. In order to support use with nodes of limited CPU processing capability, and to guard against Denial-of-Service attacks in which an attacker attempts to cause other nodes to consume excess network bandwidth or processing time, we use efficient one-way hash functions and do not use asymmetric cryptographic

A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, Prh∈F[h(x) = h(y)] = sim(x,y), where sim(x,y) ∈ [0, 1] is some similarity function defined on the collection of objects. Such a scheme leads

We present a simple dictionary with worst case constant lookup time, equaling the theoretical performance of the classic dynamic perfect hashing scheme of Dietzfelbinger et al. (Dynamic perfect hashing: Upper and lower bounds. SIAM J. Comput., 23(4):738–761, 1994). The space usage is similar

gperf is a "software-tool generating-tool" designed to automate the generation of perfect hash functions. This paper describes the features, algorithms, and object-oriented design and implementation strategies incorporated in gperf.Italso presents the results from an empirical comparison

Probabilistic hash functions that hide all partial information on their input were recently introduced. This new cryptographic primitive can be regarded as a function that offers "perfect one-wayness", in the following sense: Having access to the function value on some input

method, developed for collections that are relatively static, that supports both direct and sequential access. Indeed, the algorithm described gives hash functions that are optimal in terms of time and hash table space utilization, and that preserve any a priori ordering desired. Furthermore

A perfect hash function (PHF) h: S → [0, m − 1] for a key set S ⊆ U of size n, where m ≥ n and U is a key universe, is an injective function that maps the keys of S to unique values. A minimal perfect hash function (MPHF) is a PHF with m = n, the smallest possible range. Minimal perfect hash

Our previous research on one-probe access to large collec-tions of data indexed by alphanumeric keys has produced the first practical minimal perfect hash functions for this prob-lem. Here, a new algorithm is described for quickly finding minimal perfect hash functions whose specification space

Abstract Czech, Z.J., G. Havas and B.S. Majewski, An optimal algorithm for generating minimal perfect hash functions, Information Processing Letters 43 (1992) 257-264. A new algorithm for generating order preserving minimal perfect hash functions is presented. The algorithm is probabilistic

A heurisitic is given for finding minimal perfect hash functions without extensive searching. The procedure is to construct a set of graph (or hypergraph) models for the dictionary, then choose one of the models for use in constructing the minimal perfect hashing function. The construction