pseudoentropy k if Y with H(Y)  k such that X and Y are indistinguishable • X=X1…Xn has next-bit pseudoentropy k if Y with • iH(Yi|X1…Xi)  k such that • X_i and Y_i are indistinguishable conditioned on X1…Xi-1 • Remarks: • X and Y arejointly distributed • The two notions are identical for k=n [BM, Yao] • Generalizes to blocks (rather than bits)

  11. Our Next-Block Pseudoentropy Generator • Gnb(x,g)=f(x),g,g(x) • Next-block pseudoentropy> |x|+|g|+logn • X=G(x,g) and Y obtained from X by replacing first k+logn bits of g(x) with uniform • Advantages: •  = next-block pseudoentropy –real entropy> logn • Entropy bounds known (on total entropy) • “No bit left behind” • Relates to work on inaccessible entropy [HRVW09]

  12. HILL Revisited - Overview Gnb x,g … … … • n2 repetitions: • amplifies entropy gap and • turns next-block pseudo Shannonentropy to next-block pseudo min entropy Extract next-block pseudoentropy

  13. Uniform Construction and Uniform Security • Seed length so far O(n3), but construction non uniform (need to know how much to extract from each block). • Using an idea from [HRVW09] get uniform construction with seed length O(n4). • To carry out the hybrid (for the n2repetitions), need X and Y to be next-block indistinguishable even given an oracle that samplesX and Y. • Just as in HILL, most elegant solution is via Holenstein's Uniform Hardcore Lemma [Holens06].

  14. Final Comment • Assume f is OW-Permutation. Given f(x) hard to find x. • Intuitively, given f(x) we have that x has some computational entropy in it, (thus we can extract this entropy). • Nevertheless, given f(x), we have that x does not have any pseudoentropy in it. • However, G’nb(x)=f(x),x is a next-block pseudoentropy generator • Does it also hold for OWFs?

  15. Widescreen Test Pattern (16:9) Aspect Ratio Test (Should appear circular) 4x3 16x9

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