Publicly accessible databases are an indispensable resource for retrieving up-to-date information. But they also pose a significant risk to the privacy of the user, since a curious database operator can follow the user's queries and infer what the user is after. Indeed, in cases where the users' intentions are to be kept secret, users are often cautious about accessing the database. It can be shown that when accessing a single database, to completely guarantee the privacy of the user, the whole database should be down-loaded; namely n bits should be communicated (where n is the number of bits in the database).In this work, we investigate whether by replicating the database, more efficient solutions to the private retrieval problem can be obtained. We describe schemes that enable a user to access k replicated copies of a database (k≥2) and privately retrieve information stored in the database. This means that each individual server (holding a replicated copy of the database) gets no information on the identity of the item retrieved by the user. Our schemes use the replication to gain substantial saving. In particular, we present a two-server scheme with communication complexity O(n1/3).

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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.

Boolean circuit complexity is the combinatorics of computer science and involves many intriguing problems that are easy to state and explain, even for the layman. This book is a comprehensive description of basic lower bound arguments, covering many of the gems of this complexity Waterloo that have been discovered over the past several decades, right up to results from the last year or two. Many open problems, marked as Research Problems, are mentioned along the way. The problems are mainly of combinatorial flavor but their solutions could have great consequences in circuit complexity and computer science. The book will be of interest to graduate students and researchers in the fields of computer science and discrete mathematics.

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Boolean Function Complexity: Advances and Frontiers

Given m copies of the same problem, does it take m times the amount of resources to solve these m problems? This is the direct sum problem, a fundamental question that has been studied in many computational models. We study this question in the simultaneous message (SM) model of communication introduced by A.C. Yao (1979). The equality problem for n-bit strings is well known to have SM complexity /spl Theta/(/spl radic/n). We prove that solving m copies of the problem has complexity /spl Omega/(m/spl radic/n); the best lower bound provable using previously known techniques is /spl Omega/(/spl radic/(mn)). We also prove similar lower bounds on certain Boolean combinations of multiple copies of the equality function. These results can be generalized to a broader class of functions. We introduce a new notion of informational complexity which is related to SM complexity and has nice direct sum properties. This notion is used as a tool to prove the above results; it appears to be quite powerful and may be of independent interest.

https://www.cs.dartmouth.edu/~ac/Pubs/focs01-infocomplex.pdf

Informational complexity and the direct sum problem for simultaneous message complexity

Private information retrieval (PIR) protocols allow a user to retrieve a data item from a database while hiding the identity of the item being retrieved. Specifically, in information-theoretic, k-server PIR protocols the database is replicated among k servers, and each server learns nothing about the item the user retrieves. The cost of such protocols is measured by the communication complexity of retrieving one out of n bits of data. For any fixed k, the complexity of the best protocols prior to our work was O(n/sup 1/2k-1/). Since then several methods were developed in an attempt to beat this bound, but all these methods yielded the same asymptotic bound. In this paper, this barrier is finally broken and the complexity of information-theoretic k-server PIR is improved to n/sup O(log log k/k log k)/. The new PIR protocols can also be used to construct k-query binary locally decodable codes of length exp(n/sup O(log log k/k log k)/), compared to exp(n/sup 1/k-1/) in previous constructions. The improvements presented in this paper apply even for small values of k: the PIR protocols are more efficient than previous ones for every k/spl ges/3, and the locally decodable codes are shorter for every k/spl ges/4.

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Breaking the O(n/sup 1/(2k-1)/) barrier for information-theoretic Private Information Retrieval

We solve a 17 year old problem of A.C.C. Yao (1979). In the two-player communication model introduced by Yao in 1979, Alice and Bob wish to collaboratively evaluate a function f(x,y) in which Alice knows only input x and Bob knows only input y. Both players have unlimited computational power. The objective is to minimize the amount of communication. Yao (1979) also introduced an oblivious version of this communication game which we call the simultaneous messages (SM) model. The difference is that in the SM model, Alice and Bob don't communicate with each other. Instead, they simultaneously send messages to a referee, who sees none of the input. The referee then announces the function value. The deterministic two-player SM complexity of any function is straight forward to determine. Yao suggested the randomized version of this model, where each player has access to private coin flips. Our main result is that the order of magnitude of the randomized SM complexity of any function f is at least the square root of the deterministic SM complexity of f. We found this result in February 1996, independently but subsequently to I. Newman and M. Szegedy (1996) who obtained this lower bound for the special case of the "equality" function. Our proof is entirely different from and considerably simpler than the Newman-Szegedy solution. A proof similar in spirit to ours, was found by J. Bourgain and A. Wigderson simultaneously to us (unpublished); we include an outline of their proof. The quadratic reduction actually does occur for the "equality" function. We give a new proof of this fact. This result, combined with our main result, settles Yao's question, asking the exact randomized SM complexity of the equality function. The lower bound proof uses the probabilistic method; the upper bound uses linear algebra. We also give a constructive proof that O(log n) public coins reduce the complexity of "equality" to constant.

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Randomized simultaneous messages: solution of a problem of Yao in communication complexity

In the multiparty communication game (CFL game) of Chandra, Furst, and Lipton [Proceedings of the 15th Annual ACM Symposium on Theory of Computing, Boston, MA, 1983, pp. 94--99] k players collaboratively evaluate a function f(x0, . . . , xk-1) in which player i knows all inputs except xi. The players have unlimited computational power. The objective is to minimize communication.
In this paper, we study the SIMULTANEOUS MESSAGES (SM) model of multiparty communication complexity. The SM model is a restricted version of the CFL game in which the players are not allowed to communicate with each other. Instead, each of the k players simultaneously sends a message to a referee, who sees none of the inputs. The referee then announces the function value.
We prove lower and upper bounds on the SM complexity of several classes of explicit functions. Our lower bounds extend to randomized SM complexity via an entropy argument. A lemma establishing a tradeoff between average Hamming distance and range size for transformations of the Boolean cube might be of independent interest.
Our lower bounds on SM complexity imply an exponential gap between the SM model and the CFL model for up to $(\log n)^{1-\epsilon}$ players for any $\epsilon > 0$. This separation is obtained by comparing the respective complexities of the Generalized Addressing Function, GAFG,k, where G is a group of order n. We also combine our lower bounds on SM complexity with the ideas of Hastad and Goldmann [Comput. Complexity, 1 (1991), pp. 113--129] to derive superpolynomial lower bounds for certain depth-2 circuits computing a function related to the GAF function.
We prove some counterintuitive upper bounds on SM complexity. We show that {\sf GAF}$_{\mathbb{Z}_2^t,3}$ has SM complexity $O(n^{0.92})$. When the number of players is at least $c\log n$, for some constant c>0, our SM protocol for {\sf GAF}$_{\mathbb{Z}_2^t,k}$ has polylog(n) complexity. We also examine a class of functions defined by certain depth-2 circuits. This class includes the Generalized Inner Product function and Majority of Majorities. When the number of players is at least 2+log n, we obtain polylog(n) upper bounds for this class of functions.

/pdf/communication-complexity-of-simultaneous-messages-2gg6rxez18.pdf

Communication Complexity of Simultaneous Messages

In the multiparty communication game introduced by Chandra, Furst, and Lipton [CFL] (1983), k players wish to evaluate collaboratively a function f(x0,⋯, xk−1 for which player i sees all inputs except x i . The players have unlimited computational power. The objective is to minimize the amount of communication.

Simultaneous messages vs. communication

We generalize the multiparty communication model of Chandra, Furst, and Lipton (1983) to functions with b-bit output (b = 1 in the CFL model). We allow the players to receive up to b 1 bits of information from an all-powerful benevolent Helper who can see all the input. Extending results of Babai, Nisan, and Szegedy (1992) to this model, we construct families of explicit functions for which ( n/c k ) bits of communication are required to find the “missing bit,” where n is the length of each player’s input and k is the number of players. As a consequence we settle the problem of separating the one-way vs. multiround communication complexities (in the CFL sense) for k (1 )logn players, extending a result of Nisan and Wigderson (1991) who demonstrated this separation for k = 3 players. As a byproduct we obtain ( n/c k ) lower bounds for the multiparty complexity (in the CFL sense) of new families of explicit boolean functions (not derivable from BNS).

/pdf/the-cost-of-the-missing-bit-communication-complexity-with-4e75gvexkb.pdf

The cost of the missing bit: communication complexity with help

We generalize the multiparty communication model of Chandra, Furst, and Lipton (1983) to functions with b-bit output (b = 1 in the CFL model). We allow the players to receive up to b - 1 bits of information from an all-powerful benevolent Helper who can see all the input. Extending results of Babai, Nisan, and Szegedy (1992) to this model, we construct families of explicit functions for which bits of communication are required to find the "missing bit", where n is the length of each player's input and k is the number of players. As a consequence we settle the problem of separating the one-way vs. multiround communication complexities (in the CFL sense) for players, extending a result of Nisan and Wigderson (1991) who demonstrated this separation for k = 3 players. As a by-product we obtain lower bounds for the multiparty complexity (in the CFL sense) of new families of explicit boolean functions (not derivable from BNS). The proofs exploit the interplay between two concepts of multicolor discrepancy; discrete Fourier analysis is the basic tool. We also include an unpublished lower bound by A. Wigderson regarding the one-way complexity of the 3-party pointer jumping function.

Peter G. Kimmel

Papers

Randomized simultaneous messages: solution of a problem of Yao in communication complexity

Communication Complexity of Simultaneous Messages

Simultaneous messages vs. communication

The cost of the missing bit: communication complexity with help

The Cost of the Missing Bit: Communication Complexity with Help