Biography:

Prathamesh Churi (SMIEEE, MACM, LMCSI, LMISTE, MIGIP) is faculty member in Computer Engineering Department in School of Technology Management and Engineering, NMIMS University. India. He is Senior Member of IEEE. Currently. He is Serving as Associate editor of International Journal of Advances in Intelligent Informatics (Scopus Q4-Artificial Intelligence) and International Journal of Innovative Teaching and Learning in Higher Education and International Journal of Security and Privacy (Scopus, ESCI, ABDC -C). He is also the research mentor in Myracle IO, Germany. He is actively involved in peer review process of reputed IEEE and Springer journals such as IEEE Transactions on Education, Springer Education and Information Technologies and 17 other journals. He has 75 research papers in National/International Conferences and Journals (Scopus, ESCI and SCI Indexed). He has 5 (Including 2 Australian patent) patents in the field of Wireless Sensor Networks, Machine Learning and Internet of Things. He has edited 4 international books (CRC Press Taylor and Francis publications) in the field of Data Privacy and Education Technology. He has been a keynote speaker, chair, convener in the international conferences including the flagship conferences like IEEE TALE 2017-2020, Springer ICACDS etc. He recently received “Best Reviewer Award” by IEEE TALE. Springer JCHE and ETRD for his excellency in Review Process. He has also got appreciation award for best faculty from NMIMS University. He is active leader, coach, mentor, volunteer in many non-profit organizations. He is also involved as board of study member in many universities for curriculum development and educational transformations. 

Speech title:

PixAdapt: A novel approach to adaptive image encryption

Abstract:

Image encryption using genetic approach is a recent and advanced technique which has grabbed attention in recent years. Currently, most image encryption algorithms (using genetic approach) use a static set of parameters for image encryption without considering the features representative of the image. In this study, an innovative adaptive image encryption algorithm – PixAdapt is developed. The process of image encryption is being re-engineered in a way to calculate the fitness of encrypted image using UACI and adapting the respective parameters using genetic hill climb or simulated annealing. Pseudorandom numbers have been generated using the linear feedback shift register and chaos-based maps such as the Logistic map, Rossler map, Henon map and Tent map. PixAdapt algorithm also uses confusion and diffusion process to ensure that plain text image and cipher text image are completely un-related. The use of metaheuristic search techniques for optimization of image encryption parameters has been implemented for the first time. The results obtained show that the genetic hill climb algorithm encrypts the various images giving the most optimal value of UACI. The algorithm has been tested for fitness improvement, parameter evolution, statistical analysis, and quality of encryption. PixAdapt is not only unique but has proven the encryption parameter UACI to be an appropriate fitness function to encrypt an image efficiently.