Browsing by Author "Damilare Peter Oyinloye"

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    A New Hash Function Based on Chaotic Maps and Deterministic Finite State Automata
    (IEEE, 2020-06-16) Moatsum Alawida; Je Sen Teh; Damilare Peter Oyinloye; Musheer Ahmad; Rami S Alkhawaldeh
    In this paper, a new chaos-based hash function is proposed based on a recently proposed structure known as the deterministic chaotic finite state automata (DCFSA). Out of its various configurations, we select the forward and parameter permutation variant, DCFSAFWP due to its desirable chaotic properties. These properties are analogous to hash function requirements such as diffusion, confusion and collision resistance. The proposed hash function consists of six machine states and three simple chaotic maps. This particular structure of DCFSA can process larger message blocks (leading to higher hashing rates) and optimizes its randomness. The proposed hash function is analyzed in terms of various security aspects and compared with other recently proposed chaos-based hash functions to demonstrate its efficiency and reliability. Results indicate that the proposed hash function has desirable statistical characteristics, elevated randomness, optimal diffusion and confusion properties as well as flexibility.
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    An Improved Image Scrambling Algorithm Using {2 n -1, 2 n , 2 n +1}
    (University of the West of Scotland, School of Computing, 2018-10-01) Damilare Peter Oyinloye; Kazeem Alagbe Gbolagade
    Traditional iris segmentation methods and strategies regularly contain an exhaustive search of a large parameter space, which is sensitive to noise, time-consuming and no longer secured enough. To address these challenges, this paper proposes a secured iris template. This paper proposes a technique to secure the iris template using steganography. The experimental analysis was carried out on matrix laboratory (MATLABR2015A) environment. The segmented iris region was normalized to decrease the dimensional inconsistencies between iris region areas with the aid of the usage of Hough transform (HT). The features of the iris were encoded by convolving the normalized iris region with 1D Log- Gabor filters in order to generate a bit-wise biometric template. Then, least significant bit (LSB) was used to secure the iris template. The Hamming distance was chosen as a matching metric, which gives the measure of how many bits disagreed between the templates of the iris. The system operated at a very good training time and high level of conditional testing signifying high optimization with recognition accuracy of 92% and error of 1.7%. The proposed system is reliable, secure and efficient with the computational complexity significantly reduced. The proposed technique provides an efficient approach for securing the iris template.
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    Image Encryption System based on Length Three Moduli Set
    (Foundation of Computer Science (FCS), NY, USA, 2018-05-01) Damilare Peter Oyinloye
    Digital images have found usage in almost all our everyday applications. These images sometimes contain confidential and intelligible information which need to be protected when stored on memory or transmitted over networks (Intranet or Internet). Many techniques have been proposed to deal with this security issues in the past. This paper proposes a simple scrambling algorithm to encrypt and decrypt the grey level image based on random number generation and Residue Number System (Forward and Reverse Conversion). The image is first encrypted by changing the position of each pixel in the original image without changing the value of grey level. The original image reads row by row, pixel by pixel and each pixel will take a new position in the scrambled image. The new position is chosen based on random number generation from the random number generator. The key will be generated as a matrix during the encryption process and also the key saves the position of each pixel in the encrypted/scrambled image. The encryption layer transforms the scrambled image to moduli images which automatically adds an extra security layer to our data. The encrypted moduli images is decrypted by decoding the moduli images and converting them back to a single scrambled image (Reverse Conversion) and the single scrambled image back to the Plain and Original Image by using the saved key matrix. This scheme achieves an enhanced image encryption process and a more efficient decryption process without loses of any inherent information of the recovered plain image.
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    Proof of Behaviour (PoBh): An Enhanced Proof of Stake Blockchain Consensus Protocol
    (International Journal of Advanced Studies in Computers, Science and Engineering, 2020-03-31) Damilare Peter Oyinloye
    Alternative protocols such as proof of stake (PoS) emerged after the drawbacks of proof of work (PoW) consensus protocol had been analyzed by researchers. Bitcon which is powered by proof of work consumes almost the same amount of energy as Ireland yearly among other drawbacks. PoS became the protocol of the moment because it reduces the unimaginable energy consumption in PoW with other enhancements. PoS was not without its shortcomings/drawbacks with respect to its performance, accountability and security. This work proposes a proof of behavior (PoBh) consensus protocol, an enhanced PoS algorithm with a much better performance, enhanced security and accountability.
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    SIM-P – A Simplified Consensus Protocols Simulator: Applications to Proof of Reputation-X and Proof of Contribution
    (IEEE, 2022-11-14) Damilare Peter Oyinloye; Je Sen Teh; Norziana Jamil; Jiashen Teh
    Blockchain is a distributed ledger in which participating users with varying levels of trust agree on the ledger’s content using a consensus mechanism called consensus protocols. There has been a rising interest in the design of consensus protocols since they play a central role in blockchain architecture. However, many recently proposed consensus protocols lack experimental verification which hampers the possible deployment of these protocols in real-world blockchain networks. In this article, we propose a simple tool called simplified consensus protocol simulator (SIM-P) that can accurately simulate the behavior of these consensus protocols with ease. It is an agent-based stochastic simulator that relies on the sequential Monte Carlo method to model how block publishers are selected. The likelihood of each node (represented as agents) being selected as a block publisher is represented by independent trials in a binomial experiment. We provide a base SIM-P model that simulates Proof of Work (PoW) for benchmarking purposes. The PoW model also serves as the basic structure of the simulator that can be adapted to other protocols. We showcase the flexibility of SIM-P by proposing two additional simulation models for Proof of Reputation-X and Proof of Contribution, both of which lack experimental verification in their original design specifications. We show how the simulator can be used to produce vital metrics, such as throughput, resistance against the 51% attack, and energy consumption. We verify the accuracy of SIM-P by comparing PoW’s simulated results with theoretical estimates and historical Bitcoin data.