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A framework to assess impacts of cyber attacks in manufacturing
Abstract
Recent trends in manufacturing and industry accelerate the interconnection of industrial control systems between each other and over public networks. This brings an increase of cyber attack impact with it as the number of potential targets rises and the consequences of the attacks gain in severity. In order to build secure manufacturing systems, it is paramount to measure the possible impact of cyber attacks. This is required to evaluate security controls towards their effectiveness in attack scenarios.
In this work, a proposal for an impact assessment framework in manufacturing is given. A suitable attacker model for execution of the attacks is provided. An evaluation metric for quantifying attack impact on manufacturing systems is developed. A light-weight modeling technique is presented and used to study the impact of cyber attacks on a cellular assembly setup. Different attack scenarios are implemented and simulated within the framework. The simulations provide detailed insight and illustrate attack impact.
... In particular, the impact on industrial manufacturing control systems [1], [4]- [7] has received particular attention due to its integral nature in our everyday lives. For such analyses, experiments on real ICS or experimental testbeds are not feasible as they can damage (impact) physical equipment, the environment, or human lives [5]. Therefore, most of these studies adopt some model-based approach to model and simulate attacks on a running ICS model to uncover how various attacks can delay, disrupt, or halt physical ICS operations [1] causing serious economic, operational, and environmental impacts [8]. ...
... We chose a manufacturing ICS case study due to the emerging interest of researchers in this domain. Some notable mentions are the impact analysis of false sequential logic attacks on chemical manufacturing process [4], stealthy attacks on manufacturing assembly lines [5], field data manipulation attacks on oil and gas manufacturing systems [6], data tampering and spoofing attacks on cell manufacturing systems [1], and insider attacks on manufacturing production lines [7]. Examples of impact analysis on other types of ICS include combined tampering and spoofing attacks on a wastewater treatment system [15], bias injection attacks on power systems [9], integrity attacks on nuclear reactors [11], and integrity attacks on generic engine cooling systems [10], among others [8]. ...
... Following a modified read, the Processing Agent temporarily entered the stalled state WFI. The arbitrary attacks may also cause modification with expected values at that moment (e.g., attempts [4][5][6][7][8] with no observed impact. Due to the randomized behavior, the attacker may also correct its own attack, e.g., attempt 3 re-modifying the material variable to the expected value. ...
... Thus, building and maintaining dependable ICS involves understanding how the availability and integrity of ICS operations can be impacted. Since experimenting with ICS controlling live plant operations is usually infeasible, a suitable alternative to study potential impacts involves using system modeling to simulate monitoring, control, and actuation of ICS components under malicious attacks [5]. However, the differences between IT and ICS security mean that such approaches need to be ICS-specific to allow for a more objective and comprehensive evaluation [3]. ...
... Following the devastating impact of Stuxnet [2] in 2010, researchers have proposed diverse impact analysis approaches to study the potential impact on ICS operations [3]. However, most approaches are tied to specific modeling formalisms [1], [5]- [14] and/or modeling tools [1], [6], [9], [12], [15]- [17] (see Section II for details). Thus, the potential adoption of these approaches is limited to the intended formalisms and/or tools. ...
... Lastly, quantifying impact required developing statistical model checking (SMC) [22] queries, which deals better with state space explosion but has limited expressiveness [23]. Other proposed impact analysis approaches involve similar required expertise to be developed in reliability graphs [5], attack fault graphs [6], graph-based dynamical systems [7], finite state machines [8], stochastic hybrid automata [9], influence diagrams [10], stock-flow diagrams [11], hierarchical flow models [12], geometrical modeling [13], and hybrid Petri nets [14], among others. ...
... The Risk of Lack of Cybersecurity and Data Protection is characterized by the absence of security systems and programs for computers, networks, and software, which can result in a lack of protection of information and data in the company, facilitating access by malicious individuals [2,12,19,22,[29][30][31]35,42,58,69,71,72,77,84,85,110,112,117,122,127]. ...
... This type of attack occurs due to the invasion of computers and systems, often by hackers. Through this invasion, valuable data and information can be leaked or even modified, all due to system vulnerabilities [2,11,19,24,[28][29][30][31][32]35,39,41,45,51,52,59,61,69,70,[75][76][77]82,84,97,111,125,[127][128][129][130]. ...
... Many of these services are connected to the internet, stored in the cloud, and generate large amounts of data, thereby increasing the likelihood of cyberattacks, privacy invasions, data leaks, lack of cybersecurity, and data protection. This is due to the digitization and interconnection of healthcare systems, which can compromise the availability and reliability of patient-related data [11,29,127,145,146,148]. ...
This study aims to develop a theoretical model for digital risks arising from implementing Industry 4.0 (represented by the acronym TMR-I4.0). A systematic literature review was initially conducted using the Methodi Ordinatio methodology to map the principal dimensions and digital risks associated with Industry 4.0 in order to achieve this objective. After completing the nine steps of Methodi, a bibliographic portfolio with 118 articles was obtained. These articles were then subjected to content analysis using QSR Nvivo® version 10 software to categorize digital risks. The analysis resulted in the identification of 9 dimensions and 43 digital risks. The categorization of these risks allowed the construction of maps showing the digital risks and their impacts resulting from the implementation of Industry 4.0. This study advances the literature by proposing a comprehensive categorization of digital risks associated with Industry 4.0, which resulted from an exhaustive literature review. At the conclusion of the study, based on the proposed Theoretical Risk Model for Digital Risks arising from the implementation of Industry 4.0, a research agenda for future studies will be proposed, enabling other researchers to further explore the landscape of digital risks in Industry 4.0.
... This leads to two important observations. First, regardless of its maturity, impact assessment frameworks developed for IT networks will not be equally effective and/or applicable to OT systems (Giehl et al. 2019). Second, in systems where IT and OT systems are equally important, such as industrial control systems (ICS) or cyber-physical systems (CPS), cyberattacks will not be limited to creating cyber impacts only but will inevitably lead to physical impacts and/or cascading effects through system operations. ...
... Systems with highly coupled physical and cyber components (e.g., ICS and CPS) that make up today's critical infrastructures are novel technologies not readily available for security evaluation (Giehl et al. 2019). The construction and maintenance of physical testbeds to study such systems are costly, and tests on live equipment are challenging due to their high availability requirement. ...
... More recently, Giehl, Wiedermann, and Plaga (2019) proposed a framework where reliability graphs are used to assess the impact on manufacturing systems. Each edge of the reliability graph is assigned a probability that represents its reliability, and the overall system reliability is measured by the averaged sum over the availability of the system components. ...
... With the rapid rise in the networking technologies, multiple industries such as manufacturing [1], healthcare [2], financial institutions [3] and even worldwide government agencies [4] are adopting internet based solutions for services and data storage. These systems have to manage, process or store sensitive user data to provide the services and fulfill their functionalities. ...
With increased reliance on Internet based technologies, cyberattacks compromising users' sensitive data are becoming more prevalent. The scale and frequency of these attacks are escalating rapidly, affecting systems and devices connected to the Internet. The traditional defense mechanisms may not be sufficiently equipped to handle the complex and ever-changing new threats. The significant breakthroughs in the machine learning methods including deep learning, had attracted interests from the cybersecurity research community for further enhancements in the existing anomaly detection methods. Unfortunately, collecting labelled anomaly data for all new evolving and sophisticated attacks is not practical. Training and tuning the machine learning model for anomaly detection using only a handful of labelled data samples is a pragmatic approach. Therefore, few-shot weakly supervised anomaly detection is an encouraging research direction. In this paper, we propose an enhancement to an existing few-shot weakly-supervised deep learning anomaly detection framework. This framework incorporates data augmentation, representation learning and ordinal regression. We then evaluated and showed the performance of our implemented framework on three benchmark datasets: NSL-KDD, CIC-IDS2018, and TON_IoT.
... They provide scientific analyses of individual aspects of protocols commonly found in industrial environments. Giehl et al. provide a framework to assess security controls in manufacturing environments [16]. Cherdantseva et al. provide a survey of existing risk assessment methods and evaluate their usefulness with respect to Supervisory Control And Data Acquisition (SCADA) scenarios [2]. ...
The fourth industrial revolution leads to an increased use of embedded computation and intercommunication in an industrial environment. While reducing cost and effort for set up, operation and maintenance, and increasing the time to operation or market respectively as well as the efficiency, this also increases the attack surface of enterprises. Industrial enterprises have become targets of cyber criminals in the last decade, reasons being espionage but also politically motivated. Infamous attack campaigns as well as easily available malware that hits industry in an unprepared state create a large threat landscape. As industrial systems often operate for many decades and are difficult or impossible to upgrade in terms of security, legacy-compatible industrial security solutions are necessary in order to create a security parameter. One plausible approach in industry is the implementation and employment of side-channel sensors. Combining readily available sensor data from different sources via different channels can provide an enhanced insight about the security state. In this work, a data set of an experimental industrial set up containing side channel sensors is discussed conceptually and insights are derived.
... Schneider and Böttinger use autoencoders in order to detect real attacks in an industrial data set in an unsupervised fashion [30]. A framework for assessing the impact of cyber attacks in production environments is presented by Giehl et al. [13]. They evaluate their approach on the SUTD Security Showdown (S3) 2017 (S317) data set provided by the iTrust, Centre for Research in Cyber Security, Singapore University of Technology and Design [17]. ...
Due to the fourth industrial revolution, industrial applications make use of the progress in communication and embedded devices. This allows industrial users to increase efficiency and manageability while reducing cost and effort. Furthermore, the fourth industrial revolution, creating the so-called Industry 4.0, opens a variety of novel use and business cases in the industrial environment. However, this progress comes at the cost of an enlarged attack surface of industrial companies. Operational networks that have previously been phyiscally separated from public networks are now connected in order to make use of new communication capabilites. This motivates the need for industrial intrusion detection solutions that are compatible to the long-term operation machines in industry as well as the heterogeneous and fast-changing networks. In this work, process data is analysed. The data is created and monitored on real-world hardware. After a set up phase, attacks are introduced into the systems that influence the process behaviour. A time series-based anomaly detection approach, the Matrix Profiles, are adapted to the specific needs and applied to the intrusion detection. The results indicate an applicability of these methods to detect attacks in the process behaviour. Furthermore, they are easily integrated into existing process environments. Additionally, one-class classifiers One-Class Support Vector Machines and Isolation Forest are applied to the data without a notion of timing. While Matrix Profiles perform well in terms of creating and visualising results, the one-class classifiers perform poorly.
... They provide scientific analyses of individual aspects of protocols commonly found in industrial environments. Giehl et al. provide a framework to assess security controls in manufacturing environments [16]. Cherdantseva et al. provide a survey of existing risk assessment methods and evaluate their usefulness with respect to Supervisory Control And Data Acquisition (SCADA) scenarios [2]. ...
The fourth industrial revolution leads to an increased use of embedded computation and intercommunication in an industrial environment. While reducing cost and effort for set up, operation and maintenance, and increasing the time to operation or market respectively as well as the efficiency, this also increases the attack surface of enterprises. Industrial enterprises have become targets of cyber criminals in the last decade, reasons being espionage but also politically motivated. Infamous attack campaigns as well as easily available malware that hits industry in an unprepared state create a large threat landscape. As industrial systems often operate for many decades and are difficult or impossible to upgrade in terms of security, legacy-compatible industrial security solutions are necessary in order to create a security parameter. One plausible approach in industry is the implementation and employment of side-channel sensors. Combining readily available sensor data from different sources via different channels can provide an enhanced insight about the security state. In this work, a data set of an experimental industrial set up containing side channel sensors is discussed conceptually and insights are derived.
... Schneider and Böttinger use autoencoders in order to detect real attacks in an industrial data set in an unsupervised fashion [30]. A framework for assessing the impact of cyber attacks in production environments is presented by Giehl et al. [13]. They evaluate their approach on the SUTD Security Showdown (S3) 2017 (S317) data set provided by the iTrust, Centre for Research in Cyber Security, Singapore University of Technology and Design [17]. ...
Due to the fourth industrial revolution, industrial applications make use of the progress in communication and embedded devices. This allows industrial users to increase efficiency and manageability while reducing cost and effort. Furthermore, the fourth industrial revolution, creating the so-called Industry 4.0, opens a variety of novel use and business cases in the industrial environment. However, this progress comes at the cost of an enlarged attack surface of industrial companies. Operational networks that have previously been phyiscally separated from public networks are now connected in order to make use of new communication capabilites. This motivates the need for industrial intrusion detection solutions that are compatible to the long-term operation machines in industry as well as the heterogeneous and fast-changing networks. In this work, process data is analysed. The data is created and monitored on real-world hardware. After a set up phase, attacks are introduced into the systems that influence the process behaviour. A time series-based anomaly detection approach, the Matrix Profiles, are adapted to the specific needs and applied to the intrusion detection. The results indicate an applicability of these methods to detect attacks in the process behaviour. Furthermore, they are easily integrated into existing process environments. Additionally, one-class classifiers One-Class Support Vector Machines and Isolation Forest are applied to the data without a notion of timing. While Matrix Profiles perform well in terms of creating and visualising results, the one-class classifiers perform poorly.
The Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality control. In particular, IoT and digital manufacturing technologies have substantially accelerated product development- cycles and manufacturers can now create products of a complexity and precision not heretofore possible. New threats to supply chain security have arisen from connecting machines to the Internet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manufacturing systems and tampering with digital files, attackers can manipulate physical characteristics of parts and change the dimensions, shapes, or mechanical properties of the parts, which can result in parts that fail in the field. These defects increase manufacturing costs and allow silent problems to occur only under certain loads that can threaten safety and/or lives. To understand potential dangers and protect manufacturing system safety, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality control measures for counteracting these attacks. We systematically identify and classify possible cyber-physical attacks and connect the attacks with variations in manufacturing processes and quality control measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality control measures.
Conducting security tests such as vulnerability discovery within Industrial Control Systems (ICS) help reduce their vulnerability to cyber attacks. Unfortunately, the extreme availability requirements on ICS in operation make it difficult to conduct security tests in practice. For this reason, researchers and practitioners turn to testbeds that mimic real ICS. This study surveys ICS testbeds that have been proposed for scientific research. A total of 30 testbeds are identified. Most of these aim to facilitate vulnerability analysis, education and tests of defense mechanisms. Testbed components are typically implemented as simulation models. Testbed fidelity is rarely addressed, and at best briefly discussed.
Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space. Moreover, by utilizing advanced information analytics, networked machines will be able to perform more efficiently, collaboratively and resiliently. Such trend is transforming manufacturing industry to the next generation, namely Industry 4.0. At this early development phase, there is an urgent need for a clear definition of CPS. In this paper, a unified 5-level architecture is proposed as a guideline for implementation of CPS.
Degradation analysis can be used to assess reliability when few or even no failures are expected in a life test. In this paper, we use a simple but useful degra-dation model to compare degradation analysis and traditional failure-time analysis in terms of asymptotic efficiency. The comparisons consider a range of practical testing situations and provide insight into the trade-offs between these two meth-ods of estimating the quantiles of the time-to-failure distribution. We investigate the effect that the number of inspections, the amount of measurement error, and the quantile of interest have on the asymptotic variances of the quantile estima-tors. Although measurement error can induce some loss of precision in degradation analysis, our comparisons show that, except in extreme cases, degradation analysis provides more precision than traditional failure-time analysis.
We present two stochastic failure models for the reliability evaluation of manufacturing equipment that degrades due to its
complex operating environment. The first model examines the case when the environment is a temporally nonhomogeneous continuous-time
Markov chain, and the second assumes the environment is a temporally homogeneous semi-Markov process on a finite space. Derived
are transform expressions for the lifetime distributions. A few examples are provided to illustrate the main results.
The Internet has become essential to all aspects of modern life, and thus the consequences of network disruption have become increasingly severe. It is widely recognised that the Internet is not sufficiently resilient, survivable, and dependable, and that significant research, development, and engineering is necessary to improve the situation. This paper provides an architectural framework for resilience and survivability in communication networks and provides a survey of the disciplines that resilience encompasses, along with significant past failures of the network infrastructure. A resilience strategy is presented to defend against, detect, and remediate challenges, a set of principles for designing resilient networks is presented, and techniques are described to analyse network resilience.
Supervisory control and data acquisition(SCADA)systems arecommonly used to monitor and control critical infrastructure assets. However, over the past two decades, they have evolved from closed, proprietary systems to open networks comprising commodity platforms running common operating systems and TCP/IP stacks. The open architecture and increased connectivity provide more functionality and reduce costs, but they significantly increase the vulnerabilities and the exposure to threats. Since SCADA systems and the critical infrastructure assets they control must have 24/7 availability, it is imperative to understand and manage the risk. This paper makes the case for a European SCADA security testbed that can be used to analyze vulnerabilities, threats and the impact of attacks, ultimately helping design new architectures and robust security solutions. The paper also discusses testbed requirements, deployment strategies and potential hurdles.
Keywords: SCADA systems, risk assessment, security testbed
This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.
Information Security Management consists of various facets, such as Information Security Policy, Risk Analysis, Risk Management, Contingency Planning and Disaster Recovery; these are all interrelated in some way, often causing uncertainty and confusion among top management. This paper proposes a model for Information Security Management, called an Information Security Management Model (ISM²), which puts all the various facets in context. The model consists of five different levels, defined on a security axis. ISM² introduces the idea of international security criteria or international security standards. The rationale behind these is to enable information security evaluation according to internationally accepted criteria. Due to the lack of internationally recognized and/or accepted information security standards and criteria, this model cannot be implemented in its totality at this time. A restricted form is implemented, forming an information security evaluation tool. This tool can be used for information security management with great success within an organization.
Customer-individual production in manufacturing is a current trend related to the Industrie 4.0 paradigm. Creation of design files by the customers is becoming more frequent. These design files are typically generated outside the company boundaries and then transferred to the organization where they are eventually processed and scheduled for production. From a security perspective, this introduces new attack vectors targeting producing companies. Design files with malicious configuration parameters can threaten the availability of the manufacturing plant resulting in financial risks and can even cause harm to humans. Human verification of design files is error-prone why an automated solution is required. A graph-theoretic modeling framework for machine tools capable of verifying the security of product designs is proposed. This framework is used to model an exemplary production process implemented in a wood processing plant based on the experiences of a real-world case study. Simulation of the modeled scenario shows the feasibility of the framework. Apart from security verification, the approach can be adopted to decide if a product design can be manufactured with a given set of machine tools.
Since the early 1960, industrial process control has been applied by electric systems. In the mid 1970's, the term SCADA emerged, describing the automated control and data acquisition. Since most industrial and automation networks were physically isolated, security was not an issue. This changed, when in the early 2000's industrial networks were opened to the public internet. The reasons were manifold. Increased interconnectivity led to more productivity, simplicity and ease of use. It decreased the configuration overhead and downtimes for system adjustments. However, it also led to an abundance of new attack vectors. In recent time, there has been a remarkable amount of attacks on industrial companies and infrastructures. In this paper, known attacks on industrial systems are analysed. This is done by investigating the exploits that are available on public sources. The different types of attacks and their points of entry are reviewed in this paper. Trends in exploitation as well as targeted attack campaigns against industrial enterprises are introduced.
Industrial control systems are cyber-physical systems that are used to operate critical infrastructures such as smart grids, traffic systems, industrial facilities, and water distribution networks. The digitalization of these systems increases their efficiency and decreases their cost of operation, but also makes them more vulnerable to cyber-attacks. In order to protect industrial control systems from cyber-attacks, the installation of multiple layers of security measures is necessary. In this paper, we study how to allocate a large number of security measures under a limited budget, such as to minimize the total risk of cyber-attacks. The security measure allocation problem formulated in this way is a combinatorial optimization problem subject to a knapsack (budget) constraint. The formulated problem is NP-hard, therefore we propose a method to exploit submodularity of the objective function so that polynomial time algorithms can be applied to obtain solutions with guaranteed approximation bounds. The problem formulation requires a preprocessing step in which attack scenarios are selected, and impacts and likelihoods of these scenarios are estimated. We discuss how the proposed method can be applied in practice.
As the sophistication of cyber-attacks increases, understanding how to defend critical infrastructure systems-energy production, water, gas, and other vital systems-becomes more important, and heavily mandated. Industrial Network Security, Second Edition arms you with the knowledge you need to understand the vulnerabilities of these distributed supervisory and control systems.
Electric power grids have been identified as critical infrastructures. They are increasingly dependent on Information and Communication Technologies (ICTs) for the operation and control of physical facilities. It can be envisioned that on top of the power infrastructure reside ICT layers that are coupled with the electric grids. As the ICT connectivity increases, so does the potential for cyber intrusions. This paper describes the importance of cyber security for power systems. A testbed architecture provides an accurate and powerful tool for identification of cyber-physical system vulnerabilities, security enhancement, impact analysis, and mitigation of cyber attacks. Simulation scenarios of cyber intrusions and attacks on the power grid, using the testbed, are discussed. The impact analysis' simulation results capture the dynamic behavior of IEEE 39-bus system as a response to cyber attacks which may evolve into a partial or complete blackout. The problem of fast restoration from blackout after cyber attacks is identified.
Electric power grids have been identified as critical infrastructures. They are increasingly dependent on Information and Communication Technologies (ICTs) for the operation and control of physical facilities. It can be envisioned that on top of the power infrastructure reside ICT layers that are coupled with the electric grids. As the ICT connectivity increases, so does the potential for cyber intrusions. This paper describes the importance of cyber security for power systems. A testbed architecture provides an accurate and powerful tool for identification of cyber-physical system vulnerabilities, security enhancement, impact analysis, and mitigation of cyber attacks. Simulation scenarios of cyber intrusions and attacks on the power grid, using the testbed, are discussed. The impact analysis' simulation results capture the dynamic behavior of IEEE 39-bus system as a response to cyber attacks which may evolve into a partial or complete blackout. The problem of fast restoration from blackout after cyber attacks is identified.
Today, embedded, mobile, and cyberphysical systems are ubiquitous and used in many applications, from industrial control systems, modern vehicles, to critical infrastructure. Current trends and initiatives, such as "Industrie 4.0" and Internet of Things (IoT), promise innovative business models and novel user experiences through strong connectivity and effective use of next generation of embedded devices. These systems generate, process, and exchange vast amounts of security-critical and privacy-sensitive data, which makes them attractive targets of attacks. Cyberattacks on IoT systems are very critical since they may cause physical damage and even threaten human lives. The complexity of these systems and the potential impact of cyberattacks bring upon new threats.
This paper gives an introduction to Industrial IoT systems, the related security and privacy challenges, and an outlook on possible solutions towards a holistic security framework for Industrial IoT systems.
Network reliability encompasses a range of issues related to the design and analysis of networks which are subject to the random failure of their components. Relatively simple, and yet quite general, network models can represent a variety of applied problem environments. Network classes for which the models are discussed are particularly appropriate include data communications networks, voice communications networks, transportation networks, computer architectures, electrical power networks and command and control systems. The ultimate objective of research in the area of network reliability is to give design engineers procedures to enhance their ability to design networks for which reliability is an important consideration. Ideally, one would like to generate network design models and algorithms which take as input the characteristics of network components as well as network design criteria, and produce as output an "optimal" network design.
Most of the techniques for the cell design (CD) problem in cellular manufacturing (CM) consider only the machine-part incidence matrix as the input. They then convert this matrix into a block diagonal form to create a dedicated and independent cell for each part family, without laying out machines. Yet due to the lack of information on the layout, hence the lack of information on the performance of the shop floor, the benefits of CM cannot be validated. Furthermore, operational issues, e.g. scheduling, have an effect on the CD. However, current techniques are not comprehensive enough for a complete CD which should consider the aforementioned issues as a whole. This paper proposes a two-phase method based on total manufacturing lead time (MLT) reduction to overcome these drawbacks. In the first phase, the system is simulated by considering all of the operational issues under the assumption of zero material handling times to minimize total MLT. Besides minimized total MLT, the first phase also yields the waiting times of parts and the volume of the parts-flow between machines, which are used to find similarity measures between machines in the second phase. The second phase then exploits an algorithm which creates and uses these similarity measures to construct a layout by locating machines with higher similarity next to each other to justify the assumption of minimal total MLT and to minimize total material handling time.
This paper discusses reliability properties of some simple paralleled or redundant systems, where repair is possible in case of failure. We are assuming here that a ``failure'' may always be instantly identified, and the appropriate steps taken. In certain problems such an assumption is not warranted. The ``systems'' discussed are composed of two identical ``subsystems,'' e.g., computers, or radars, and the system is considered to be in a state of failure when, and only when, both subsystems are simultaneously in such a state. Such system design strategies have been proposed for various applications, but have received little analysis. Two measures of reliability are discussed: 1) the time to system failure, measured from an instant at which both subsystems are operative, and 2) the long-run availability of the system, where the latter means the average fraction of the time during which the system is able to perform its function. Analysis is based on the assumption of ``random'' (Poisson-like) failure for the subsystems (for theoretical justification see Drenick [2]), and independent but otherwise arbitrarily distributed repair times. It is of some interest that several of the important operational measures deduced, depend in detail upon the form of the distribution of repair times, as it is summarized in its Laplace transform, and not simply upon certain simple averages or moments of repair time.
This paper presents a framework for cyber attack impact analysis of a smart grid. We focus on the model synthesis stage in which both cyber and physical grid entity relationships are modeled as directed graphs. Each node of the graph has associated state information that is governed by dynamical system equations that model the physics of the interaction (for electrical grid components) or functionality (for cyber grid elements). We illustrate how cause-effect relationships can be conveniently expressed for both analysis and extension to large-scale smart grid systems.
In this paper we provide a concise review of the literature on cell formation aspects of design of cellular manufacturing systems. The usefulness and limitations of existing approaches are identified. Future research directions are explored considering manufacturing requirements.
Information Security Management consists of various facets, such as Information Security Policy, Risk Analysis, Risk Management, Contingency Planning and Disaster Recovery; these are all interrelated in some way, often causing uncertainty and confusion among top management. This paper proposes a model for Information Security Management, called an Information Security Management Model (ISM2), which puts all the various facets in context. The model consists of five different levels, defined on a security axis. ISM2 introduces the idea of international security criteria or international security standards. The rationale behind these is to enable information security evaluation according to internationally accepted criteria. Due to the lack of internationally recognized and/or accepted information security standards and criteria, this model cannot be implemented in its totality at this time. A restricted form is implemented, forming an information security evaluation tool. This tool can be used for information security management with great success within an organization.
The development of a trustworthy smart grid requires a deeper understanding of potential impacts resulting from successful cyber attacks. Estimating feasible attack impact requires an evaluation of the grid's dependency on its cyber infrastructure and its ability to tolerate potential failures. A further exploration of the cyber–physical relationships within the smart grid and a specific review of possible attack vectors is necessary to determine the adequacy of cybersecurity efforts. This paper highlights the significance of cyber infrastructure security in conjunction with power application security to prevent, mitigate, and tolerate cyber attacks. A layered approach is introduced to evaluating risk based on the security of both the physical power applications and the supporting cyber infrastructure. A classification is presented to highlight dependencies between the cyber–physical controls required to support the smart grid and the communication and computations that must be protected from cyber attack. The paper then presents current research efforts aimed at enhancing the smart grid's application and infrastructure security. Finally, current challenges are identified to facilitate future research efforts.
An agent-based framework for the impact analysis of faults and attacks in large-scale networks is discussed. The framework is used to discover attack points and to examine the behavior of critical network components during an attack or system fault. The two common types of attacks are server attacks such as TCP SYN, and ICMP flood, and routing attacks, such as distributed denial-of-service (DDoS) attacks. In network attacks, attackers overwhelm the target system with a continuous flood of traffic designed to consume all system resources. The framework analyze the impact of multiple failures on overall system behavior and identify critical resources and vulnerabilities.
Recently the use of public key encryption to provide secure network communication has received considerable attention. Such public key systems are usually effective against passive eavesdroppers, who merely tap the lines and try to decipher the message. It has been pointed out, however, that an improperly designed protocol could be vulnerable to an active saboteur, one who may impersonate another user or alter the message being transmitted. Several models are formulated in which the security of protocols can be discussed precisely. Algorithms and characterizations that can be used to determine protocol security in these models are given.
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