A simulation-based platform for assessing the impact of cyber-threats on smart manufacturing systems

Bracho, Alejandro; Saygin, Can; Wan, Hung-da; Lee, Yooneun; Zarreh, Alireza

doi:10.1016/j.promfg.2018.07.148

Cited by 28 publications

(12 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Horak et al (2021), Huraj et al (2021) and Wu et al (2020), respectively, a practical investigation of attacks on real production lines with an emphasis on the Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices to prove their weaknesses; creating a communication map and preventing communication degradation from infected IoT devices at the switch level towards the production line; use of machine learning to detect and prevent intrusions; and a testbed to investigate cyber intrusions, validating countermeasures. Already Bracho et al (2018), Leander et al (2020), Kosmowski et al (2019), Kühnle et al (2017), Lopez et al (2017) and Zarreh et al (2019), designed a more conceptual analysis of security issues through statistical testing; formulating a list of access control requirements for an intelligent manufacturing system; use of risk charts to determine and verify the level of performance and integrity of security functions; categorization of anomalies and detection mechanisms; and unification into a common framework to help identify potential solutions.…”

Section: Cyber Security Threats To Iot Applications and Service Domains 2020mentioning

confidence: 99%

The State of Cybersecurity in Smart Manufacturing Systems: A Systematic Review

Júnior

Pio

Fonseca

et al. 2021

EJBMR

View full text Add to dashboard Cite

With the advent of the so-called 4th Industrial Revolution, personified in the globally commented Industry 4.0, there is a change in progress in manufacturing systems, provided by the development of communication and information technologies, adding an intelligence component in manufacturing plants, through the possibility connectivity and interaction throughout the production chain (intelligent manufacturing systems or cyber-physical systems). However, this new paradigm has an extremely sensitive component, which is the question of the security of the data that is transferred and of the production processes itself. Due to this premise, this article proposed to bring, through a systematic literature review, research about the academic works related to security in these new manufacturing structures (smart manufacturing systems), analyzing which strategies, methodologies, techniques, and technologies have currently used to learn about their vulnerabilities and mitigate possible attacks.

show abstract

Section: Cyber Security Threats To Iot Applications and Service Domains 2020mentioning

confidence: 99%

The State of Cybersecurity in Smart Manufacturing Systems: A Systematic Review

Júnior

Pio

Fonseca

et al. 2021

EJBMR

View full text Add to dashboard Cite

show abstract

“…Moreover, Zarreh et al [17,18] assume the interaction of attacker and manufacturing enterprise as a game and proposed a framework to assess the repercussions of a cyber-physical thereat and choose a proper method to defend. Utilizing the same mindset, Bracho et al [19,20] introduces a simulation-based model to assess the consequences of manufacturing systems' performance under the presence of cybersecurity risks.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment for Cyber Security of Manufacturing Systems: A Game Theory Approach

Zarreh

Wan

Lee

et al. 2019

Procedia Manufacturing

Self Cite

View full text Add to dashboard Cite

This paper presents a novel approach using game theory to assess the risk likelihood in manufacturing systems quantifiably. Cybersecurity is a pressing issue in the manufacturing sector. Nevertheless, managing the risk in cybersecurity has become a critical challenge for modern manufacturing enterprises. In risk management thinking, the first step is to identify the risk, then validate it, and lastly, consider responses to the risk. If the risk is below the security risk appetite of the manufacturing system, it could be accepted. However, if it is above the risk appetite, the system should appropriately respond by either avoiding, transferring, or mitigating the risk. The validation of the risk in terms of severity and likelihood of the threat, however, is challenging because the later component is hard to quantify. In this paper, Failure Modes and Effects Analysis (FMEA) method is modified by employing game theory to quantitatively assess the likelihood of cyber-physical security risks. This method utilizes the game theory approach by modeling the rivalry between the attacker and the system as a game and then try to analyze it to find the likelihood of the attacker's action. We first define players of the game, action sets, and the utility function. Major concerns of cyber security issues in the manufacturing area are carefully considered in defining the cost function composed of defense policy, loss in production, and recovery. A linear optimization model is utilized to find a mixed-strategy Nash Equilibrium, which is the probability of choosing any action by the attacker also known as the likelihood of an attack. Numerical experiments are presented to further illustrate the method. Forecasting the attacker's behavior enables us to assess the cybersecurity risk in a manufacturing system and thereby be more prepared with plans of proper responses.

show abstract

“…Grey wolves tend to encircle prey before the hunt. This behaviour can be mathematically simulated through equations (5)(6)(7)(8).…”

Section: Encircling Preymentioning

confidence: 99%

“…Cloud manufacturing (CMfg) has been proposed as the panacea to implement this groundbreaking idea in recent years. Nonetheless, to fully achieve this goal, there remains significant issues with regard to enabling technologies [3][4][5][6][7], trust evaluation [8], task and resource description [9,10], scheduling [11][12][13] and service composition, among which the last one, is the key to offering composite services through the above-mentioned collaboration among partners. This has to be done by selecting the optimal resource for each sub-task out of the existing candidates at the resources pool and composing them to achieve the highest quality of service (QoS).…”

Section: Introductionmentioning

confidence: 99%

Optimal composition of tasks in cloud manufacturing platform: a novel hybrid GWO-GA approach

Bouzary¹,

Chen²,

Shahin³

2019

Preprint

View full text Add to dashboard Cite

Emerging cloud manufacturing paradigm aims towards providing highly integrated solutions via enabling cooperation between distributed manufacturing resources and capabilities. Implementation of this groundbreaking idea, however, is facing serious challenges springing from the currently centralized industrial structures. In order to help it make its way out, researchers have to address a number of pivotal issues in this regard. Service composition and optimal selection (SCOS), which tackles the problem of optimally selecting and combining available resources into a composite service is one of them. To deal with this NP-hard problem, we developed a novel hybrid algorithm based on the recentlyintroduced grey wolf optimizer (GWO) in which evolutionary operators are also embedded into the hunting mechanism of the basic algorithm.This approach not only makes it possible to adapt an algorithm with continuous structure such as GWO to solve a combinatorial problem such as SCOS, but also empowers it with providing higher exploration through crossover and mutation operators. Experiments conducted clearly proves the superior performance of the proposed algorithm over existing discrete variations of GWO and genetic algorithm, especially in large-scale SCOS problems.

show abstract

A simulation-based platform for assessing the impact of cyber-threats on smart manufacturing systems

Cited by 28 publications

References 27 publications

The State of Cybersecurity in Smart Manufacturing Systems: A Systematic Review

The State of Cybersecurity in Smart Manufacturing Systems: A Systematic Review

Risk Assessment for Cyber Security of Manufacturing Systems: A Game Theory Approach

Optimal composition of tasks in cloud manufacturing platform: a novel hybrid GWO-GA approach

Contact Info

Product

Resources

About