Adaptive Bloom filter

A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information, and has broad applications. In this paper, we generalize the traditional Bloom filter to Adaptive Bloom Filter, which incorporates the information on the query frequencies and the membership likelihood of the elements into its optimal design. It has been widely observed that in many applications, some popular elements are queried much more often than the others. The traditional Bloom filter for data sets with irregular query patterns and non-uniform membership likelihood can be further optimized. We derive the optimal configuration of the Bloom filter with query-frequency and membership-likelihood information, and show that the adapted Bloom filter always outperforms the traditional Bloom filter. Under reasonable frequency models such as the step distribution or the Zipf's distribution, the improvement of the false positive probability of the adaptive Bloom filter over that of the traditional Bloom filter is usually of orders of magnitude

Query Authentication and processing on outsourced databases

Master'sMASTER OF SCIENC

Zero-Knowledge Accumulators and Set Operations

Accumulators provide a way to succinctly represent a set with elements drawn from a given domain, using an \emph{accumulation value}. Subsequently, short proofs for the set-\emph{membership} (or \emph{non-membership}) of any element from the domain can be constructed and efficiently verified with respect to this accumulation value. Accumulators have been widely studied in the literature, primarily, as an \emph{authentication} primitive: a malicious prover (e.g., an untrusted server) should not be able to provide convincing proofs on false statements (e.g., successfully prove membership for a value not in the set) to a verifier that issues membership queries (of course, having no access to set itself). In essence, in existing constructions the accumulation value acts as a (honestly generated) ``commitment\u27\u27 to the set that allows selective ``opening\u27\u27 as specified by membership queries---but with no ``hiding\u27\u27 properties. In this paper we revisit this primitive and propose a privacy-preserving enhancement. We define the notion of a \emph{zero-knowledge accumulator} that provides the following very strong privacy notion: Accumulation values and proofs constructed during the protocol execution leak nothing about the set itself, or any subsequent updates to it (i.e., via element insertions/deletions). We formalize this property by a standard real/ideal execution game. An adversarial party that is allowed to choose the set and is given access to query and update oracles, cannot distinguish whether this interaction takes place with respect to the honestly executed algorithms of the scheme or with a simulator that is not given access to the set itself (and for updates, it does not even learn the type of update that occurred---let alone the inserted/deleted element). We compare our new privacy definition with other recently proposed similar notions showing that it is strictly stronger: We give a concrete example of the update-related information that can be leaked by previous definitions. We provide a mapping of the relations between zero-knowledge accumulators and primitives that are either set in the same security model or solve the same problem. We formally show and discuss a number of implications among primitives, some of which are not immediately evident. We believe this contribution is interesting on its own, as the area has received considerable attention recently (e.g., with the works of [Naor et al., TCC~2015] and [Derler et al., CT-RSA~2015]). We then construct the first dynamic universal zero-knowledge accumulator. Our scheme is perfect zero-knowledge and is secure under the $q$-Strong Bilinear Diffie-Hellman assumption. Finally, building on our dynamic universal zero-knowledge accumulator, we define a \emph{zero-knowledge authenticated set collection} to handle more elaborate set operations (beyond set-membership). In particular, this primitive allows one to outsource a collection of sets to an untrusted server that is subsequently responsible for answering union, intersection and set difference queries over these sets issued by multiple clients. Our scheme provides proofs that are succinct and efficiently verifiable and, at the same time, leak nothing beyond the query result. In particular, it offers verification time that is asymptotically optimal (namely, the same as simply reading the answer), and proof construction that is asymptotically as efficient as existing state-of-the-art constructions--- that however, do not offer privacy

Trust-Preserving Set Operations

We describe a method of performing trustpreserving set operations by untrusted parties. Our motivation for this is the problem of securely reusing contentbased search results in peer-to-peer networks. We model search results and indexes as data sets. Such sets have value for answering a new query only if they are trusted. In the absence of any system-wide security mechanism, a data set is trusted by a node a only if it was generated by some node trusted by a. Our mai