<--- Back to Details
First PageDocument Content
Information theory / Formal sciences / Key / Entropy / Cryptographically secure pseudorandom number generator / Randomness extractor / Cryptography / Randomness / Pseudorandom number generators
Date: 2013-12-19 22:46:27
Information theory
Formal sciences
Key
Entropy
Cryptographically secure pseudorandom number generator
Randomness extractor
Cryptography
Randomness
Pseudorandom number generators

Microsoft PowerPoint - dp-slides

Add to Reading List

Source URL: www.cs.nyu.edu

Download Document from Source Website

File Size: 762,66 KB

Share Document on Facebook

Similar Documents

Information retrieval / Information science / Hashing / Search algorithms / Universal hashing / Hash table / Linear probing / Hash function / Bloom filter / Cuckoo hashing / Randomness extractor / Cryptographic hash function

Why Simple Hash Functions Work: Exploiting the Entropy in a Data Stream∗ Michael Mitzenmacher† Salil Vadhan‡ School of Engineering & Applied Sciences Harvard University

DocID: 1r5sy - View Document

Information retrieval / Hashing / Information science / Search algorithms / Universal hashing / Hash table / Hash function / Linear probing / Cuckoo hashing / Bloom filter / Cryptographic hash function / Randomness extractor

Why Simple Hash Functions Work: Exploiting the Entropy in a Data Stream

DocID: 1qUBE - View Document

Cryptography / Theoretical computer science / Pseudorandomness / Randomness / Applied mathematics / Information theory / Computational complexity theory / Random number generation / Extractor / Entropy / Disperser / Pseudorandom generator

Lossless Condensers, Unbalanced Expanders, and Extractors Amnon Ta-Shma∗ Christopher Umans† David Zuckerman‡

DocID: 1qPOU - View Document

Cryptography / Theoretical computer science / Computational complexity theory / Theory of computation / Pseudorandomness / Random number generation / Randomness / Randomness extractor / Pseudorandom generator / Extractor / Advice / List decoding

Simple Extractors for All Min-Entropies and a New Pseudorandom Generator∗ Ronen Shaltiel † Christopher Umans ‡

DocID: 1qB1P - View Document

Statistics / Probability / Mathematical analysis / Probability distributions / Normal distribution / Randomness extractor / Exponential distribution / Central limit theorem / Gaussian function

LNCSOur Data, Ourselves: Privacy Via Distributed Noise Generation

DocID: 1pOcL - View Document