Securing Smart Healthcare Cyber-Physical Systems against Blackhole and Greyhole Attacks Using a Blockchain-Enabled Gini Index Framework
Author:
Javed Mannan1, Tariq Noshina1ORCID, Ashraf Muhammad1ORCID, Khan Farrukh Aslam2ORCID, Asim Muhammad3ORCID, Imran Muhammad4ORCID
Affiliation:
1. Department of Avionics Engineering, Air University, Islamabad 44000, Pakistan 2. Center of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh 11653, Saudi Arabia 3. Department of Cyber Security, National University of Computer and Emerging Sciences, Islamabad 44000, Pakistan 4. Institute of Innovation, Science, and Sustainability, Federation University, Brisbane, QLD 4000, Australia
Abstract
The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity of CPSs. The current detection and mitigation approaches often struggle to accurately differentiate between legitimate and malicious behavior, leading to ineffective protection. This paper introduces Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), a novel technique designed for efficient detection and mitigation of blackhole and greyhole attacks in smart health monitoring CPSs. GBG-RPL leverages the analytical prowess of the Gini index and the security advantages of blockchain technology to protect these systems against sophisticated threats. This research not only focuses on identifying anomalous activities but also proposes a resilient framework that ensures the integrity and reliability of the monitored data. GBG-RPL achieves notable improvements as compared to another state-of-the-art technique referred to as BCPS-RPL, including a 7.18% reduction in packet loss ratio, an 11.97% enhancement in residual energy utilization, and a 19.27% decrease in energy consumption. Its security features are also very effective, boasting a 10.65% improvement in attack-detection rate and an 18.88% faster average attack-detection time. GBG-RPL optimizes network management by exhibiting a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay, thus showing its potential for enhanced reliability, efficiency, and security.
Funder
Deanship for Research and Innovation, Ministry of Education in Saudi Arabia
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference120 articles.
1. A literature review of IoT and CPS—What they are, and what they are not;Lesch;J. Syst. Softw.,2023 2. Amlan, K.N.H., Shamsu, M., Uddin, T.M., and Riyan, N.B. (2023). Intelligent Techniques for Cyber-Physical Systems, CRC Press. 3. Evaluation of key factors for industry 4.0 technologies adoption in small and medium enterprises (SMEs): An emerging economy context;Karuppiah;J. Asia Bus. Stud.,2023 4. A Comprehensive Survey on Cyber-Physical Systems Towards Healthcare 4.0;Gupta;SN Comput. Sci.,2023 5. Kumar, M., Kumar, A., Verma, S., Bhattacharya, P., Ghimire, D., Kim, S.H., and Hosen, A.S. (2023). Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues. Electronics, 12.
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