Benny Chor

Private information retrieval

We describe schemes that enable a user to access k replicated copies of a database (k/spl ges/2) and privately retrieve information stored in the database. This means that each individual database gets no information on the identity of the item retrieved by the user. For a single database, achieving this type of privacy requires communicating the whole database, or n bits (where n is the number of bits in the database). Our schemes use the replication to gain substantial saving. In particular, we have: A two database scheme with communication complexity of O(n/sup 1/3/). A scheme for a constant number, k, of databases with communication complexity O(n/sup 1/k/). A scheme for 1/3 log/sub 2/ n databases with polylogarithmic (in n) communication complexity.

Tracing traitors

We give cryptographic schemes that help trace the source of leaks when sensitive or proprietary data is made available to a large set of parties. A very relevant application is in the context of pay television, where only paying customers should be able to view certain programs. In this application, the programs are normally encrypted, and then the sensitive data is the decryption keys that are given to paying customers. If a pirate decoder is found, it is desirable to reveal the source of its decryption keys. We describe fully resilient schemes which can be used against any decoder which decrypts with nonnegligible probability. Since there is typically little demand for decoders which decrypt only a small fraction of the transmissions (even if it is nonnegligible), we further introduce threshold tracing schemes which can only be used against decoders which succeed in decryption with probability greater than some threshold. Threshold schemes are considerably more efficient than fully resilient schemes.

Discovering local structure in gene expression data: the order-preserving submatrix problem.

This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing methods for pattern discovery in such matrices are based on clustering genes by comparing their expression levels in all experiments, or clustering experiments by comparing their expression levels for all genes. Our work goes beyond such global approaches by looking for local patterns that manifest themselves when we focus simultaneously on a subset G of the genes and a subset T of the experiments. Specifically, we look for order-preserving submatrices (OPSMs), in which the expression levels of all genes induce the same linear ordering of the experiments (we show that the OPSM search problem is NP-hard in the worst case). Such a pattern might arise, for example, if the experiments in T represent distinct stages in the progress of a disease or in a cellular process and the expression levels of all genes in G vary across the stages in the same way. We define a probabilistic model in which an OPSM is hidden within an otherwise random matrix. Guided by this model, we develop an efficient algorithm for finding the hidden OPSM in the random matrix. In data generated according to the model, the algorithm recovers the hidden OPSM with a very high success rate. Application of the methods to breast cancer data seem to reveal significant local patterns.

Unbiased bits from sources of weak randomness and probabilistic communication complexity

A new model for weak random physical sources is presented. The new model strictly generalizes previous models (e.g., the Santha and Vazirani model [27]). The sources considered output strings according to probability distributions in which no single string is too probable.The new model provides a fruitful viewpoint on problems studied previously such as: • Extracting almost-perfect bits from sources of weak randomness. The question of possibility as well as the question of efficiency of such extraction schemes are addressed. • Probabilistic communication complexity. It is shown that most functions have linear communication complexity in a very strong probabilistic sense. • Robustness of BPP with respect to sources of weak randomness (generalizing a result of Vazirani and Vazirani [32], [33]).

The bit extraction problem or t-resilient functions

We consider the following adversarial situation. Let n, m and t be arbitrary integers, and let f : {0, 1}n → {0, 1}m be a function. An adversary, knowing the function f, sets t of the n input bits, while the rest (n-t input, bits) are chosen at random (independently and with uniform probability distribution) The adversary tries to prevent the outcome of f from being uniformly distributed in {0, 1}m. The question addressed is for what values of n, m and t does the adversary necessarily fail in biasing the outcome of f : {0,1}n → {0, 1}m, when being restricted to set t of the input bits of f. We present various lower and upper bounds on ms allowing an affirmative answer. These bounds are relatively close for t ≤ n/3 and for t ≥ 2n/3. Our results have applications in the fields of faulttolerance and cryptography.

RSA and Rabin functions: certain parts are as hard as the whole

The RSA and Rabin encryption functions

A knapsack-type public key cryptosystem based on arithmetic in finite fields

E_N ( \cdot )

On the power of two-point based sampling

are respectively defined by raising

Computationally private information retrieval (extended abstract)

x \in Z_N

Tight lower bounds for certain parameterized NP-hard problems

to the power e (where e is relatively prime to