Blockchain based AI-enabled Industry 4.0 CPS Protection against Advanced Persistent Threat
Ziaur Rahman, Xun Yi Ibrahim Khalil

TL;DR
This paper proposes a blockchain and AI-enabled system for detecting advanced persistent threats in Industry 4.0 environments, enhancing security, trust, and efficiency in edge computing and data management.
Contribution
It introduces a novel integrated approach combining blockchain and AI for efficient APT detection, trust enhancement, and edge storage in Industry 4.0 settings.
Findings
Outperforms existing systems in APT detection accuracy
Ensures secure, transparent data transfer without certificates
Facilitates predictive maintenance with edge storage
Abstract
Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today's industry ecosystem. Breaching data or forging source devices after injecting advanced persistent threats (APT) damages the industry owners' money and loss of operators' lives. The existing challenges include APT injection attacks targeting vulnerable edge devices, insecure data transportation, trust inconsistencies among stakeholders, incompliant data storing mechanisms, etc. Edge-servers often suffer because of their lightweight computation capacity to stamp out unauthorized data or instructions, which in essence, makes them exposed to attackers. When attackers target edge servers while transporting data using traditional PKI-rendered trusts, consortium blockchain (CBC) offers proven techniques to transfer and maintain…
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