A Memory Optimized Public-Key Crypto Algorithm Using Modified Modular Exponentiation (MME)

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dc.contributor.authorOluwatope, A. O.
dc.contributor.authorOjo, B. A.
dc.contributor.authorAderounmu, G. A.
dc.contributor.authorAdigun, M. O.
dc.date.accessioned2023-05-13T16:48:43Z
dc.date.available2023-05-13T16:48:43Z
dc.date.issued2016-06
dc.descriptionInternational Journal of Advanced Pervasive and Ubiquitous Computing,volume 8,No 2 p,16-17.en_US
dc.description.abstractThis study designed, simulated and evaluated the performance of a conceptual framework for ambient ad hoc home network. This was with a view to detecting malicious nodes and securing the home devices against attacks. The proposed framework, called mobile ambient social trust consists of mobile devices and mobile ad hoc network as communication channel. The trust model for the device attacks is Adaptive Neuro Fuzzy (ANF) that considered global reputation of the direct and indirect communication of home devices and remote devices. The model was simulated using Matlab 7.0. In the simulation, NSL-KDD dataset was used as input packets, the artificial neural network for packet classification and ANF system for the global trust computation. The proposed model was benchmarked with an existing Eigen Trust (ET) model using detection accuracy and convergence time as performance metrics. The simulation results using the above parameters revealed a better performance of the ANF over ET model. The framework will secure the home network against unforeseen network disruption and node misbehavior.en_US
dc.identifier.urihttps://ir.oauife.edu.ng/123456789/5362
dc.language.isoenen_US
dc.publisherInternational Journal of Advanced Pervasive and Ubiquitous Computingen_US
dc.subjectAd Hoc Home Networken_US
dc.subjectAdaptive Neuro Fuzzyen_US
dc.subjectAmbienten_US
dc.subjectDevice Attacksen_US
dc.subjectTrust Managementen_US
dc.titleA Memory Optimized Public-Key Crypto Algorithm Using Modified Modular Exponentiation (MME)en_US
dc.typeJournalen_US
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