TY - JOUR
T1 - An AI-Enabled Hybrid Lightweight Authentication Scheme for Intelligent IoMT Based Cyber-Physical Systems
AU - Adil, Muhammad
AU - Khan, Muhammad Khurram
AU - Jadoon, Muhammad Mohsin
AU - Attique, Muhammad
AU - Song, Houbing
AU - Farouk, Ahmed
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - In the era of smart healthcare, Internet of Medical Things-based Cyber-Physical Systems (IoMT-based-CPS) play an important role in acquiring, evaluating, monitoring, tracking, and prescribing patients ubiquitously. For these applications, trustworthy authentication and unassailable communication are the most noteworthy impediments to be considered to attain the trust of patients, healthcare experts, nursing staff, pharmacologists, and other involved commodities. To address these security concerns, in this paper, we present a lightweight hybrid authentication, data privacy and preservation model that is constituted from supervised machine learning (SML) algorithm and a Cryptographic Parameter Based Encryption and Decryption (CPBE&D) algorithm to guarantee the authentication of legitimate IoMT-based-CPS accompanied by encrypted data transmission over the wireless communication channel. To accomplish promising results, we have facilitated a decentralized verification and authentication among legitimate IoMT-based-CPS in the network with an objective to reduce the authentication time, computation cost, and communication overhead with the assistance of the SML algorithm to predicate and forward the authentication parameters of these devices to the next concerned trusted authority when a patient is moving from one hospital (region) to another hospital (region). During the simulation results analysis, SML and CPBE&D authentication scheme demonstrated impressive security features in terms of cost-effective authentication throughout the legitimate patient wearable IoMT-based-CPS validation process, accompanied by profitable communication metrics in the comparison of predecessor works.
AB - In the era of smart healthcare, Internet of Medical Things-based Cyber-Physical Systems (IoMT-based-CPS) play an important role in acquiring, evaluating, monitoring, tracking, and prescribing patients ubiquitously. For these applications, trustworthy authentication and unassailable communication are the most noteworthy impediments to be considered to attain the trust of patients, healthcare experts, nursing staff, pharmacologists, and other involved commodities. To address these security concerns, in this paper, we present a lightweight hybrid authentication, data privacy and preservation model that is constituted from supervised machine learning (SML) algorithm and a Cryptographic Parameter Based Encryption and Decryption (CPBE&D) algorithm to guarantee the authentication of legitimate IoMT-based-CPS accompanied by encrypted data transmission over the wireless communication channel. To accomplish promising results, we have facilitated a decentralized verification and authentication among legitimate IoMT-based-CPS in the network with an objective to reduce the authentication time, computation cost, and communication overhead with the assistance of the SML algorithm to predicate and forward the authentication parameters of these devices to the next concerned trusted authority when a patient is moving from one hospital (region) to another hospital (region). During the simulation results analysis, SML and CPBE&D authentication scheme demonstrated impressive security features in terms of cost-effective authentication throughout the legitimate patient wearable IoMT-based-CPS validation process, accompanied by profitable communication metrics in the comparison of predecessor works.
KW - AI-enabled cryptography
KW - CPBE & D validation model
KW - Cyber-physical systems
KW - Data privacy and preservation
KW - Digital and smart healthcare
KW - IoMT-based-CPS authentication
UR - http://www.scopus.com/inward/record.url?scp=85126706384&partnerID=8YFLogxK
U2 - 10.1109/TNSE.2022.3159526
DO - 10.1109/TNSE.2022.3159526
M3 - Article
AN - SCOPUS:85126706384
SN - 2327-4697
VL - 10
SP - 2719
EP - 2730
JO - IEEE Transactions on Network Science and Engineering
JF - IEEE Transactions on Network Science and Engineering
IS - 5
ER -