AALMOND: Decentralized Adaptive Access Control of Multi-Party Data Sharing in Industrial Networks

Access control is an important security parameter in industrial networks; a mismanaged access control system leads to security breaches. The existing security solutions significantly consider the access control methods in the Industrial Internet of Things (IIoT); however, falsified identity can bypass the secure access control system. Thus, a centralized access control method leads to risks for data security. We are the first to address the risk factors of granted access in an industrial environment and present a risk-adaptive access control framework for IIoTs. Our proposed solution framework uses blockchain to provide secure decentralized access control in the industrial environment with privacy-preserved multi-party data sharing. We name our framework “Adaptive Access controL for Multi-party data cOmputation in iNdustrial Decentralization (AALMOND)”. AALMOND uses lightweight cryptographic operations to reduce the complexity of the execution and loosen up the tight bounds on resource-constrained industrial devices. Further, the risk-adaptive access control in AALMOND provides a better security analysis of the multi-party sharing data. Our framework uses role-based, attribute-based, and organization-based access controls to map the assets for risk calculation. We put all the required policies in a smart contract for the ease of multi-party data sharing to obtain a transparent access control execution more suitably. We also pioneer in the calculation of the risk adaptivity of AALMOND considering the NIST recommendations of operation risk, security risk, and heuristic risk. We measure the performance of AALMOND with state-of-the-art frameworks based on throughput, latency, complexity analysis, and risk adaptivity factors. We find that AALMOND is efficient for IIoTs as it shows 24% reduced latency and 20% better throughput as compared to the other existing models.