Designing substitution boxes based on chaotic map and globalized firefly algorithm

Cipher strength mainly depends on the robust structure and a well-designed interaction of the components in its framework. A significant component of a cipher system, which has a significant influence on the strength of the cipher system, is the substitution box or S-box. An S-box is a vital and most essential component of the cipher system due to its direct involvement in providing the system with resistance against certain known and potential cryptanalytic attacks. Hence, research in this area has increased since the late 1980s, but there are still several issues in the design and analysis of the S-boxes for cryptography purposes. Therefore, it is not surprising that the design of suitable S-boxes attracts a lot of attention in the cryptography community. Nonlinearity, bijectivity, strict avalanche criteria, bit independence criteria, differential probability, and linear probability are the major required cryptographic characteristics associated with a strong S-box. Different cryptographic systems requiring certain levels of these security properties. Being that S- boxes can exhibit a certain combination of cryptographic properties at differing rates, the design of a cryptographically strong S-box often requires the establishment of a trade-off between these properties when optimizing the property values. To date, many S-boxes designs have been proposed in the literature, researchers have advocated the adoption of metaheuristic based S-boxes design. Although helpful, no single metaheuristic claim dominance over their other countermeasure. For this reason, the research for a new metaheuristic based S-boxes generation is still a useful endeavour. This thesis aim to provide a new design for 8 × 8 S-boxes based on firefly algorithm (FA) optimization. The FA is a newly developed metaheuristic algorithm inspired by fireflies and their flash lighting process. In this context, the proposed algorithm utilizes a new design for retrieving strong S- boxes based on standard firefly algorithm (SFA). Three variations of FA have been proposed with an aim of improving the generated S-boxes based on the SFA. The first variation of FA is called chaotic firefly algorithm (CFA), which was initialized using discrete chaotic map to enhance the algorithm to start the search from good positions. The second variation is called globalized firefly algorithm (GFA), which employs random movement based on the best firefly using chaotic maps. If a firefly is brighter than its other counterparts, it will not conduct any search. The third variation is called globalized firefly algorithm with chaos (CGFA), which was designed as a combination of CFA initialization and GFA. The obtained result was compared with a previous S-boxes based on optimization algorithms. Overall, the experimental outcome and analysis of the generated S-boxes based on nonlinearity, bit independence criteria, strict avalanche criteria, and differential probability indicate that the proposed method has satisfied most of the required criteria for a robust S-box without compromising any of the required measure of a secure S-box

Data Security Issues In Cloud Computing: Review

Cloud computing is an internet based model that empower on demand ease of access and pay for the usage of each access to shared pool of networks. It is yet another innovation that fulfills a client's necessity for computing resources like systems, stockpiling, servers, administrations and applications. Securing the Data is considered one of the principle significant challenges and concerns for cloud computing. This persistent problem is getting more affective due to the changes in improving cloud computing technology. From the perspective of the Clients, cloud computing is a security hazard especially when it comes to assurance affirmation issues and data security, remain the most basically which backs off for appropriation of Cloud Computing administrations. This paper audits and breaks down the essential issue of cloud computing and depicts the information security and protection of privacy issues in cloud

A bat-inspired testing strategy for generating constraints pairwise test suite

Indubitably, exhaustive testing is impractical in real world. Several sampling strategies have been introduced to minimize test data systematically. Complementing existing interaction based sampling strategies, pairwise testing has been extensively exploited resulting into many prototypes strategy implementations. Recently, the growing interests of adopting optimization algorithms as a backbone search engine for the new and upcoming search based software testing is increasing for newly developed test suite generation methods. This paper proposes an enhancement design and implementation of BTS strategy for constraints pairwise test generation based on the bat-inspired algorithm (BA). The benchmarking results of BTS show that it outperforms the generated test suite of the existing tools and strategies even in the presence of constraints