This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength (ACW(n)) algorithm. The proposed scheme enhances the compression ratio of the ACW(n) algorithm by dividing the binary sequence into a number of subsequences (s), each of them satisfying the condition that the number of decimal values (d) of the n-bit length characters is equal to or less than 256. Therefore, the new scheme is referred to as ACW(n, s), where n is the adaptive character wordlength and s is the number of subsequences. The new scheme was used to compress a number of text files from standard corpora. The obtained results demonstrate that the ACW(n, s) scheme achieves higher compression ratio than many widely used compression algorithms and it achieves a competitive performance compared to state-of-the-art compression tools.

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This study introduces a method for generating a particular permutation P of a given size N out of N! permutations from a given key. This method computes a unique permutation for a specific size since it takes the same key; therefore, the same permutation can be computed each time the same key and size are applied. The name of random permutation comes from the fact that the probability of getting this permutation is 1 out of N! possible permutations. Beside that, the permutation can not be guessed because of its generating method that is depending completely on a given key and size.

In this paper, we propose a new web search engine model based on index-query bit-level compression. The model incorporates two bit-level compression layers both implemented at the backend processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index, and the second layer be located after the query parser for query compression to enable bit-level compressed index-query search. This contributes to reducing the size of the index file as well as reducing disk I/O overheads, and consequently yielding higher retrieval rate and performance. The data compression scheme used in this model is the adaptive character wordlength (ACW(n,s)) scheme, which is an asymmetric, lossless, bit-level scheme that permits compressed index-query search. Results investigating the performance of the ACW(n,s) scheme is presented and discussed.

This study presents a new efficient password-based strong key derivation algorithm using the key based random permutation the KBRP method. The algorithm consists of five steps, the first three steps are similar to those formed the KBRP method. The last two steps are added to derive a key and to ensure that the derived key has all the characteristics of a strong key. In order to demonstrate the efficiency of the algorithm, a number of keys are derived using various passwords of different content and length. The features of the derived keys show a good agreement with all characteristics of strong keys. In addition, they are compared with features of keys generated using the WLAN strong key generator v2.2 by Warewolf Labs.