  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 those
sensitive data securely. With the recent improvement of edge machine learning,
edge devices can filter malicious data at their end which largely motivates us
to institute a Blockchain and AI aligned APT detection system. The unique
contributions of the paper include efficient APT detection at the edge and
transparent recording of the detection history in an immutable blockchain
ledger. In line with that, the certificateless data transfer mechanism boost
trust among collaborators and ensure an economical and sustainable mechanism
after eliminating existing certificate authority. Finally, the edge-compliant
storage technique facilitates efficient predictive maintenance. The respective
experimental outcomes reveal that the proposed technique outperforms the other
competing systems and models.
