An Improved Model for Securing Ambient Home Network against Spoofing Attack

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Solomon A. Akinboro 1,* Adebayo Omotosho 2 Modupe O. Odusami 3

1. Bells University of Technology/ Department of Computer Science and Information Technology, Ota, Nigeria

2. Landmark University/ Department of Computer Science, Omu-Aran, Nigeria

3. Covenant University/ Department of Electrical and Information Engineering, Ota, Nigeria

* Corresponding author.


Received: 27 Sep. 2017 / Revised: 20 Oct. 2017 / Accepted: 7 Nov. 2017 / Published: 8 Feb. 2018

Index Terms

Spoofing, Steganography, MANET, Home network, Ambient, Transposition cipher, Adaptive-neuro-fuzzy


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.

Cite This Paper

Solomon A. Akinboro, Adebayo Omotosho, Modupe O. Odusami, "An Improved Model for Securing Ambient Home Network against Spoofing Attack", International Journal of Computer Network and Information Security(IJCNIS), Vol.10, No.2, pp.20-26, 2018. DOI:10.5815/ijcnis.2018.02.03


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