Blockchain-Enabled Decentralized Edge Computing in Cyber Security for Intrusion Detection
Keywords:
Blockchain, Edge Computing, Cybersecurity, Intrusion Detection, DecentralizationAbstract
The foundation of our modern society is an ever-expanding digital ecosystem; nevertheless, this ecosystem is also one that is continuously vulnerable to the threats posed by cyberattacks. The fact that intrusion detection is tasked with identifying and stopping unauthorised access to computer networks and systems has made it abundantly obvious that it is one of the most important aspects of cybersecurity in its entirety. On the other hand, due to the centralised architecture of old intrusion detection systems (IDS), it may be difficult for these systems to respond quickly and effectively to the complex nature of modern cyber threats because of the nature of the design itself. This unique technique makes an attempt to resolve some of the pressing problems that plague traditional intrusion detection systems. These problems include vulnerabilities caused by a single point of failure, data integrity concerns, and scalability concerns. This study presents a brand-new distributed intrusion detection system (IDS) that makes use of fog computing in order to recognise DDoS assaults against mining pools in blockchain-enabled IoT networks. Finding answers to the problems that were discussed before is the reason for doing this research in the first place. Random Forest (RF) and an updated gradient tree boosting approach (XG Boost) are used in order to conduct the performance evaluation of distributed fog nodes. On the basis of the use case of video analytics at the edge, an experimental configuration for an Internet of Things edge solution using the Hyperledger Sawtooth Blockchain has been constructed.
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