The rapid development of the Industrial Internet of Things (IIoT) has led to an explosion of industrial data. Due to computing and storage capacity limitations, IIoT devices often outsource the collected data to remote cloud servers. Unfortunately, cloud storage and cloud sharing services are not as reliable as they claim to be. Existing schemes aim to check data integrity in the cloud through cloud auditing. However, they suffer from a number of security and privacy vulnerabilities. The challenge of designing a secure storage auditing framework for industrial IoT comes from two aspects: 1) lack of physical protection of data owner IIoT devices; 2) privacy issues due to auditing of sensitive shared data. Inspired by the aforementioned challenges, we design the secure storage audit framework to support flexible cloud data sharing in IIoT: S2A-P2FS. The first contribution in our work is the Polynomial Prefix Message Authentication Code(P2MAC) design. We design an innovative P2MAC data structure as a label, which can simultaneously achieve efficient data verification in cloud data storage and privacy protection in flexible cloud data sharing for cloud auditing. The second contribution is the design of a unique Physical Unclonable Function(PUF) for IIoT. Harsh industrial conditions hinder the stable operation of PUFs. To protect the trustness of IIoT data owners, we propose a robust PUF-based physical protection mechanism for IIoT devices. The key point is that the required key is not stored in the memory of IIoT but hidden within its physical structure. A security analysis was conducted to demonstrate the robustness of S2A-P2FS against known vulnerabilities. A prototype was implemented in a real-world IIoT scenario. Experimental results indicate that, compared to state-of-the-art schemes, S2A-P2FS achieves over a 3x speedup in computational time and requires only 67.5% of the communication cost.

The deep integration of informatization and industrialization has resulted in an increasingly close connection between supervisory control and data acquisition (SCADA) systems and the Internet. The boundaries of the SCADA system are monitored by industrial smart sensors, which only have limited security protection and face severe security threats. One major threat is that smart sensors are vulnerable to physical attacks because they are often installed in unsafe areas far from plant protection. Under this attack, the data of sensors can be easily tampered with. Moreover, since sensors are resource-constrained physical devices, complex and expensive encryption algorithms are not applicable. In this paper, we design a lightweight industrial smart sensor data stream integrity verification scheme based on physical unclonable function (PUF) for industrial IoT, which can protect the physical security of sensors and the integrity of data streams to ensure the secure transmission of industrial smart sensor data streams. We utilize PUF, fuzzy extractor and bit selection algorithm to generate stable PUF responses. A malicious attacker cannot extract the key information through physical attack. In addition, we design a lightweight integrity verification algorithm with efficient key updating based on lightweight cryptographic primitives, making it suitable for resource-constrained physical devices. We perform the security analysis to demonstrate the security of the scheme to known security vulnerabilities. We implement the proposed scheme and evaluate the performance of our scheme with extensive experiments. The experimental results show the scheme is efficient and superior to existing schemes in computational and communication efficiency.