000			01926nam a2200133 4500
008			250825b |||||||| |||| 00| 0 eng d
100			_aC.A. Yogaraja
245			_aCryptography in IoT Using Elliptic Curve Cryptography with Adaptive Hunter-Prey Optimization
300			_ap1119-1133
520			_aThe Internet of Things (IoT) is utilized in different applications and the increasing connectivity of IoT devices raises significant concerns regarding data security and privacy. Security is a major aspect and a fundamental necessity in IoT design. The rise in cyberattacks necessitates the development of an effective strategic approach to safeguard IoT systems. Better data security in IoT has become a significant challenge and this issue can be addressed by evaluating proper encryption techniques while storing data in IoT environments. Cryptographic techniques should be lightweight, efficient, and versatile to the limited computational resources of IoT devices. This work proposes an approach called Elliptic Curve Cryptography (ECC) with the Adaptive Hunter Prey Optimization (AHPO) algorithm for providing data security in IoT. The encryption technique ECC provides a robust and lightweight encryption mechanism and the AHPO is employed for optimal key generation and management processes, enhancing both security and efficiency. Then, the encrypted data are hashed by the MD-5 algorithm. The suggested model addresses the need for reduced computational load and power consumption in IoT environments and maintaining a high level of security. Experimental outcomes demonstrate the efficacy of this approach in optimizing cryptographic operations, making it a feasible solution to secure IoT networks.
654			_aAdaptive hunter-prey optimization _aData security _aEncryption _aInternet of Things _aOptimal key generation
773	0		_080269 _9113443 _dNew Delhi IETE _tIETE Journal of Research _x0377-2063
942			_cJA
999			_c132569 _d132569