On Constructing Parallel Pseudorandom Generators from One-Way Functions Emanuele Viola Harvard University June 2005.

Slides:



Advertisements
Similar presentations
Impagliazzos Worlds in Arithmetic Complexity: A Progress Report Scott Aaronson and Andrew Drucker MIT 100% QUANTUM-FREE TALK (FROM COWS NOT TREATED WITH.
Advertisements

On the Complexity of Parallel Hardness Amplification for One-Way Functions Chi-Jen Lu Academia Sinica, Taiwan.
Approximate List- Decoding and Hardness Amplification Valentine Kabanets (SFU) joint work with Russell Impagliazzo and Ragesh Jaiswal (UCSD)
1 Efficient Pseudorandom Generators from Exponentially Hard One-Way Functions Iftach Haitner, Danny Harnik, Omer Reingold.
Talk for Topics course. Pseudo-Random Generators pseudo-random bits PRG seed Use a short “ seed ” of very few truly random bits to generate a long string.
Uniform Hardness vs. Randomness Tradeoffs for Arthur-Merlin Games. Danny Gutfreund, Hebrew U. Ronen Shaltiel, Weizmann Inst. Amnon Ta-Shma, Tel-Aviv U.
1 Reducing Complexity Assumptions for Statistically-Hiding Commitment Iftach Haitner Omer Horviz Jonathan Katz Chiu-Yuen Koo Ruggero Morselli Ronen Shaltiel.
CS151 Complexity Theory Lecture 8 April 22, 2004.
Simple Affine Extractors using Dimension Expansion. Matt DeVos and Ariel Gabizon.
Circuit Complexity and Derandomization Tokyo Institute of Technology Akinori Kawachi.
A survey on derandomizing BPP and AM Danny Gutfreund, Hebrew U. Ronen Shaltiel, Weizmann Inst. Amnon Ta-Shma, Tel-Aviv U.
Hardness amplification proofs require majority Ronen Shaltiel University of Haifa Joint work with Emanuele Viola Columbia University June 2008.
Better Pseudorandom Generators from Milder Pseudorandom Restrictions Raghu Meka (IAS) Parikshit Gopalan, Omer Reingold (MSR-SVC) Luca Trevian (Stanford),
Using Nondeterminism to Amplify Hardness Emanuele Viola Joint work with: Alex Healy and Salil Vadhan Harvard University.
Time vs Randomness a GITCS presentation February 13, 2012.
The Bright Side of Hardness Relating Computational Complexity and Cryptography Oded Goldreich Weizmann Institute of Science.
Derandomization: New Results and Applications Emanuele Viola Harvard University March 2006.
ACT1 Slides by Vera Asodi & Tomer Naveh. Updated by : Avi Ben-Aroya & Alon Brook Adapted from Oded Goldreich’s course lecture notes by Sergey Benditkis,
Arithmetic Hardness vs. Randomness Valentine Kabanets SFU.
CS151 Complexity Theory Lecture 8 April 22, 2015.
GOING DOWN HILL: MORE EFFICIENT PSEUDORANDOM GENERATORS FROM ANY ONE-WAY FUNCTION Joint with Iftach Haitner and Salil Vadhan Omer Reingold&
Hardness amplification proofs require majority Emanuele Viola Columbia University Work done at Harvard, IAS, and Columbia Joint work with Ronen Shaltiel.
The Power of Randomness in Computation 呂及人中研院資訊所.
In a World of BPP=P Oded Goldreich Weizmann Institute of Science.
1 A New Interactive Hashing Theorem Iftach Haitner and Omer Reingold WEIZMANN INSTITUTE OF SCIENCE.
CS151 Complexity Theory Lecture 9 April 27, 2004.
1 On the Power of the Randomized Iterate Iftach Haitner, Danny Harnik, Omer Reingold.
Computational Entropy Joint works with Iftach Haitner (Tel Aviv), Thomas Holenstein (ETH Zurich), Omer Reingold (MSR-SVC), Hoeteck Wee (George Washington.
If NP languages are hard on the worst-case then it is easy to find their hard instances Danny Gutfreund, Hebrew U. Ronen Shaltiel, Haifa U. Amnon Ta-Shma,
GOING DOWN HILL : EFFICIENCY IMPROVEMENTS IN CONSTRUCTING PSEUDORANDOM GENERATORS FROM ONE-WAY FUNCTIONS Iftach Haitner Omer Reingold Salil Vadhan.
Can we base cryptography on SZK-Hardness? Salil Vadhan Harvard University.
A Linear Lower Bound on the Communication Complexity of Single-Server PIR Weizmann Institute of Science Israel Iftach HaitnerJonathan HochGil Segev.
Optimal Proof Systems and Sparse Sets Harry Buhrman, CWI Steve Fenner, South Carolina Lance Fortnow, NEC/Chicago Dieter van Melkebeek, DIMACS/Chicago.
Why Extractors? … Extractors, and the closely related “Dispersers”, exhibit some of the most “random-like” properties of explicitly constructed combinatorial.
On Constructing Parallel Pseudorandom Generators from One-Way Functions Emanuele Viola Harvard University June 2005.
Cryptography Lecture 2 Arpita Patra. Summary of Last Class  Introduction  Secure Communication in Symmetric Key setting >> SKE is the required primitive.
Using Nondeterminism to Amplify Hardness Emanuele Viola Joint work with: Alex Healy and Salil Vadhan Harvard University.
On the Communication Complexity of SFE with Long Output Daniel Wichs (Northeastern) joint work with Pavel Hubáček.
On approximate majority and probabilistic time Emanuele Viola Institute for advanced study Work done during Ph.D. at Harvard University June 2007.
Polynomials Emanuele Viola Columbia University work partially done at IAS and Harvard University December 2007.
Umans Complexity Theory Lectures Lecture 17: Natural Proofs.
CRYPTOGRAPHY AND NP-HARDNESS Andrej Bogdanov Chinese University of Hong Kong MACS Foundations of Cryptography| January 2016.
Pseudorandom Bits for Constant-Depth Circuits with Few Arbitrary Symmetric Gates Emanuele Viola Harvard University June 2005.
CRYPTOGRAPHIC HARDNESS OTHER FUNCTIONALITIES Andrej Bogdanov Chinese University of Hong Kong MACS Foundations of Cryptography| January 2016.
Hardness amplification proofs require majority Emanuele Viola Columbia University Work also done at Harvard and IAS Joint work with Ronen Shaltiel University.
Pseudo-random generators Talk for Amnon ’ s seminar.
Iftach Haitner and Eran Omri Coin Flipping with Constant Bias Implies One-Way Functions TexPoint fonts used in EMF. Read the TexPoint manual before you.
Error-Correcting Codes and Pseudorandom Projections Luca Trevisan U.C. Berkeley.
The Power of Negations in Cryptography
Almost SL=L, and Near-Perfect Derandomization Oded Goldreich The Weizmann Institute Avi Wigderson IAS, Princeton Hebrew University.
Pseudorandomness: New Results and Applications Emanuele Viola IAS April 2007.
Umans Complexity Theory Lectures Lecture 9b: Pseudo-Random Generators (PRGs) for BPP: - Hardness vs. randomness - Nisan-Wigderson (NW) Pseudo- Random Generator.
Pseudo-randomness. Randomized complexity classes model: probabilistic Turing Machine –deterministic TM with additional read-only tape containing “coin.
Complexity Theory and Explicit Constructions of Ramsey Graphs Rahul Santhanam University of Edinburgh.
B504/I538: Introduction to Cryptography
Cryptography Lecture 5 Arpita Patra © Arpita Patra.
Derandomization & Cryptography
Randomness and Computation
Pseudorandomness when the odds are against you
Pseudo-derandomizing learning and approximation
Cryptography Lecture 12 Arpita Patra © Arpita Patra.
Cryptography Lecture 5 Arpita Patra © Arpita Patra.
On the Efficiency of 2 Generic Cryptographic Constructions
Indistinguishability by adaptive procedures with advice, and lower bounds on hardness amplification proofs Aryeh Grinberg, U. Haifa Ronen.
Cryptography Lecture 5 Arpita Patra © Arpita Patra.
Emanuele Viola Harvard University June 2005
On Derandomizing Algorithms that Err Extremely Rarely
Emanuele Viola Harvard University October 2005
Pseudorandomness: New Results and Applications
Presentation transcript:

On Constructing Parallel Pseudorandom Generators from One-Way Functions Emanuele Viola Harvard University June 2005

Poly(n)-time Computable Stretch s(n) ¸ 1 (e.g., s(n) = 1, s(n) = n) Fools efficient adversaries: 8 PPT A Pr X, |X| = n+s(n) [A(X) = 1] ¼ Pr , |  | = n [A(PRG(  )) = 1] Pseudorandom Generator (PRG) [BM,Y] PRG

PRG, One-Way Functions (OWF) [BM,Y,GL,…,HILL] (f OWF if easy to compute but hard to invert, i.e. 8 PPT M, almost never M(f(X)) 2 f(X) -1 ) Applications of PRG: cryptography, derandomization need stretch s(n) = poly(n) Stretch s(n) only makes sense relative to n –E.g. G : {0,1} n ! {0,1} n+s(n) ) G : {0,1} n 2 ! {0,1} n 2 + n¢s(n) –Two main cases s(n) = 1, or s(n) = n Background on PRG

PRG Constructions We study complexity of constructing PRG with big stretch from OWF f Def.: black-box PRG constructions G f : for every (comput.-unbounded) function f, adversary A A breaks G f ) 9 PPT M : M f,A inverts f Most constructions are black-box [BM,Y,…,HILL] Many negat. results for black-box model [IR,…,GT,RTV] –Cannot make sense of negat. result in non-black-box model

STEP 1: OWF f ) G f : {0,1} n ! {0,1} n+1 –Think e.g. f : {0,1} n  ! {0,1} n  STEP 2: G f ) PRG with stretch s(n) = poly(n) [GM] Stretch s ) s adaptive queries to f ) circuit depth ¸ s Question [this work]: stretch s vs. adaptivity & depth? E.g., can have s = n, circuit depth O(log n)? Standard Constructions w/ big stretch GfGf Input  GfGf GfGf GfGf GfGf GfGf Output …

Previous Results [AIK] Log-depth OWF/PRG ) O(1)-depth PRG (!!!) However, any stretch ) stretch s = 1 [GT] s vs. number q of queries to OWF (Thm: q ¸ s) [This work] s vs. adaptivity & circuit depth [ …,IN,NR] O(1)-depth PRG from specific assumptions [This work] general assumptions Context: [V] studies complexity of NW-type PRG

Outline Our model Our results Proof sketch of main negative result Other: new negative result on worst-case vs. average-case connections in NP, PH

Parallel PRG G f : {0,1} n ! {0,1} n+s(n) from OWF f Our Model of PRG construction Input , |  | = n f ÆÆÆÆÆÆÆÆ Ç ÇÇÇÇÇ ÆÆÆÆÆÆÆÆ ff Constant Depth Circuit (AC 0 ) Output, n+s(n) bits f q 1 q 2 q 3 q 4 Nonadaptive Queries to f

Our Results on PRG Constructions Parallel construction G f : {0,1} n ! {0,1} n+s(n) From one-way function f ( e.g. f : {0,1} n  ! {0,1} n   f arbitraryf one-to-onef permutation Neg.s(n) · o(n) ? Pos.?s(n) ¸ 1

Thm[this work]: Parallel black-box PRG constructions G f : {0,1} n ! {0,1} n+s(n) satisfy s(n) · o(n) Proof: Exhibit comput.-unbounded f, A such that: (1) A breaks G f when s(n) =  (n) (2) f one-way, i.e. hard to invert. We show distribution on f s. t. (1) & (2) hold w.h.p. Proof Sketch of Negative Result

Def. of f and (1) break G f Restriction [FSS,H,…]  maps bits to {0,1,*} Def. distribution on f apply  to truth-table of f –  known to adversary A replace * with random bits (1) A breaks G f : 8 , G f (  ) is  AC  function of truth-table of f )  makes G f (  ) biased ) A breaks G f (  ). –If s(n) =  (n) can union bound over all . 01** 1*0*  1**0 f(0) f(1)  f(111)  1110

(2) f one-way Problem: f not one-way :  leaks info about x E.g. First bit f(x) = 0 ) x Solution: Force many x’s to share same restriction Compose f with hash function Many preimages ) f one-way Low collision prob. ) A still breaks G f Q.E.D. f(0) f(1) f(10)  f(111) 01** 1*0* 1***  1**0 hash 01** 1*0* 1***  1**0 f =

Question: given f 2 NP worst-case hard (f 2 P/poly), can build f 0 2 NP average-case hard? I.e. 8 small circuit A : Pr x [A(x)  f 0 (x)] ¸ 1/3 Thm[V]: no black-box construction of f 0 using both function f and adversary A as black-box Thm[BT]: no construction using A as black-box –Also uses A ``non-adaptively’’ Thm[this work]: no construction using f as black-box –Proof uses pseudorandom restrictions Our Result on Average Case Complexity

Conclusion Thm[this work]: Parallel black-box construction G f : {0,1} n ! {0,1} n+s(n) satisfy Average-case complexity Thm[this work]: given f 2 NP worst-case hard no construction of average-case hard f 0 2 NP using f as black-box f arbitraryf one-to-onef permutation Neg.s(n) · o(n) ? Pos.?s(n) ¸ 1