Integration of blockchain and collaborative intrusion detection for secure data transactions in industrial IoT: a survey
Source of Publication
The advent of the Industrial Internet of Things (IIoT) integrates all manners of computing technologies, from tiny actuators to process-intensive servers. The distributed network of IoT devices relies on centralized architecture to compensate for their lack of resources. Within this complex network, it is crucial to ensure the security and privacy of data in the IIoT systems as they involve real-time functions that manage people’s movement and industrial materials like chemicals, radio-active goods, and large equipment. Intrusion Detection Systems (IDS) have been widely used to detect and thwart cyber-attacks on such systems. However, these are inefficient for the multi-layered IIoT networks which include heterogeneous protocol standards and topologies. With the need for a novel security method, the integration of collaborative IDS (CIDS) and blockchain has become a disruptive technology to ensure secure and trustable network transactions. Which detection methodology is suitable for this integration, and IIoT? Will blockchain render IIoT completely immune to cyber-attacks? In this paper, we provide a comprehensive review of the state of the art, analyze, and classify the integration approaches of CIDS and blockchain, and discuss suitable approaches for securing IIoT systems. We also categorize the major blockchain vulnerabilities with their potential losses to expose significant gaps for future research directions.
Springer Science and Business Media LLC
Medicine and Health Sciences
Anomaly-based IDS, Blockchain, Collaborative intrusion detection systems, Industrial internet of things, Industry 4.0, Signature-based IDS, Specification-based IDS, Trust management
Mathew, Sujith Samuel; Hayawi, Kadhim; Dawit, Nahom Aron; Taleb, Ikbal; and Trabelsi, Zouheir, "Integration of blockchain and collaborative intrusion detection for secure data transactions in industrial IoT: a survey" (2022). All Works. 5207.
Indexed in Scopus