Browsing by Author "Ajao, J."

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    Development of a Multi-Level Data Encryption Standard with Residue Number System for Data Security
    (Faculty of Communication and Information Sciences, University of Ilorin, Ilorin, Nigeria - Proceedings of the 3rd International Conference on ICT for National Development and its Sustainability, May 21-24, 2024 (ICT4NDS2024), 2024) Adebayo, A.; Adeniyi, A.E.; Ajao, J.; Isiaka, R.; Gbolagade, K.; Abdulsalam, S.
    Data security is critical in ensuring the privacy of data including sensitive material that ought to only be known by a few people. Every society needs secured data to maintain the integrity and authentication of the data. Data Encryption Standard (DES) is a block cipher algorithm that has been used to secure data or information over the years. Despite the tremendous efforts made by researchers on DES algorithm and efforts to reduce its computational complexity, DES is still susceptible to brute force attack. The need to increase the degree of security of DES algorithm led to the introduction of Residue Number System (RNS) to the DES algorithm as proposed in this study. The method for DES-RNS multilevel encryption uses a 64bits plaintext message which was encrypted using the DES technique. The 64bits plaintext message was divided into two equal halves; 32bit left plaintext (LPT) and 32bit right plaintext (RPT). The RPT was encrypted using 48bit sub-keys and the result was XORed with LPT. The transformation of RPT and LPT was performed for sixteen (16) rounds to produce encrypted text of 64bits. The encrypted text of DES was converted to American Standard Code for Information Interchange (ASCII) and passed through RNS forward conversion. The RNS made use of the moduli set 〖m_1=2 〗^n+1,m_2= 2^n and m_3=2^n-1. The decryption was performed using Chinese Remainder Theorem (CRT). The result was evaluated when it comes to cryptographic time, encryption/decryption memory, encryption/decryption throughput and security on three varying text sizes (256, 800 and 1472 bit) for DES only and DES-RNS multilevel cyrptosystem. Using DES, time and throughput shows a better performance for 256bit, 800bit and 1472bit message size but lesser performance in memory and security for 256bit, 800bit and 1472bit message size. On the other hand, using DES-RNS, time and throughput gives a lesser performance for 256bit, 800bit and 1472bit message size. Therefore, DES-RNS multilevel encryption model outperformed the conventional DES model in regard to storage utilization and safety, thereby achieving the aim of this research. Consequently, this DES-RNS model can be employed where security and memory conservation is of utmost concern. Keywords: Cryptography, Block Cipher, Data Encryption Standard (DES), Residue Number System (RNS)
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    Predicting Nigeria Budget Allocation Using Regression Analysis: A Data Mining Approach
    (Nigeria Computer Society (NCS), Lagos, Nigeria - The Journal of Computer Science and Its Application, An International Journal of the Nigeria Computer Society. 21(1), 73 – 82, 2014) Adewole, K.; Mabayoje, M.; Abdulsalam, S.; Ajao, J.
    Budget is used by the Government as a guiding tool for planning and management of its resources to aid in effective decision-making. Data mining is one of the most vital areas of research with the objective of finding meaningful information from large datasets. The delay in the preparation of budget of the Federation by the Government has become incessant issue in the running of affairs of the country. This is evident in the delay in implementation of the previous budgets in the country; hence, the need for automated system to tackle the setback. In this paper, regression analysis which is one of the data mining techniques is employed to predict budget allocation from Nigeria budget dataset. 200 records consisting of the budget allocation summary for the year 2008, 2009, 2010, 2011, and 2012 across 40 data points containing Ministries, Departments, Commissions and Agencies (MDCAs) were used. A web-based data mining tool that employed linear regression to predict both Nigeria budget allocation across the 40 data points and the overall budget summary allocation of the Federation is proposed. The proposed data mining software predicted N1,803,196,024,657.40, N1,871,754,338,112.68 and N2,007,780,403,902.98 for the year 2013, 2014 and 2015 respectively. The tool is found capable of discovering interesting patterns in the data and for predicting budget allocation. Keywords: Budget, Data Mining, Dataset, Linear Regression, Prediction