Middleware Challenges for Cyber-Physical Systems

Cyber-Physical Systems (CPS) intrinsically combine hardware and physical systems with software and network, which are together creating complex and correlated interactions. CPS applications often experience uncertainty in interacting with environment through unreliable sensors. They can be faulty and exhibit runtime errors if developers have not considered environmental interaction uncertainty adequately. Existing work in verifying CPS applications ignores interaction uncertainty and thus may overlook uncertainty-related faults. To improve verification accuracy, in this article we propose a novel approach to verifying CPS applications with explicit modeling of uncertainty arisen in the interaction between them and the environment. Our approach builds an Interactive State Machine network for a CPS application and models interaction uncertainty by error ranges and distributions. Then it encodes both the application and uncertainty models to Satisfiability Modulo Theories (SMT) formula to leverage SMT solvers searching for counterexamples that represent application failures. The precision of uncertainty model can affect the verification results. However, it may be difficult to model interaction uncertainty precisely enough at the beginning, because of the uncontrollable noise of sensors and insufficient data sample size. To further improve the accuracy of the verification results, we propose an approach to identifying and calibrating imprecise uncertainty models. We exploit the inconsistency between the counterexamples’ estimate and actual occurrence probabilities to identify possible imprecision in uncertainty models, and the calibration of imprecise models is to minimize the inconsistency, which is reduced to a Search-Based Software Engineering problem. We experimentally evaluated our verification and calibration approaches with real-world CPS applications, and the experimental results confirmed their effectiveness and efficiency.

Cloud computing and its related virtualization technologies have become one of dominant trends to deploy software, compute difficult problems, store different types of data, and stream real-time video and audio. Due to its benefits from cost-efficiency and scalability to maintain server solutions, many organizations are migrating their server applications running on physical servers to virtual servers in cloud computing infrastructures. Moreover, cloud computing has enabled mobile and battery-powered devices to operate without strong processing power and large storage capacity. However, it is not trivial to use this trendy technology for medical Cyber Physical Systems (CPSs) which require processing tasks’ requests to send instructions to the local actuator within specified deadlines. Since a medical CPS device monitoring a patient’s vital signs may not have a second chance to recover from an erroneous state, achieving cost-efficiency with higher resource utilization in cloud computing may not be the ultimate goal to configure the healthcare IT infrastructure with medical CPS devices. In this paper, we focus on private cloud infrastructures with the fair resource sharing mechanism in order to run medical CPS applications. First, we introduce our medical CPS device model used for designing our cloud infrastructure following the Integrated Clinical Environment (ICE) standard developed by the Medical Device Plug-and-Play (MDPnP) project. Second, we investigate limitations to deploy CPS applications using existing auto-scaling mechanisms. Finally, we propose our novel middleware with a virtual resource sharing mechanism inspired by autonomic computing, and present its performance evaluation results simulated in the OpenStack private cloud.

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.

In Cyber-Physical Systems (CPS), cyber and physical components must work seamlessly in tandem. Runtime verification of CPS is essential yet very difficult, due to deployment environments that are expensive, dangerous, or simply impossible to use for verification tasks. A key enabling factor of runtime verification of CPS is the ability to integrate real-time simulations of portions of the CPS into live running systems. We propose a verification approach that allows CPS application developers to opportunistically leverage real-time simulation to support runtime verification. Our approach, termed B race B ind , allows selecting, at runtime, between actual physical processes or simulations of them to support a running CPS application. To build B race B ind , we create a real-time simulation architecture to generate and manage multiple real-time simulation environments based on existing simulation models in a manner that ensures sufficient accuracy for verifying a CPS application. Specifically, B race B ind aims to both improve simulation speed and minimize latency, thereby making it feasible to integrate simulations of physical processes into the running CPS application. B race B ind then integrates this real-time simulation architecture with an existing runtime verification approach that has low computational overhead and high accuracy. This integration uses an aspect-oriented adapter architecture that connects the variables in the cyber portion of the CPS application with either sensors and actuators in the physical world or the automatically generated real-time simulation. Our experimental results show that, with a negligible performance penalty, our approach is both efficient and effective in detecting program errors that are otherwise only detectable in a physical deployment.

Cyber-Physical Systems (CPS) is a relatively novel computing paradigm where there is a tight integration of communications, computation, and the physical environment. An important component of the CPS devices is the sensors they use to interact with each other and the physical world around them. With CPS applications, engineers monitor the structural health of highways and bridges, farmers check the health of their crops, and ecologists observe wildlife in their natural habitat. Nonetheless, current security models consider protecting only networking components of the CPS devices utilizing traditional security mechanisms (e.g., an intrusion detection system for the data that traverse the network protocol stacks). The protection mechanisms are not sufficient to protect CPS devices from threats emanating from sensory channels. Using sensory channels (e.g., light, temperature, infrared), an adversary can successfully attack systems. Specifically, the adversary can (1) trigger existing malware, (2) transfer malware, or (3) combine malicious use of different sensory channels to increase the impact of the attack on CPS devices. In this work, we focus on these novel sensory channel threats to CPS devices and applications. We first note how sensory channel threats are an emerging area for the CPS world. Then, we analyze the performance various sensory channel threats. Moreover, using an iRobot Create as our CPS platform, we exploit simple vulnerable programs on iRobot through its infrared channel. Finally, we introduce the design of a novel sensory channel aware intrusion detection system as a protection mechanism against the sensory channel threats for CPS devices.

Unmanned aerial vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas.

Editorial: This special issue features eight selected papers with high quality. The first article, “A Cost-Effective Methodology Applied to Videoconference Services on Hybrid Clouds” by Javier Cervino, Pedro Rodriguez, Irena Trajkovska, Fernando Escribano and Joaquin Salvachua, tackles the optimization of applications in multi-provider hybrid cloud scenarios from an economic point of view. However the approach was intended to introduce a novel solution by making maximum use of divide and rule. Also this article describes a methodology to create cost aware cloud applications that can be broken down into the three most important components in cloud infrastructures: computation, network and storage. A real videoconference system has been modified in order to evaluate this idea with both theoretical and empirical experiments. The proposed system has become a widely used as a tool in several national and European projects for e-learning and collaboration purposes. The second article, “An Efficient Dynamic Integration Middleware for Cyber-Physical Systems in Mobile Environments” by Young-Sik Jeong, Sang Oh Park and Jong Hyuk Park, proposes a cyber-physical system (CPS) middleware framework that ensures interoperability and communication between heterogeneous components in a global CPS network. A CPS is a tight integration of the system’s computational and physical elements. The CPS technology builds on the older discipline of embedded systems, and CPS applications can be found in diverse industry sectors, such as smart home, health care, and transportation. The article assume that a global CPS network that integrates different CPS networks appears in the near future. Through local and global communications, the proposed middleware makes mobile devices in different networks interoperable. The third article, “Particle Swarm Optimization with Skyline Operator for Fast Cloud-based Web Service Composition” by Shangguang Wang, Qibo Sun, Hua Zou, Fangchun Yang, proposed a fast Cloud-based web service T. Shon (*) Division of Information and Computer Engineering, College of Information Technology, Ajou University, Suwon, South Korea e-mail: taeshik.shon@gmail.com

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.

Security and Privacy Aspect of Cyber Physical Systems

This paper addresses the problem of devising an effective information fusion architecture for a task scheduling algorithm which facilitates data processing of a Cyber Physical System (CPS) under bounded latency for bursty or lossy traffic. Task scheduling traditionally caters to real-time systems where a feedback loop does not exist allowing the serviced application to be independent of the inputs from the server. However, owing to the nature of a near real-time CPS, such liberties cannot be entertained. Additionally, the advent of big data in CPS has necessitated the use of Cloud Computing as a scalable and cost effective alternative. Task scheduling in such CPSs, where inputs from the Cloud complete the feedback loop is a major research issue. Therefore, in this paper, we propose a multi-layered information fusion architecture which integrates such a task scheduling mechanism by accommodating both traffic bursts and packet losses. Our scheduling algorithm ensures that the overall latency always remains under an acceptable upper bound as required by the CPS application.

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 Physics Systems consists of physical systems and information systems. Modern power systems are increasingly dependent on information systems, experts and scholars are paying more and more attention to cyber attacks on CPS. This paper first introduces the existing research on cyber physical power system. Then this paper reviews the current status of existing cyber attacks. Finally, the modeling method for CPS is summarized such as correlation characteristic matrix, graph theory, complex network theory, finite state machine, mathematical programming and cellular automata method. These methods have vital theoretical and practical significance for the research of cyber physical power system.

Modern industry 4.0 applications are shifting towards decentralized automation of computing and cyber-physical systems (CPS), which necessitates building a robust, secure, and efficient system that performs complex interactions with other physical processes. To handle complex interactions in CPS, trust and consensus among various stakeholders is a prime concern. In a similar direction, consensus algorithms in blockchain have evolved over the years that focus on building smart, robust, and secure CPS. Thus, it is imperative to understand the key components, functional characteristics, and architecture of different consensus algorithms used in CPS. Many consensus algorithms exist in the literature with a specified set of functionalities, performance, and computing services. Motivated from these facts, in this survey, we present a comprehensive analysis of existing state-of-the-art consensus mechanisms and highlight their strength and weaknesses in decentralized CPS applications. In the first part, we present the scope of the proposed survey and identify gaps in the existing surveys. Secondly, we present the review method and objectives of the proposed survey based on research questions that address the gaps in existing studies. Then, we present a solution taxonomy of decentralized consensus mechanisms for various CPS applications. Then, open issues and challenges are also discussed in deploying various consensus mechanisms in the CPS with their merits and demerits. The proposed survey will act as a road-map for blockchain developers and researchers to evaluate and design future consensus mechanisms, which helps to build an efficient CPS for industry 4.0 stakeholders.

Optimizing intrusion detection in industrial cyber-physical systems through transfer learning approaches

Cyberphysical systems (CPSs) are new class of engineered systems that offer close interaction between cyber and physical components. The field of CPS has been identified as a key area of research, and CPSs are expected to play a major role in the design and development of future systems. In this paper, we survey recent advancements made in the development and applications of CPSs. We classify the existing research work based on their characteristics and identify the future challenges. We also discuss the examples of prototypes of CPSs. The aim of this survey is to enable researchers and system designers to get insights into the working and applications of CPSs and motivate them to propose novel solutions for making wide-scale adoption of CPS a tangible reality.