Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Artificial Bee Colony


Proposal New S-box for AES Algorithm Depend on A.I Bee Colony

Alaa Kadhim; Sura Khalaf

Engineering and Technology Journal, 2015, Volume 33, Issue 1, Pages 12-24

The AES algorithm, also called the Rijndael algorithm, is a symmetric block cipher, where the data are encrypted/ decrypted in blocks of 128 bits. Each data block is modified by several rounds of processing, where each round involves four steps. Three different key sizes are allowed: 128 bits, 192 bits, or 256 bits, and the corresponding number of rounds for each is 10 rounds, 12 rounds, or 14 rounds, respectively. From the original key, a different “round key” is computed for each of these rounds. The single nonlinear step is the Sub Bytes step, where each byte of the input is replaced by the result of applying the “S-box” function to that byte. This nonlinear function involves finding the inverse of the 8-bit number, considered as an element of the Galois field GF (216). The Galois inverse is not a simple calculation, and so many current implementations use a table of the S-box function output. This table look-up method is fast and easy to implement. S-box is influenced by linear and differential cryptanalysis and also interpolation attacks. In this paper intended a new approach for the design of s-box based on the bee colony algorithm to increase the power of s-box and enhanced resistance against attacks through the use of artificial intelligence algorithms.

Artificial Bee Colony based Approach for Web Information Retrieval

Hasanen S. Abdullah; Mustafa J. Hadi

Engineering and Technology Journal, 2014, Volume 32, Issue 5, Pages 899-909

With the tremendous growth of information in the web, the classic query processing approaches are unable to respond to queries in real time. The aim of this paper is to develop an innovative tool using swarm intelligence to address information retrieval in the context of response time and solution quality through cope with the complexity induced by that huge volume of information. In this paper, we will show that our proposed approach that use of Artificial Bee Colony (ABC) algorithm called MABC can be another alternative to palliate the complexity issue in terms of response time while it produces a solution quality is relatively convergent or even better. Experimental tests have been conducted on two well-known CACM and NPL collections. Both are different in size, CACM is small while NPL is relatively large. Numerical results exhibit the superiority and the benefit gained from using the MABC approach instead of the classic approaches.