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Faculty of Accounting and Informatics

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    RSA and elliptic curve encryption system : a systematic literature review
    (IGI Global, 2024-03-20) Ugbedeojo, Musa; Adebiyi, Marion O.; Aroba, Oluwasegun Julius; Adebiyi, Ayodele, Ariyo; International Journal of Information Security and Privacy
    Almost every living species has a motive to communicate electronically with one another and preserve data for immediate or future use. These data are becoming too large to be maintained on personal storage devices. Technological innovation has cleared the path for vast, remote storage known as the cloud. This innovation is being provided as a service to people and organizations due to the high cost of investment and the high-tech skills needed for its maintenance. Despite the many benefits of cloud computing, data privacy, integrity, and access control are issues that require immediate attention. Many studies have been conducted in order to find solutions to these challenges. In this review, the authors look at the numerous methods that have been proposed to address these security challenges. The research revealed that elliptic curve cryptography and the advance encryption system (AES) were the techniques that were most frequently used to address security issues in the digital world.
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    A hyper-heuristic heterogeneous multisensor node scheme for energy efficiency in larger wireless sensor networks using DEEC-Gaussian algorithm
    (Hindawi Limited, 2021-02-15) Aroba, Oluwasegun Julius; Naicker, Nalindren; Adeliyi, Timothy
    A wireless sensor network (WSN) is an intellect-sustainable network that comprises multiple spatially distributed sensor nodes and several sink nodes that collect data from sensors. WSNs remain an active research area in the literature due to challenging factors such as the selection of sensor location according to a given premise, finding optimal routing algorithm, and ensuring energy efficiency and consumption. Minimizing energy and prolonging the network lifetime in the WSNs are the focus of this research work. In the literature, a clustering approach is used in grouping sensor nodes into clusters and is seen as an effective technique used in optimizing energy consumption in WSNs. Hence, in this paper, we put forward a novel clustering-based approach by amalgamating the Gaussian elimination method with the Distributed Energy-Efficient Clustering to produce DEEC_Gaussian (DEEC_Gaus) to stabilize energy efficiency optimization in WSNs. We took the advantages of DEEC and Gaussian elimination algorithms to resolve energy efficiency problems in WSNs. DEEC presents attributes such as increased heterogeneity performance level, clustering stability in operation, and energy efficiency which helps to prolong network lifetime while the Gaussian elimination algorithm added an additional advantage to improve and optimize energy efficiency, to aggregate packets of operations performed in the network lifestyle of energy efficiency in WSNs. The simulations were carried out using MATLAB software with 1000 to 1500 nodes. The performance of the proposed work was compared with state-of-the-art algorithms such as DEEC, DDEEC, and EDEEC_E. The simulated results presented show that the proposed DEEC-Gauss outperformed the three other conventional algorithms in terms of network lifetime, first node dead, tenth node dead, alive nodes, and the overall timing of the packets received at the base station. The results showed that the proposed hyper-heuristic heterogeneous multisensor DEEC-Gauss algorithm presented an average percentage of 3.0% improvement for the tenth node dead (TND) and further improvement of 4.8% for the first node dead (FND). When the performance was compared to the state-of-the-art algorithms in larger networks, the overall delivery was greatly improved and optimized.