Int. J. Applied Pattern Recognition, Vol. 6, No. 3, 2021 217 Copyright © 2021 Inderscience Enterprises Ltd. Nature inspired hybrid algorithms for binding shared key with user trait P. Suresh* and K.R. Radhika Department of Information Science and Engineering, BMS College of Engineering, Visvesvaraya Technological University, India Email: sureshpad@rediffmail.com Email: rkr.ise@bmsce.ac.in *Corresponding author 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. Keywords: symmetric key; iris biometric; nature inspired algorithms; neural network. Reference to this paper should be made as follows: Suresh, P. and Radhika, K.R. (2021) ‘Nature inspired hybrid algorithms for binding shared key with user trait’, Int. J. Applied Pattern Recognition, Vol. 6, No. 3, pp.217–231. Biographical notes: P. Suresh is a Research Scholar with deep interest in pattern recognition, biometrics and identity management systems. He has worked on dynamic signature, fingerprint, iris and facial emotions. He received his Bachelor of Engineering in Electronics and Communication from the College of Engineering, Guindy and Master of Technology in Computer Science and Engineering from IIT, Delhi. He is currently a PhD scholar from the VTU and has been exploring nature inspired algorithms for extracting optimal feature traits from user biometrics. K.R. Radhika is an academician by choice, presumes in dedicated service towards teaching, research and academic activities. She has a rich experience of 24 years in teaching a wide spectrum of subjects in the areas of information technology at the BMSCE. She has about 50 publications to her credit with Google Scholar citations greater than 140. One of the noteworthy publications is in Elsevier journal, Pattern Recognition with an impact factor of 5.898. Other significant publications worth mentioning are in a book chapter, Pattern Recognition, Machine Intelligence and Biometrics – Expanding Frontiers, Springer and Applied Soft Computing, Elsevier with impact factor 4.873.