Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2022 Association for Computing Machinery. 1551-6857/2022/1-ART1 $15.00 http://dx.doi.org/10.1145/3561513 ACM Trans. Multimedia Comput. Commun. Appl. EiMOL: A Secure Medical Image Encryption Algorithm based on Optimization and the Lorenz System KEDAR NATH SINGH, OM PRAKASH SINGH, and AMIT KUMAR SINGH Department of CSE, NIT Patna, Patna, Bihar (India) AMRIT KUMAR AGRAWAL Galgotias College of Engineering & Technology, Greater Noida, Uttar Pradesh (India) Nowadays, the demand for digital images from different intelligent devices and sensors has dramatically increased in smart healthcare. Due to advanced low-cost and easily available tools and software, manipulation of these images is an easy task. Thus, the security of digital images is a serious challenge for the content owners, healthcare communities and researchers against illegal access and fraudulent usage. In this paper, a secure medical image encryption algorithm, EiMOL, based on optimization and the Lorenz system, is proposed for smart healthcare applications. In the first stage, an optimized random sequence (ORS) is generated through directed weighted complex network particle swarm optimization using the genetic algorithm (GDWCN-PSO). This random number matrix and the Lorenz system are adopted to encrypt plain medical images, obtaining the cipher messages with a relationship to the plain images. According to our obtained results, the proposed EiMOL encryption algorithm is effective and resistant to the many attacks on benchmark Kaggle and Open-i datasets. Further, extensive experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art approaches. CCS Concepts: • Security and privacy → Cryptography; Symmetric cryptography and hash functions KEYWORDS Healthcare system, Medical image, Encryption, Optimization, Security 1 INTRODUCTION With the proliferation of the Internet of Things (IoT), the healthcare industry has experienced significant growth in recent years [1]. There is no doubt that the use of the IoT in healthcare not only improves operational efficiency for medical professionals and hospitals but also provides service convenience for supporting patients and their relatives. Particularly after the Authors ۑaddress: Authors ۑaddress: K. N. Singh, O. P. Singh and A. K. Singh (Corresponding Author) Deptt. of CSE, National Institute of Technology Patna, Patna, Bihar, India, 800005; email: knsinghait@gmail.com, omprakash7667@gmail.com, amit.singh@nitp.ac.in. K. N. Singh also associated with the Department of CSE, Noida Institute of Engineering and Technology, Greater Noida, UP, (India) AK Agrawal, Deptt. of CSE, Galgotias College of Engineering & Technology, Greater Noida, Uttar Pradesh, India, 201310; email: agrawal.amrit4@gmail.com. 2020 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty- free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.