Distribution grids are becoming more decentralized with the increasing penetration of renewable energy resources such as storages, electrical vehicles and renewable energy resources. IEC 61850 is the dominant standard for engineering substation automation systems and the scope is traditionally within the Local Area Network. The scope has since extended to include wide area networks and cybersecurity is now a system requirement that is becoming a must-have. We propose EASy-RM, a requirement management framework for Energy Automation Systems that can trace cybersecurity requirements from requirements (IEC 62443) to specifications (IEC 61850) and to the automation control (IEC 61499). The underlying framework is based on graph theory for formally linking requirements and system artefacts, and graph algorithms over these links are used for requirement management activities. Our results are demonstrated on a CIGRE case study where we demonstrate the tracing of IEC 62443 authentication requirements to IEC 61850 specifications and IEC 61499 implementation.

The paradigm of Logical Execution Time (LET) tasks is widely adopted by major tool vendors for designing deterministic and time-predictable software in multi-core systems, particularly in the automotive industry. To extend the use of LET in distributed environments, System Level Logical Execution Time (SL-LET) has been developed to effectively manage communication and delays between networked devices. However, there is currently a lack of open-source tools available for SL-LET, and the task allocation and scheduling problem for SL-LET remains unsolved.

Industrial Cyber-Physical Systems (ICPS) are heterogeneous computer systems interacting with physical processes in an industrial environment. The presence of numerous interconnected components poses significant security threats to ICPS. Slow-Rate Attacks (SRA), in which attackers attack a system constantly at low volumes, are difficult to detect for resource-constrained ICPS computers like programmable logic controllers (PLC). We propose an optimised light-weight active security framework for SRA detection based on Online Sequential Extreme Learning Machine (OSELM). We optimise the memory and space footprint of OSELM for deployment in resource-constrained ICPS. Additionally, a simple stratified k-fold cross training method improves the performance and accuracy of binary and multi-class SRA detection. Compared to existing methods, our technique requires less space and reduces attack detection time by at least 95%.

Abstract Agile software development (ASD) emphasizes iterative development, continuous feedback, and team collaboration, addressing the limitations of traditional methodologies. This research explores the application of machine learning (ML) to improve story point estimation in ASD, a critical practice for planning and prioritization. Traditional methods like Planning Poker often suffer from human biases and inconsistencies, leading to unreliable estimates. This study introduces an innovative ML-based ensemble stacking technique, combining RoBERTa, a transformer model for natural language processing, with BiLSTM, a neural network adept at handling sequential data. The research involves reviewing existing ML methodologies, developing the proposed model, and evaluating its effectiveness using 21,064 data points from 14 open-source projects. The model’s performance was assessed through Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Results show that the proposed ensemble model achieved lower MAE and MAPE, with performance improvements ranging from 4% to 32% over state-of-the-art models. While promising, the study suggests there is still room for further refinement, indicating the potential for ongoing advancements. This research contributes to the integration of ML in software engineering, offering a path toward more accurate and efficient project management.

This paper examines the use of supervised machine learning to construct a digital twin model replicating a physical plant. An inverted pendulum simulation has been used as a case study.A comparative study was conducted on single-step and multistep Dense models, Convolutional Neural Network (CNN), Recurrent Neural Net (RNN), and a Residual Neural Net (RNN2) models to investigate the most appropriate model for replicating the plant model.The study found that single-step models were consistently more accurate than multi-step models due to single-step model’s iterative nature. Whereas, multi-step models were better at revealing prediction patterns and identifying causes for large deviations. The best-performing model was the RNN2 model, however, signs of overfitting were observed. In general, all models were able to take into account minor random actuation, however, large changes such as the pendulum falling over caused the models to behave sporadically.

In smaller components of industrial or energy automation systems, such as device controllers of Protection and Control (PAC) systems in smart grids, controller functionality is tightly coupled with the physical device or sensor capabilities. At this level, software is small and therefore easy to maintain and test. However, when multiple controllers are interconnected and higher-level functionality is added, software applications grow exponentially, and ensuring maintainability becomes proportionally challenging. In this paper, we extend the IEC 61499 reference architecture used to develop industrial automation software with the principles of Abstraction Layered Architecture (ALA) that has shown up to 400% improvements in industrial software maintainability. We show that even a light application of abstraction layering on the top, application-level of IEC 61499 applications makes them significantly more readable and slightly more maintainable. More concrete gains in maintainability are expected when abstraction layering is integrated into lower layers.

The significant growth in modern communication technologies has led to an increase in zero-day vulnerabilities that degrade the performance ofindustrialcyber-physical systems (ICPS). Distributed denial of service (DDoS) attacks are one such threat that overwhelms a target with floods of packets, posing a severe risk to the normal operations of the ICPS. Current solutions to detect DDoS attacks are unsuitable for resource-constrained ICPS. This study proposes actively detecting multiscale flooding DDoS attacks in resource-constrained ICPS by analyzing network traffic in the frequency domain. A two-phased technique detects attack presence and attack volume. Both phases use a novel combination of light-weight and theoretically sound statistical methods. The effectiveness of the proposed technique is evaluated using mainstream metrics like true and false positive rates, accuracy, and precision using BOUN DDoS 2020 and CICDDoS 2019 datasets. An implementation of the proposed approach on a programmable logic controllers-based ICPS demonstrated improvements in resource usage and detection time compared to the existing state-of-the-art.

Abstract We must explicitly capture relationships and hierarchies between the multitude of system and security standards requirements. Current security requirements specification methods do not capture such structure effectively, making requirements management and traceability harder, consequently increasing costs and time to market for developing certified ICS. We propose a novel requirements repository model for ICS that uses labelled property graphs to structure and store system-specific and standards-based requirements using well-defined relationship types. Furthermore, we integrate the proposed requirements repository with design-time ICS tools to establish requirements traceability. A wind turbine case study illustrates the overall workflow in our framework. We demonstrate that a robust requirements traceability matrix is a natural consequence of using labelled property graphs. We also introduce a compatible requirements change management procedure that aids in adapting to changes in development and certification schemes.

Denial of Service is a significant availability threat in Industrial Cyber-Physical systems and smart manufacturing is not an exception. The types, methods, and duration of these attacks have been evolving rapidly and their number has increased dramatically, reaching a new record in history. In particular, digitisation of the manufacturing process and increased connectivity have created a battleground between product quality of service and threats associated with cross-domains and multi-vector attacks that affect the manufacturing system performance. The existing research on cyber-threats related to smart manufacturing system does not consider the comprehensive landscape of denial of service attacks. In this study, we classify well-accepted (distributed) denial of service attacks according to a proposed taxonomy, focusing on both the multi-vector attacks and cross-domain attacks. Utilising the taxonomy, more than fifty different denial of service attacks on smart manufacturing system were classified in terms of Endpoint and Network (distributed) denial of service attacks. As an example, a Cyber-Physical Conveyor System was used to examine the proposed taxonomy.

Internet-of-Things (IoT) devices and their sensors are capable of monitoring diverse environments and generate a massive amount of data to be communicated to a sink node (base station) for further analysis. In many cases they are located outdoors in harsh conditions and are powered by battery. It is highly desired to avoid accessing them for battery replacement and for many a battery lifespan of about 10 years or more is considered a prominent advantage. The main contributor for power consumption of IoT constrained devices with limited processing and memory performance is the communication module, and in Low-Power Wide-Area Network (LPWAN) it is the transmit operation.The aim of this paper will be to minimize power consumption of edge devices by reducing the transmitted bits. This paper will first review existing studies and evaluate the most appropriate compression algorithms for LPWAN constrained edge devices. Our results show that by adjusting the latency and the algorithms thresholds a great deal of energy could be saved, up to 70%-99% depending on applications and data types. We then propose a novel context-aware adaptive data compression algorithm which takes into account the operating environment and sensor data types which balances system response and power consumption.

In Industrial Cyber-Physical Systems (ICPS), containerisation promises high scalability, reconfigurability and dependability. Denial of Service (DoD/DDoS) is a significant security threat in containerised ICPS applications, which execute on resource-constrained computers like PLCs, and cannot support traditional security mechanisms like firewalls that sacrifice performance and throughput. We propose a novel, light-weight active security approach to detecting DoS/DDoS attacks through frequency analysis of network traffic (packets). Our approach identifies attacks by recording a frequency signature of the flow of packets in an ICPS under normal operation. Subsequently, an attack is modelled as any anomalies in the network that modify the frequency profile of network traffic in the ICPS. Our prototype implementation and evaluation show that this active security method is light-weight and suitable for resource-constrained ICPS platforms.

Increasing automation and external connectivity in industrial control systems (ICS) demand a greater emphasis on software-level communication security. In this article, we propose a secure-by-design development method for building ICS applications, where requirements from security standards like ISA/IEC 62443 are fulfilled by design-time abstractions calledsecure links. Proposed as an extension to the IEC 61499 development standard, secure links incorporate both light-weight and traditional security mechanisms into applications with negligible effort. Applications containing secure links can be automatically compiled into fully IEC 61499-compliant software. Experimental results show secure links significantly reduce design and code complexity and improve application maintainability and requirements traceability.

Cyber-physical systems (CPSs) are implemented in many industrial and embedded control applications. Where these systems are safety-critical, correct and safe behavior is of paramount importance. Malicious attacks on such CPSs can have far-reaching repercussions. For instance, if elements of a power grid behave erratically, physical damage and loss of life could occur. Currently, there is a trend toward increased complexity and connectivity of CPS. However, as this occurs, the potential attack vectors for these systems grow in number, increasing the risk that a given controller might become compromised. In this article, we examine how the dangers of compromised controllers can be mitigated. We propose a novel application of runtime enforcement that can secure the safety of real-world physical systems. Here, we synthesize enforcers to a new hardware architecture within programmable logic controller I/O modules to act as an effective line of defence between the cyber and the physical domains. Our enforcers prevent the physical damage that a compromised control system might be able to perform. To demonstrate the efficacy of our approach, we present several benchmarks, and show that the overhead for each system is extremely minimal.

In recent years we have seen numerous proof-of-concept attacks on implantable medical devices such as pacemakers. Attackers aim to breach the strict operational constraints that these devices operate within, with the end-goal of compromising patient safety and health. Most efforts to prevent these kinds of attacks are informal, and focus on application- and system-level security --- for instance, using encrypted communications and digital certificates for program verification. However, these approaches will struggle to prevent all classes of attacks. Runtime verification has been proposed as a formal methodology for monitoring the status of implantable medical devices. Here, if an attack is detected a warning is generated. This leaves open the risk that the attack can succeed before intervention can occur. In this paper, we propose a runtime-enforcement based approach for ensuring patient security. Custom hardware is constructed for individual patients to ensure a safe minimum quality of service at all times. To ensure correctness we formally verify the hardware using a model-checker. We present our approach through a pacemaker case study and demonstrate that it incurs minimal overhead in terms of execution time and power consumption.

IEC61499 is an emerging standard for the design of automation systems. While many compilers and associated tools for IEC61499 have been developed, systematic techniques for modelling the continuous dynamics of the physical processes are lacking. Current practices involve using co-simulation, where plants are modelled in a tool such as Simulink and controllers are designed using IEC-61499. Co-simulation has many limitations such as slow sampling and free-wheeling. In this paper we propose a systematic approach for the design and simulation of Cyber-Physical Systems (CPS) using IEC61499. We propose the concept of Hybrid Function Blocks (HFBs), as syntactic extensions, to specify the continuous dynamics of a physical plant. A Hybrid Function Block can be compiled into a standards compliant Basic Function Block, based on new deterministic synchronous semantics. To show that our approach is both scalable and efficient when designing CPS, we present benchmarks showing that it runs 29 % faster than Simulink when generating correlating traces.

Mixed-Criticality Systems are capable of accommodating tasks of varying criticality. In this paper, these are [life, mission, and non-critical]. Tasks usually have an overestimated execution time to allow for the Worst Case Execution Time (WCET). When these tasks finish execution prior to their allotted execution time due to pessimistic assumptions present in the static analysis of the system. The surplus time is used to accommodate tasks with tolerance for deadline-misses. Non-critical tasks are often treated in a ”best-effort” capacity where no quality of service is considered. When processor utilisation is not overconstrained, all deadlines will be met. However, in cases where not enough processing resources exist to meet all deadlines for non-critical tasks, the allotted time for the non-critical tasks must be rationed between non-critical tasks. This paper proposes a novel method of prioritising non-critical tasks. By treating task execution as a service, non-critical tasks with unbounded deadline miss tolerance are given a Grade of Service for their met deadlines. This Grade of Service is used for the dynamic scheduling of non-critical tasks. Four different scheduling algorithms were tested with the proposed Highest Penalty First algorithm for distributing the effort of task execution amongst non-critical tasks in a proportionate manner and showing superior fairness of task execution compared to all other tested algorithms.

Many complex industrial control systems need to meet stringent timing requirements. Ensuring that implementations can meet these requirements can be a very difficult task. IEC 61499 is an emerging standard for modelling and implementing large distributed industrial control systems. However, there is currently no established approach for executing IEC 61499 code in a distributed time-predictable manner. In this paper, we present a novel time-predictable runtime called RunSync for executing IEC 61499 on the Precision Timed (PRET) architecture FlexPRET. PRET architectures are designed to guarantee timing repeatability while preserving performance. They are often designed as RISC architectures which utilize multiple hardware threads to remove pipeline hazards. Determining the allocation of tasks to the hardware threads is a key problem when utilizing such architectures. Hence, in this paper it is demonstrated that through RunSync it is possible to dynamically map IEC 61499 tasks to hardware threads during runtime, while preserving determinism and remaining amenable to timing analysis. Following that, quantitative results are presented, showing the minimal overheads of RunSync compared to implementations of the existing synchronous approach. RunSync is thus demonstrated to be more performant with large IEC 61499 networks, and when there are more hardware resources to be allocated.

IEC 61499 enables component-oriented descriptions of complex industrial processes facilitating model-driven engineering. One aspect that is lacking, however, is the ability to directly express Statecharts-like hierarchy and concurrency within basic function blocks (BFBs). Such features can significantly enhance function blocks and help create more succinct and readable specifications. We propose a new syntactic extension to the standard called hierarchical and concurrent execution control chart (HCECC). A major roadblock for any suggested changes to the standard is the need for compliance. Our approach extends the synchronous execution semantics of IEC 61499, where HCECCs are purely syntactic sugar. Using a revised synchronous semantics, our compiler generates standard compliant C code from HCECCs. Benchmarking and usability studies reveal the relative superiority of the proposed approach over existing approaches.

Synchronous languages are widely used to design safety-critical embedded systems. These languages are based on the synchrony hypothesis, asserting that all tasks must complete instantaneously at each logical time step. This assertion is, however, unsuitable for the design of mixed-criticality systems, where some tasks can tolerate missed deadlines. This paper proposes a novel extension to the synchronous approach for supporting three levels of task criticality: life, mission, and non-critical. We achieve this by relaxing the synchrony hypothesis to allow tasks that can tolerate bounded or unbounded deadline misses. We address the issue of task communication between multi-rate, mixed-criticality tasks, and propose a deterministic lossless communication model. To maximize system utilization, we present a hybrid static and dynamic scheduling approach that executes schedulable tasks during slack time. Extensive benchmarking shows that our approach can schedule up to 15% more task sets and achieve an average of 5.38% better system utilization than the Early-Release EDF (ER-EDF) approach. Tasks are scheduled fairer under our approach and achieve consistently higher execution frequencies, but require more preemptions.

Static computation of the worst-case reaction time (WCRT) is required for the real-time execution of synchronous programs. Existing approaches use model checking or integer linear programming. we formulate this as an abstraction-based reachability analysis yielding a lower worst case complexity. Benchmarking shows a significant overall speed-up of 64-times over existing approaches.