ABSTRACT
Chaotic system requires parameters to generate random sequences. Recent studies show that the improper selection of parameter values make secret keys generated from chaotic system vulnerable. Meta-heuristic techniques have been introduced in the area of image encryption to improve the selection of chaotic system parameters. But, these techniques suffer from poor computational speed. To overcome this issue, in this paper, a parallel Non-Dominated Sorting Genetic Algorithm (NSGA-II)-based intertwining logistic map is proposed to encrypt the images. To implement NSGA-II in parallel fashion, master–slave environment is designed. Initially, the execution time analysis of NSGA-II is done to determine the computationally expensive operations. Thereafter, NSGA-II operators are divided into master and slave jobs. The Message Passing Interface (MPI) is used for intercommunication between master and slave nodes. The simulation results show that the parallel proposed technique provides a significant improvement in computational speed as compared to the existing techniques.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Manjit Kaur has done her Master of Engineering in Information Technology from Panjab University, Chandigarh, Punjab, India (2011). Currently she is pursuing her PhD degree in computer science and engineering from Thapar Institute of Engineering and Technology, Patiala, Punjab, India. Her research interest includes wireless sensor networks, digital image processing and meta-heuristic techniques.
Vijay Kumar received B.Tech. from M.M. Engineering College, Mullana. He received M.Tech. from Guru Jambheshwer University of Science and Technology, Hisar. He received Ph.D. degree in Computer Engineering with the National Institute of Technology, Kurukshetra. He has been an Assistant Professor with the Department of Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala. He has more than 9 years of teaching and research experience. He has more than 45 research papers in international journals, book chapters, and conference proceedings. His main research focuses on Soft Computing, Image Processing, Data Clustering and Multiobjective optimization.
ORCID
Manjit Kaur http://orcid.org/0000-0001-6259-2046