Affiliations: [a] Department of Mathematics and Computer Science, Brandon University, Brandon, Manitoba, Canada
| [b] Department of Computer Science and Engineering, School of Computing, SRM, Institute of Science and Technology, Chennai, India
| [c] Research Center for Interneural Computing, China Medical University, Taichung, Taiwan, Republic of China
Correspondence:
[*]
Corresponding author. Gautam Srivastava, Department of Mathematics and Computer Science, Brandon University,
Brandon, Manitoba, Canada. E-mail: [email protected].
Abstract: Securing a wireless sensor system is a hard task for researchers today. Strengthening the authentication system before connection establishment is the right way to enhance the architecture and also to provide secured communication from eavesdroppers. In this paper, we present a novel algorithm to enhance the security of data using a hybrid model which uses an adaptive encoding technique alongside Chaotic Hopfield Neural Network. The proposed computation upgrades the security of a key shared between any nodes. Our experimental results show that the security of transmitted data is better than traditional algorithms. Moreover, we also show that the computational time for the proposed algorithm is less than known traditional algorithms.
