With the rapid development of the Industrial Internet of Things (IIoT), programmable logic controllers (PLCs) are becoming increasingly intelligent, leading to improved productivity. However, this also brings about a growing number of security vulnerabilities. As a result, efficiently identifying potential security vulnerabilities in PLCs has become a crucial research topic for security researchers. This article proposes a method for fuzzing industrial proprietary protocols to effectively identify security vulnerabilities in PLCs’ proprietary protocols. The aim of this study is to develop a protocol fuzzing approach that can uncover security vulnerabilities in PLCs’ proprietary protocols. To achieve this, the article presents a protocol structure parsing algorithm specifically designed for PLC proprietary protocols, utilizing information theory. Additionally, a fuzzing case generation algorithm based on genetic algorithms is introduced to select test cases that adhere to the format specifications of the proprietary protocol while exhibiting a high degree of mutation. The research methodology consists of several steps. Firstly, the proposed protocol structure parsing algorithm is used to analyze two known industrial protocols, namely Modbus TCP and S7Comm. The parsing results obtained from the algorithm are then compared with the correct results to validate its effectiveness. Next, the protocol structure parsing algorithm is applied to analyze the proprietary protocol formats of two PLC models. Finally, based on the analysis results, the PLCs are subjected to fuzzing. Overall, the proposed protocol fuzzing approach, incorporating the protocol structure parsing algorithm and the fuzzing case generation algorithm, successfully identifies two denial-of-service vulnerabilities in the PLCs’ proprietary protocols. Notably, one of these vulnerabilities is a zero-day vulnerability, indicating that it was previously unknown and undisclosed.

The Fourth Industrial Revolution, also known as Industrial 4.0, has greatly accelerated inter-connectivity and smart automation in industrial control systems (ICSs), which has introduced new challenges to their security. With the fast growth of the Internet of Things and the advent of 5G/6G, the collaboration of Artificial Intelligence (Al) and the Internet of Things (loT) in ICSs has also introduced lots of security issues as it highly relies on advanced communication and networking techniques. Frequent ICS security incidents have demonstrated that attackers have the ability to stealthily breach the current system defenses and cause catastrophic effects to ICSs. Thankfully, trusted computing technology, which has been a popular research topic in the field of information security in recent years, offers distinct advantages when applied to ICSs. In this paper, we first analyze the vulnerabilities of ICSs and the limitations of existing protection technologies. Then, we introduce the concept of trusted computing and present a security framework for ICSs based on Trusted Computing 3.0. Finally, we discuss potential future research directions.

In recent years, with the upgrading of the attack technology, stealthy DoS jamming attacks have become the primary factor to threaten the security of Industrial Cyber-Physical Systems (ICPS). Considering the complex industrial scenarios of ICPS, which are influenced by a variety of external and internal interference, a $H_{\infty }$ controller designing problem is studied in this paper for an ICPS which deploys a hybrid-triggered mechanism (HTM) in the wireless channel encountering stealthy DoS jamming attacks. By employing a compensation mechanism which is employed in the controller to mitigate the impacts of attacks, external disturbance, limited channel capacity, wireless channel noise, we establish a closed-loop system and prove the closed-loop system is mean square exponentially stable and can achieve the desired $H_{\infty }$ disturbance rejection level theoretically. Finally, simulation examples are used to demonstrate effectiveness of the proposed $H_{\infty }$ controller.

The control instructions of industrial control systems are prone to threats such as unauthorized access and tampering during transmission and interaction, and access control is a fundamental method to protect data security. Due to the cyber-physical integration and availability constraints in industrial control systems, existing access control methods cannot be directly applied. In this paper, we propose an access control policy for control instructions based on the ciphertext policy attribute-based encryption (CP-ABE) under the availability constraints in industrial control systems. First, we analyze the abnormal behaviors of control instructions in process industrial monitoring systems, and model the attributes associated with field control business and integrate them into CP-ABE to achieve fine-grained access control and avoid non-compliant operations. Second, we adopt a trusted computing mechanism to protect the identity trustworthiness of the transmission node; the confidentiality of the transmitted control instruction is guaranteed by the negotiated symmetric key and the key authorization is realized by the CP-ABE. We further optimize the measuring frequency of the trusted measurement and the deployment policy of the access control method to guarantee business availability. Finally, we conduct formal analysis and experimental validation of the proposed method, and the results show that the proposed access control policy can prevent unauthorized access and non-compliant tampering by industrial control devices and achieve trustworthy delivery of control instructions with controlled computational complexity.