A comprehensive study on DNA based Security scheme Using Deep Learning in Healthcare

Abstract

The internet is widening day by day followed by security issues related to it. There are many approaches to achieve a secure cyber environment but still, there always exists room for the optimal choice to attain security goals. Artificial intelligence (AI) has given a new vision to the technology by implementing its remarkable applications for common users by providing ease in human life with its unique inventions. Deep learning (DL) has emerged from machine learning that relates to the branch of AI itself. In DL, the machine adopts the behavior of the human mind through its various hidden layers to generate the output similarly as the human mind should do. Research is on DNA-based security using DL that works similarly to cryptography and ensures secure data transfer among cyber users. This combination is studied by recent researchers and found its successfulness in enhancing the security of data. Moreover, the DNA scheme has empowered security systems by safeguarding against major cyberattacks. Although, it is being used in multiple real-world domains, we concise our research on the health sector where it is used to handle various forms of patient’s health data records. The study found that the combination of DNA sequence along with DL techniques enhances data confidentiality to be shared with concerned legitimate users and hence ensuring data confidentiality, integrity, authorization, and authentication and this is what we require in the medical field too. So, DNA security mechanisms undoubtedly strengthen the security of data by implementing DL methods and techniques in the health section.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sehrish Aqeel

Sehrish Aqeel has done Msc in  Information Technology (Information System) and Mphil in Computer Science(Software Engineering) with distinction from PUCIT, University of Punjab  and Virtual University of Pakistan respectively. She has worked as Sr. Lecturer in Department of Computer Science, King Khalid University KSA from 2009 to 2019. She is currently persuing her PhD from University of Malaysia, Sarawak (UNIMAS) with Faculty of Computer Science  and Information Technology. Her research interests are in Computer Network, Cyber Security, Information System, Data Science, Internet of Things, Big Data, Deep Learning and Software Engineering.

Adnan Shahid Khan

Adnan Shahid Khan (Senior Member, IEEE) received the B.Sc. degree (Hons.) in computer science from the University of the Punjab, Lahore, Pakistan, in 2005, and the master’s, Ph.D., and Postdoctoral degrees in networks and information security from Universiti Teknologi Malaysia, Johor Bahru, Malaysia, in 2008, 2012, and 2013, respectively. He is currently a Senior Lecturer with the Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak. His research interests include wireless communication, cloud computing, the Internet of Things, software-defined networking, cryptography, networks, and information security.

Zeeshan Ahmad

Zeeshan Ahmad (Member, IEEE) received the B.S. degree in Computer Engineering from COMSATS University Islamabad (previously COMSATS Institute of Information Technology), Pakistan, in 2005, the M.S. degree in Computer Science (Networks) from the Virtual University of Pakistan, in 2019, and the M.S. degree in Electrical Engineering (Telecommunication) from Kalmar University College, Sweden, in 2008. He is currently pursuing a Ph.D. degree with Universiti Malaysia Sarawak (UNIMAS), Sarawak, Malaysia. He worked with the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Barcelona, Spain, for his M.S. degree thesis for six months, from 2007 to 2008. He has also worked as a Research Assistant with the Institute of Theoretical Information Technology, RWTH Aachen University, Germany, from 2008 to 2010. He is currently affiliated with the Department of Electrical Engineering, King Khalid University, Abha, Saudi Arabia, as a Lecturer. His research interests include Big Data, Cloud Computing, Machine learning, and Deep learning methods for network and information security in the Internet-of-Things networks.

Johari Abdullah

Johari Abdullah received the Bachelor’s degree in Computer Science (Networking) from Universiti Putra Malaysia, the Master’s degree in IT from the Queensland University of Technology, Brisbane, Australia, and the Ph.D. degree in Computing Science from Newcastle University, U.K. He is currently serving as an Associate Professor with the Faculty of Computer Science and IT, UNIMAS, Sarawak. His research interests include ICT is wide and ranging from trusted systems, blockchain technology, web system design and development, system architecture, problem-solving using tools, such as TRIZ, ICT education for children and youth through computational thinking, scratch, computer science unplugged, and open-source system and software.