Securing Smart Healthcare Cyber-Physical Systems against Blackhole and Greyhole Attacks Using a Blockchain-Enabled...

Area of Science:

• Cyber-Physical Systems Security
• Network Intrusion Detection
• Blockchain Applications

Background:

• Cyber-physical systems (CPSs) are increasingly vital in critical sectors like healthcare, demanding robust security against threats.
• Blackhole and greyhole attacks threaten CPS availability and integrity, with current methods often failing to distinguish malicious from legitimate behavior.

Purpose of the Study:

• To introduce a novel technique, Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), for efficient blackhole and greyhole attack detection and mitigation in smart health monitoring CPSs.
• To enhance the security, integrity, and reliability of monitored data within CPSs.

Main Methods:

• Leveraging the Gini index for anomaly detection.
• Utilizing blockchain technology for enhanced security and a resilient framework.
• Implementing the GBG-RPL technique in smart health monitoring CPSs.

Main Results:

• GBG-RPL achieved a 7.18% reduction in packet loss ratio and improved residual energy utilization by 11.97%.
• Demonstrated a 10.65% improvement in attack detection rate and an 18.88% faster average detection time.
• Optimized network management with a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay.

Conclusions:

• GBG-RPL offers significant improvements in reliability, efficiency, and security for smart health monitoring CPSs.
• The integration of Gini index and blockchain provides a robust defense against sophisticated cyber threats.
• The proposed method outperforms existing techniques like BCPS-RPL in key performance metrics.