A Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems

Security and Privacy Aspect of Cyber Physical Systems

Guest Editorial

Cyber-Physical Systems (CPS) are being developed to provide useful interactions between physical systems and environments and cyber world for a variety of applications. CPS are designed with a set of software and interconnected distributed hardware components that are linked with physical elements to provide advanced monitoring and control mechanisms geared towards enhancing the targeted physical system or environment. These components function seamlessly to offer specific functionalities that help enhance human lives, physical system operations and environments. While CPS can offer many smart enhancements for improving physical processes, the development of such complex systems composed of many distributed and heterogeneous components is extremely difficult. This is due to the many communication, computing, and networking challenges. Using an appropriate middleware that provides a framework to support developing and operating diverse CPS applications is a novel method to address these challenges. The availability of advanced middleware services and platforms can provide effective approaches for enhancing CPS application development processes as well as provide more robust environments for operating CPS applications. Such middleware can significantly reduce the time needed to design, build, test, and operate robust CPS applications. However, designing a common middleware platform for diverse types of CPS applications is not trivial. This paper investigates the middleware challenges for CPS, based on the different types of CPS applications being developed and their specific challenges. In addition, the paper discusses the current efforts of developing middleware platforms for CPS and the open research issues in the field.

Blockchain is a distributed, decentralized ledger mechanism with a various features. It is used in diverse applications nowadays, from financial sector to password management. It does not have any central tool to validate and verify the transactions, yet every transaction in the Blockchain is secured and verified. This is achieved because of a consensus algorithm in the network. Latest study reports show that emergence of quantum computing will impact the overall safety of Blockchain and its internal working. Attacks using Grover's and Shor's algorithm can threaten the hashing and public key schemes in cryptography. It will force a complete redesign of the Blockchain systems to withstand quantum attacks. So there is a need to develop quantum-safe Blockchain systems. Consensus mechanisms like Proof of Work (PoW) and Signing algorithms like Elliptic Curve Cryptography used in Blockchain can be modified to overcome quantum attacks. Here a comparative study and analysis of different consensus algorithms developed using post-quantum cryptosystems are done, which can be implemented in Blockchain systems to make them quantum safe.

The development of the legal framework for ensuring information security of cyber-physical systems in recent years is associated with their widespread use and equipment of industries and households. Various kinds of cyber attacks on cyber-physical systems bring benefits to the attackers in the form of data whose distribution is limited, as well as in the form of the failure of such systems. The article provides statistics on the most common attacks on cyber-physical information systems, as well as the consequences faced by a household or organization. The main stage of the research is the analysis of existing norms of legal regulation of the development and operation of cyber-physical systems. This analysis is the foundation for creating criteria on the basis of which a model for the development of legal support of information security in the field of the functioning of cyber-physical systems can be formed. The result of the research is a formed set of legal measures, the implementation of which will reduce both the number of attacks and the consequences of such attacks on cyber-physical systems.

Cyber Physical Systems (CPS) are characterized by their ability to integrate\nthe physical and information or cyber worlds. Their deployment in critical\ninfrastructure have demonstrated a potential to transform the world. However,\nharnessing this potential is limited by their critical nature and the far\nreaching effects of cyber attacks on human, infrastructure and the environment.\nAn attraction for cyber concerns in CPS rises from the process of sending\ninformation from sensors to actuators over the wireless communication medium,\nthereby widening the attack surface. Traditionally, CPS security has been\ninvestigated from the perspective of preventing intruders from gaining access\nto the system using cryptography and other access control techniques. Most\nresearch work have therefore focused on the detection of attacks in CPS.\nHowever, in a world of increasing adversaries, it is becoming more difficult to\ntotally prevent CPS from adversarial attacks, hence the need to focus on making\nCPS resilient. Resilient CPS are designed to withstand disruptions and remain\nfunctional despite the operation of adversaries. One of the dominant\nmethodologies explored for building resilient CPS is dependent on machine\nlearning (ML) algorithms. However, rising from recent research in adversarial\nML, we posit that ML algorithms for securing CPS must themselves be resilient.\nThis paper is therefore aimed at comprehensively surveying the interactions\nbetween resilient CPS using ML and resilient ML when applied in CPS. The paper\nconcludes with a number of research trends and promising future research\ndirections. Furthermore, with this paper, readers can have a thorough\nunderstanding of recent advances on ML-based security and securing ML for CPS\nand countermeasures, as well as research trends in this active research area.\n

The cyber-physical system (CPS) has made tremendous progress in recent years and also disrupting technical fields ranging from health, transportation, industries, and more. However, CPS security is still one of the concerns for wide adoption owing to the high number of devices connecting to the internet and the traditional security solutions may not be suitable to protect the advanced, application-specific attacks. This paper presents a programmable device network layer architecture to combat attacks and efficient network monitoring in heterogeneous environment CPS applications. The authors leverage industrial control systems (ICS) to discuss the existing issues, highlighting the importance of advanced network layers for CPS. The programmable data plane language (P4) is introduced to detect well known HELLO flood attacks with minimal effort in the network level and show that programmable switches are suitable to implement security solutions in CPS applications.

Cyber-physical systems (CPS) security has become an increasingly important research topic in recent years. Geared towards more advanced cyberattack detection techniques as part of strategies for enhancing the security of CPS, in this paper we propose a machine learning based cyber-attack detection scheme. The proposed scheme is a physical-domain technique; specifically, it assumes the physical measurements of the system carry sufficient information for capturing the system behavior, thus can be used for differentiating normal operation and attacks. CPS are complex in nature and the number of physical measurements available for CPS is often overwhelmingly high. Thus, accurately modeling CPS’ dynamic behavior, more importantly, distinguishing normal and adversary activities based on the large number of physical measurements, can be challenging. To address the challenge, we have focused our research effort on feature engineering, that is, to intelligently derive a set of salient signatures or features from the noisy measurements. We make sure the derived features are more compact and, more importantly, have more discriminant power than the original physical measurements, thus enabling us to achieve more accurate and robust detection performance. To demonstrate the effectiveness of the proposed scheme, in our experimental study we consider gas turbines of combined cycle power plants as the cyber-physical system. Using the data from the high-fidelity simulation we show that our proposed cyberattack detection scheme is able to achieve high detection performance.

Smart Grid is the deep interactive fusion of power information system and physical system under the background of modern energy interconnection. Compared with the traditional power grid, its performance has been greatly improved. The essence of smart grid is the application of cyber physical system (CPS) in power industry, which is called power CPS. In view of the cyber security risk caused by the integration of the two systems in power CPS, which may cause the system to suffer complex and severe cascading failures and blackouts, it is of great significance to study the power CPS modeling and security defense based on the integration of the two networks. Different things have different classification methods from different angles. This paper summarizes the main research and analysis methods of power CPS modeling and security defense protection at home and abroad, and puts forward the future development direction, hoping to provide reference for the relevant researchers.

Cyber-Physical System (CPS) networks represent distributed systems characterized by command, communication, and control elements, acting over the environment in order to fulfill complex interactions with it. The CPS applications need to be robust, error prone and to own dynamically self-reconfigurable and self-maintainable capabilities. In this paper we propose a Linear Programming based approach for solving the computational, error prone detection and dynamical reconfigurable aspects which CPS applications needs to achieve. To illustrate the usage and benefits of this approach, we discuss the design of an aircraft fuel management system implemented using a CPS solution.

Due to digitalization and technological advancement, systems and their requirements are changing, and there is an increasing use of Cyber-Physical Systems (CPS) with a direct connection between the physical and the digital world. These systems process data and have integrated functions and a real-time requirement. There is a great need for security, protection of data, and reliability. The use of digital systems in the energy sector is increasing and changing, as are consumers and generators. This requires a secure IT, communications infrastructure, and highly performing data platforms. The new systems being created are called CPS, which are highly scalable, dynamic, and volatile and process many data of various kinds. One significant aspect of a CPS is security. Personal data and business-sensitive data may be processed, or mission-critical processes may be mapped. Risk analysis and security assessments based on conventional methods and guidelines (for example, BSI IT Basic Protection) have revealed drawbacks. Present security assessment methods focus on analyzing corporate information systems or are applied for software development life cycles. CPS criteria and their impact on security have not yet been accounted for in today’s security assessments and their corresponding frameworks. This thesis concentrates on modeling CPS security and deriving a framework for CPS security assessments. The considered criteria are data security as conventional, expanded by scalability, and real-time. The underlying framework is process-oriented. CPS use cases will be broken down into (atomic) processes and the security assessed based on each process’ data security, scalability and real-time model. Eventually, this will mean security measures can be mapped at the process level. Conducting this research, the focus was on smart grid systems as one example of CPS. For the discussion of mapping security measures, authentication was selected. The result analysis shows an added value in the security assessment of CPS based on the criteria of data security, scalability, real-time, and the breakdown at the process level. The underlying model allows to cope with the complexity of CPS and more precisely assess the security of CPS. The overall approach of CPS security modeling and provision by using a process-oriented framework is highly innovative and provides a concept for developing future CPS security assessment tools.

The growing requirement for the rise of production, quality, and efficiency of industrial products drives humans to jointly develop novel technologies capable of following up with the exponential technology growth they are facing today in production processes. In the 21st century, industrial internet of things (IIoT) is dedicated to endorsing the internet of things (IoT) to allow the interconnection of anywhere, any time, and anything to enhance efficiency, productivity, intelligence, and safety in the manufacturing system. Consequently, the combined IoT and cyber physical system (CPS) in IIoT will have an influence on industrial techniques through the industrial 4.0 confluence to encourage connected factories. CPS effectively combines physical and cyber components employing modern components such as sensors, network, and computing technologies. But various securities challenges rising in the CPS, like increasing cyberattacks due to the increase in IoT devices, modelling of security threads, CPS vulnerabilities assessment development techniques, and designing of fault-tolerant architectures, motivate new technologies to meet CPS requirements in order to offer security, confidentiality, and reliability of users’ data. Thus, this chapter presents the classification of various existing studies based on CPS security in terms of IIoT applications. Also, it provides the limitations, shortcomings, CPS architectures, and future potential applications to help researchers in the context of practical work.

Unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) with a blockchain consensus algorithm is a promising solution for addressing mobile offloading of computation-intensive or latency-sensitive tasks with extensive service range, while ensuring the authenticity of the offloading. Existing UAV-aided MEC studies focus on task offloading or trajectory planning of single-antenna UAVs, missing multiple-input multiple-output (MIMO) UAV systems. In addition, most blockchain-based UAV-aided edge computing studies adopt energy-consuming proof-of-work-based consensus mechanisms, which are unsuitable for energy-limited UAV scenarios. To address the above issues, in this paper, we develop a joint deadline-aware task offloading and UAV trajectory planning scheme, utilizing the effects simulated through an energy-efficient consensus protocol. In order to prevent the exhaustion of UAVs' energy and ensure the authenticity of decision-making, we propose an energy-based Raft (E-Raft) consensus algorithm, enabling dynamic leader selection through a series of decreasing energy thresholds. Subsequently, we present a computational profit maximization problem to jointly optimize deadline-aware task offloading and the UAV swarm's trajectory planning. To address this NP-hard problem, we develop an online priority-based task offloading and trajectory selection algorithm, which is performed by the selected leader of the E-Raft consensus in each round. Simulation results demonstrate that our proposed scheme achieves up to 40% performance improvement over other approaches.

The Internet of Things (IoT) is a network of smart objects connected via the Internet, where each object is identified by a unique, accessible, and programmable address, while Blockchain is a technology for storing and transmitting information based on a decentralized system such that the centralized validation of transactions is replaced by a consensus mechanism. The integration of these two technologies requires consensus protocols to overcome the major challenges encountered in IoT systems, including issues related to security, storage capacity limits, computing power, etc. Therefore, different consensus algorithms have been implemented. For this purpose, this paper presents a research study on the criteria that would render a Blockchain consensus algorithm suitable for IoT networks, namely, computing power, latency, storage capacity, and security.

A Through Analysis on Protecting Cyber Threats and Attacks on Cps Embedded Subsystems