Modupe O. Odusami

Work place: Covenant University/ Department of Electrical and Information Engineering, Ota, Nigeria



Research Interests: Computational Engineering, Software Engineering, Computer systems and computational processes, Computer Architecture and Organization, Embedded System, Computer Networks


Modupe Odusami obtained a B.Eng.  degree in Electrical  Engineering at the University of Ilorin in 2000. She further obtained her Master’s degree (M.Sc.) in Information Technology from the Bells University, Ota in 2015. She is currently pursuing her Ph.D. in Computer Engineering at the Covenant University, Ota. She is a member of several professional bodies such as the Nigerian Society of Engineers (NSE), Institute of Electrical and Electronics Engineers (NIEE), She has published in scholarly journals both National and International. Her current research interests include Software Engineering, Embedded System, Computer Security and Networking. She is a Lecturer II at the Department of Electrical and Information Engineering, College of Engineering, Covenant University, Ota, Ogun State, Nigeria. She is happily married with three kids.

Author Articles
An Improved Model for Securing Ambient Home Network against Spoofing Attack

By Solomon A. Akinboro Adebayo Omotosho Modupe O. Odusami

DOI:, Pub. Date: 8 Feb. 2018

Mobile Ad hoc Networks (MANET) are prone to malicious attacks and intermediate nodes on the home network may spoof the packets being transmitted before reaching the destination. This study implements an enhanced Steganography Adaptive Neuro-Fuzzy Algorithm (SANFA) technique for securing the ambient home network against spoofing attacks. Hybrid techniques that comprises image steganography, adaptive neuro-fuzzy and transposition cipher were used for the model development. Two variant of the model: SANFA and transpose SANFA were compared using precision and convergence time as performance metrics. The simulation results showed that the transpose SANFA has lower percentage of precision transmitting in a smaller network and a higher percentage of precision transmitting in a larger network. The convergence time result showed that packet transmitted in a smaller network size took longer time to converge while packet transmitted in a larger network size took shorter period to converge.

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