Industrial Critical Infrastructures Research Articles

A secure fog‐based platform for SCADA‐based IoT critical infrastructure

SummaryThe rapid proliferation of Internet of things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures and control systems has put stringent performance and scalability requirements on modern Supervisory Control and Data Acquisition (SCADA) systems. While cloud computing has enabled modern SCADA systems to cope with the increasing amount of data generated by sensors, actuators, and control devices, there has been a growing interest recently to deploy edge data centers in fog architectures to secure low‐latency and enhanced security for mission‐critical data. However, fog security and privacy for SCADA‐based IoT critical infrastructures remains an under‐researched area. To address this challenge, this contribution proposes a novel security “toolbox” to reinforce the integrity, security, and privacy of SCADA‐based IoT critical infrastructure at the fog layer. The toolbox incorporates a key feature: a cryptographic‐based access approach to the cloud services using identity‐based cryptography and signature schemes at the fog layer. We present the implementation details of a prototype for our proposed secure fog‐based platform and provide performance evaluation results to demonstrate the appropriateness of the proposed platform in a real‐world scenario. These results can pave the way toward the development of a more secure and trusted SCADA‐based IoT critical infrastructure, which is essential to counter cyber threats against next‐generation critical infrastructure and industrial control systems. The results from the experiments demonstrate a superior performance of the secure fog‐based platform, which is around 2.8 seconds when adding five virtual machines (VMs), 3.2 seconds when adding 10 VMs, and 112 seconds when adding 1000 VMs, compared to the multilevel user access control platform.

Review of cybersecurity issues in industrial critical infrastructure: manufacturing in perspective

ABSTRACTNowadays, the industrial sector is being challenged by several cybersecurity concerns. Direct attacks by malicious persons and (or) software form part of the severe jeopardies of industrial control systems (ICSs). These affect products/production qualities, brand reputations, sales revenues, and aggravate the risks to health and safety of human lives. These have been enabled due to progressive adoption of technology trends like Industry 4.0, BYOD, mobile computing, and Internet-of-Things (IoT), in the quest for improved relevance and value of production decisions, minimised operational overheads, optimum resource utilisation, markets globalisation, etc. However, several security vulnerabilities and risks have also emerged, and are increasingly being exploited in the industrial sector especially manufacturing. To manage this phenomenon, refined and holistic (combining people, process, and technology perspectives) security strategies and solutions are required to enhance security in ICS. This paper offers an insightful review of possible solution path beginning with the understanding of ICS security trends relative to cyber threats, vulnerabilities, attacks and patterns, agents, risks, and the impacts of all these on the industrial environment and entities that depend on it. Such episteme can improve security awareness, proficiency for respective stakeholders, and advance the development of appropriate security mechanisms, and adoption of recommendations.

A method for malware propagation in industrial critical infrastructures

The main goal of this work is to propose a model for the study and analysis of malware propagation in an industrial critical infrastructure. Specifically, an individual-based mathematical model is introduced and its parameters, variables and equations are explicitly defined and constructed. This model follows the agent based modeling paradigm which makes it extremely suitable for use within the small and heterogeneous environments where individual characteristics of all devices can be captured. The main strengths of this model are its ease of computational implementation (both in hardware and software), and its ability to simulate control measures (which can be of great help for security system administrators); however, this model strongly depends on a proper identification of the parameters.

A model of distributed key generation for industrial control systems

The cyber-security of industrial control systems (ICS) is gaining high relevance due to the impact of industrial system failures on the citizen life. There is an urgent need for the consideration of security in their design, and for the analysis of the related vulnerabilities and potential threats. The high exposure of industrial critical infrastructure to cyber-threats is mainly due to the intrinsic weakness of the communication protocols used to control the process network. The peculiarities of the industrial protocols (low computational power, large geographical distribution, near to real-time constraints) make hard the effective use of traditional cryptographic schemes and in particular the implementation of an effective key management infrastructure supporting a cryptographic layer. In this paper, we describe a “model of distributed key generation for industrial control systems” we have recently implemented. The model is based on a known Distributed Key Generator protocol we have adapted to an industrial control system environment and to the related communication protocol (Modbus). To validate in a formal way selected security properties of the model, we introduced a Petri Nets representation. This representation allows for modeling attacks against the protocol and understanding some potential weaknesses of its implementation in the industrial control system environment.