Aspect-Oriented MDA Approach for Non-functional Properties of Distributed Cyber Physical Systems

Cyber physical systems are envisioned to integrate computation, control and communication with the physical environment. Therefore, CPS requires strong interactions between the cyber and physical worlds in time. The design of cyber physical systems (CPS) poses many challenges because of their complexity, high safety requirements, distribution, and real time nature. We propose a novel paradigm, based on the idea of using simplicity of the aspect-oriented MDA design method to control complexity, to achieve highly correct CPS designs. The model-based development, aspect-oriented approach and formal methods are integrated effectively for the development of the non-functional properties of distributed cyber physical systems. A case study illustrates the aspect oriented MDA development of cyber physical systems.

Engineering cyber-physical systems (CPS) is complex and time-consuming due to the heterogeneity of the involved engineering domains and the high number of physical and logical interactions of their subsystems. Model-based systems engineering (MBSE) approaches tackle the complexity of developing CPS by formally and explicitly modeling subsystems and their interactions. Newer approaches also integrate domain-specific models and modeling languages to cover different aspects of CPS. However, MBSE approaches are currently not fully applicable for CPS development since they do not integrate formal models for physical and mechanical behavior to an extent that allows to seamlessly link mechanical models to the digital models and reuse them. In this paper, we discuss the challenges arising from the missing integration of physics into MBSE and introduce a model-based methodology capable of integrating physical functions and effects into an MBSE approach on a level where detailed physical effects are considered. Our approach offers a fully virtual, model-based development methodology covering the whole development process for the development of CPS. Evaluating this methodology on a real automotive use case demonstrates benefits regarding virtual development and functional testing of CPS. It shows potentials regarding automated development and continuous integration of the whole CPS including all domains. As an outlook of this paper, we discuss potential further research topics extending our development workflow.

Security threats and measures for the cyber-physical systems

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.

Abstract. Motivated by the application of industry 4.0 and Internet of Things (IoT) technologies, the development of cyber physical systems (CPS) is gaining momentum. As CPS require multiple measurement technologies to drive the intended function, e.g., condition monitoring and in situ measurement, the integration of measurement systems into industrial processes or individual products becomes a critical activity within the development process. Development methods like the V-Model support developers with methodological guidelines, but the related methods and models do not provide sufficient information regarding the energy supply of embedded systems. If the measurement system, consisting of sensor, calculation and communication unit is integrated inside an either sealed or moveable system, e.g., in a gearbox, ensuring a reliable communication and energy supply is a challenging task. This contribution therefore focuses on the energy supply, in particular the electric power consumption of autarchic measurement systems, referred to as sensor nodes. Based on a literature review of existing physical principles determining the energy consumption of semiconductors, a simple estimation model is derived. Estimation models in the current literature mainly focus on the effects of source code or software in general without analyzing a possible impact of operation strategies, such as generic data processing logics in practical applications. The model presented in this contribution is therefore used to identify the energy consumption of sensor nodes influenced by ambient and operating conditions of sensor nodes. Strategies are examined experimentally using an exemplary sensor node, a climatic chamber and a sensor-integrated gearbox as the system to be observed. An analysis of the conducted experiments leads to a more precise model, which is evaluated regarding its significance for predicting the energy consumption and the underlying simplifications. Finally, general relations influencing the energy consumption are presented and necessary research suggested.

The objective of this paper is to present an approach and experiences with introducing robotic devices accessible online to a course on Cyberphysical Systems in an undergraduate Software Engineering program. A closer look at both technologies, online labs and cyberphysical systems education, reveals that they are not in sync. Remote labs have embraced a wide variety of science and engineering disciplines, but they are not popular in software engineering. On the other hand, software engineering education, being crucial to the development of cyberphysical systems has not focused on such systems by any measure. This project and paper aim at addressing this gap.

This paper is related to dissemination and exploitation of the InFoCPS PhD research project: Failure of Cyber-Physical Systems (CPS) may cause extensive damage. Safety standards emphasize the use of formal analysis in CPS development processes. Performance degradation assessment and estimation of lifetime of energy storage (electric batteries) are vital in supporting maintenance decisions and guaranteeing CPS reliability. Existing formal analysis techniques mainly focus on specifying energy constraints in simplified manners and checking whether systems operate within given energy bounds. Leading to overlooked energy features that impede development of trustworthy CPS. Prognostics and health management (PHM) estimate energy uncertainty and predict remaining life of systems. We aim to utilize PHM techniques to rigorously model dynamic energy behaviors; resulting models are amenable to formal analysis. This project will increase the degree of maintenance of CPS while (non)-functional requirements are preserved correctly.

Smart robotics is one of the fields that are been greatly enriched by the development of Cyber-Physical Systems (CPS). Under this frame, the software facet of robots is as important as the physical one. As it is widely known, the ever-increasing complexity of robots usually implies a parallel increase in the number of failures of such systems. Due to this, system monitoring and anomaly detection play a key role in the implementation of smart robotics and Artificial Intelligence (AI) can significantly contribute to this task. Accordingly, some Exploratory Projection Pursuit techniques, mainly implemented through neural networks, are applied an compared in the present paper to monitor the performance of a component-based robotic software. Thanks to the intuitive projections obtained by these techniques, anomaly detection can be also visually carried out. The visualizations are validated on an open and up-to-date dataset containing information about software anomalies that affect the middleware (a crucial component in CPS) of the analysed robot.

V-model based development of cyber-physical systems and cyber-physical production systems

The development of Cyber Physical Systems (CPS) requires to model both the cyber (i.e., digital) parts, the physical parts and the interaction between them. The state of the practice in such domain usually involves different stakeholders, which use dedicated modeling languages tailored syntactically and semantically to their domain. Functional Mock-up Interface (FMI) is a recent standard, which provides technical facilities to enable the co-simulation among the different dedicated modeling languages. In this context, this paper investigates how discrete-event models of the cyber part are supported by FMI standard for co-simulation. Two main results are presented: 1) how SystemC models can be integrated into the FMI environment and 2) FMI limitations for the efficient use of discrete-event models in co-simulation. Both results are illustrated by using a simple but illustrative use case mixing models in SystemC (for the cyber part) and Modelica (for the physical part).

In the modern world, the problem of providing the population with high-quality food products is becoming increasingly important. This is due to a number of factors, such as the growth of the Earth’s population, globalization, which introduces significant changes in the usual models and structure of nutrition, insufficient efficiency of traditional technologies for processing agricultural products, etc. An important element in solving the problem is the use of cyber-physical systems (CPS), which are the integration of computing, physical and network components into private processes and system technologies. In the food industry, CPS are used in the management of production lines, product quality control, logistics, predictive models of demand, and contribute to the personalization of nutrition. In the future, the development of CPS and artificial intelligence technologies can lead to the creation of fully autonomous food production, where robot-assisted technologies will manage all processes - from growing raw materials to delivering finished products.

Cyber-Physical Systems (CPS) are often deployed in critical domains like health, traffic management etc. Therefore security is one of the major driving factor in development of CPS. In this paper, we focus on cryptographic hardware embedded in CPS and propose a simulation methodology to evaluate the security of these cryptographic hardware cores. Designers are often concerned about attacks like Side-Channel Analysis (SCA) which target the physical implementation of cryptography to compromise its security. SCA considers the physical leakage of a well chosen intermediate variable correlated with the secret. Certain countermeasures can be deployed, like dual-rail logic or masking, to resist SCA. However to design an effective countermeasure or to fix the vulnerable sources in a circuit, it is of prime importance for a designer to know the main leaking sources in the device. In practice, security of a circuit is evaluated only after the chip is fabricated followed by a certification process. If the circuit has security concerns, it should pass through all the design phases right from RTL to fabrication which increases time-to-market. In such a scenario, it is very helpful if a designer can determine the vulnerabilities early in the design cycle and fix them. In this paper, we present an evaluation of different strategies to verify the SCA robustness of a cryptographic circuit at different design steps, from the RTL to the final layout. We compare evaluation based on digital and electrical simulations in terms of speed and accuracy in a side-channel context. We show that a low-level digital simulation can be fast and sufficiently accurate for side-channel analysis.

The article reveals the periodization of the evolution of the main scientific and industrial discoveries in the field of digitalization, artificial intelligence, cyberphysics, as well as the prospects for the evolution of needs and product markets in connection with the development of cyber-physical systems. For cyberphysical systems, there is already an extensive knowledge base formed by various technical disciplines, including information systems, engineering, computer science, and mechanotronics. Neurotechnological companies aim to create a holistic brain interface capable of linking biological and artificial intelligence more closely. The neural interface is able to absolutely determine consumer behavior in accordance with the project. He will be able to set, set consumer behavior in a range in accordance with management goals – from absolutely rational to irrational. The range of applications of cyber-physical systems includes transport, logistics, medical devices, energy, security systems, asset and resource management, distributed robotics, military systems and many others. The products of the future are a computer program that simulates the work of the mind; physical media for storing information; means of extracting and transferring information located in the brain to a computer; quantum computers; controlling machines with the power of thought; exchange of information between people without additional “physical” control interfaces.

The development of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) has influenced Cyber-Physical Manufacturing Systems (CPMS). Collaborative manufacturing among organizations with geographically distributed operations using Nanomanufacturing (NM) requires integrated networking for enhanced productivity. The present research provides a unique cyber nanomanufacturing framework by combining digital design with various artificial neural networks (ANN) approaches to predict the optimal nano/micro-manufacturing process. It enables the visualization tool for real-time allocation of nano/micro-manufacturing resources to simulate machine availability for five types of NM processes in real-time for a dynamic machine identification system. This research establishes a foundation for a smart agent system with predictive capabilities for cyber nanomanufacturing in real-time.

The development of cyber-physical systems (CPS) has brought much attention of researchers to cyber-attack and cyber-security. A sensor attacker targeting on a supervised discrete event system can modify a set of sensor readings and cause the closed-loop system to reach undesirable states. In this letter, we propose a new attack detection mechanism under which the supervisor only needs to keep track of the last observable event received. Given a plant and a supervisor enforcing a state specification, we define a sensor attacker <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">threatening</i> if it may cause the closed-loop system to enter a forbidden state. Our goal is to verify whether there exists such a threatening sensor attacker for a given controlled system. A new structure, called All Sensor Attack (ASA), is proposed to capture all possible sensor attacks launched by the attacker. Based on the ASA automaton, a necessary and sufficient condition for the existence of a stealthy threatening sensor attacker is presented. Finally, we show that the condition can be verified in polynomial time.