Nature Inspired Hybrid Algorithm for Binding Shared Key with User Trait

Abstract

Increased digital transactions accentuate the need for secure communication over open channels. Confidentiality and safe distribution of shared key is a mandatory requirement in symmetric key-based systems. The work proposes a novel nature inspired optimisation technique for binding secret key with user traits extracted from iris biometrics. Validation of key binding is demonstrated by ensuring that successful decryption happens by authorised user alone. Nature inspired swarm and population algorithms are used to extract optimal feature vectors from user trait. Chicken swarm optimisation and deer hunting optimisation algorithms have been used for the first time with iris traits to achieve optimal key binding. Experiments for different shared key lengths have been carried out with IIT Delhi and Multimedia University iris datasets. Accuracy of the proposed model is 7% better than whale optimisation algorithm and 4% better than grey wolf optimisation.