Analysis of safety and security challenges and opportunities related to cyber-physical systems

El-Kady, Ahmed Hamdy; Halim, Syeda Zohra; El‐Halwagi, Mahmoud M.; Khan, Faisal

doi:10.1016/j.psep.2023.03.012

Cited by 27 publications

(7 citation statements)

References 195 publications

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“…According to Figure 2, using the VOSviewer tool, a bibliometric study reveals the connections between 3D modeling, 3D reconstruction, and computer algorithms in relation to SLAM with AR and VR systems, highlighting their significance in the field [54][55][56][57][58][59][60][61]. These findings underscore the additional need for 3D reconstructions and modeling to ensure accurate representation of environmental data, which is essential for SLAM's mapping and localization objectives.…”

Section: Resultsmentioning

confidence: 99%

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

Obaideen,

AlShabi

2024

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI

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The growing sector of Extended Reality (XR), comprising Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), requires successful approaches for localization and mapping. Simultaneous Localization and Mapping (SLAM) has gained more importance in XR uses. This research conducts an in-depth bibliometric examination of the utilization of SLAM in XR settings, analyzing publications from the last ten years. We investigate the developing trends, fields of knowledge, prominent contributors, and important publications that have influenced this intersection. Our study indicates a notable increase in research on incorporating SLAM in XR, especially in fields such as gaming, architectural visualization, and remote collaboration. A study of the region highlights North America and the Asia-Pacific as key players in this field of research. The research also discusses the difficulties involved in integrating SLAM into XR, such as handling the computational requirements, guaranteeing real-time processing, and accomplishing successful sensor fusion. This paper strives to provide a thorough overview of the current status of SLAM in XR, pinpointing gaps that already exist and suggesting directions for further research. These observations aim to help researchers, developers, and industry professionals who want to use SLAM's capabilities in the quickly changing XR field.

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Section: Resultsmentioning

confidence: 99%

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

Obaideen,

AlShabi

2024

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI

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“…Cyber-physical systems (CPS) mainly refers to next generation systems that integrate communication, computation, and control in order to achieve stability, high performance, robustness, and efficiency as it relates to physical systems [1]. Therefore, CPS is a physically interconnected system that can be remotely controlled, monitored, and operated with real-time perception [2].…”

Section: Introductionmentioning

confidence: 99%

“…Their common objective is to safeguard CPS from failures [6]. According to authors in [2], security is described as ensuring the integrity, authenticity, and confidentiality of information through the prevention of intentional threats, whereas safety is defined as avoiding operational dangers by preventing these unintended threats.…”

Section: Introductionmentioning

confidence: 99%

Security and Safety in Cyber-Physical System (CPS): An Inclusive Threat Model

Mardiana Mohamad Noor,

Ali Selamat,

Nurulakmar Abu Husain

et al. 2024

ARASET

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A Cyber-Physical System (CPS) is a combination of computational algorithms and physical processes that are integrated together. Cyber-Physical Systems (CPS) integrate computer and communication capabilities with the monitoring and management of physical parts, establishing a mutually beneficial interaction between the cyber and physical components. Industrial Control System (ICS) is one example of CPS which integrates the physical (OT) and cyber domains (IT), which makes them more vulnerable to attacks. Two essential characteristics of Cyber-Physical Systems (CPS) are safety and security. Threat models are methods for identifying, analysing, and proposing security control countermeasures for threats and their capabilities. However, the threat model methods which are used for the traditional IT systems are not sufficient as they do not include the physical interactions, consequences and impacts to the safety aspects in the Operational Technology (OT). On the other hand, a risk assessment analyses attack scenario, examines cybersecurity from the attacker's point of view, and gives cost-benefit data to support the expenditure on security measures. This study proposes an inclusive attacker’s centric threat model and pro-active risk assessment model for CPS using Mamdani Fuzzy Inference System (FIS). The outcomes of the threat model prove that the lateral propagation of the threat is possible and threat may also propagate from the CPS assets to the IT segment. The risk assessment by using FIS shown that the safety and security risk for the CPS is significant and calculated as medium level. Hence, the risk factors that are considered in calculating the overall risk for a CPS need to be immediately addressed and mitigated.

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“…Among them are mechanical anomalies and security vulnerabilities that can seriously compromise the reliability and efficiency of the entire system [14]. These problems can have a series of serious consequences, including productivity degradation, data leakage, and in extreme cases, loss of life [15,16]. Therefore, the main objective of this study is to develop a robust algorithm that can quickly and accurately detect mechanical anomalies and security vulnerabilities in building automation systems using the BACnet protocol.…”

Section: Introductionmentioning

confidence: 99%

Advancing Fault Detection in Building Automation Systems through Deep Learning

Choi,

Lewe

2024

Buildings

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This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine learning algorithms and outlier detection techniques, this model is capable of monitoring and learning anomaly patterns in real-time. The primary aim of this paper is to enhance the reliability and efficiency of buildings and industrial facilities, offering solutions applicable across diverse industries such as manufacturing, energy management, and smart grids. Our findings reveal that the developed algorithm detects mechanical faults and security vulnerabilities with an accuracy of 96%, indicating its potential to significantly improve the safety and efficiency of building automation systems. However, the full validation of the algorithm’s performance in various conditions and environments remains a challenge, and future research will explore methodologies to address these issues and further enhance performance. This research is expected to play a vital role in numerous fields, including productivity improvement, data security, and the prevention of human casualties.

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Analysis of safety and security challenges and opportunities related to cyber-physical systems

Cited by 27 publications

References 195 publications

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

SLAM in XR: a bibliometric analysis of its application in virtual, augmented, and mixed reality

Security and Safety in Cyber-Physical System (CPS): An Inclusive Threat Model

Advancing Fault Detection in Building Automation Systems through Deep Learning

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