Cyber-Physical Systems Security -- A Survey

Humayed, Abdulmalik; Lin, Jingqiang; Li, Fengjun; Luo, Bo

doi:10.48550/arxiv.1701.04525

Cited by 7 publications

(5 citation statements)

References 58 publications

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“…The protocol validates the transaction's legitimacy, eliminating the requirement for a trusted third party to do so. When the transaction is finished [15] Mining is the process of adding the records of a transaction to the ledger of prior transactions. The rest of the network's nodes must verify the proof of work.…”

Section: Components Of Blockchain: -mentioning

confidence: 99%

Review on Smart City Iot Security Using Blockchain

Dhanju¹,

Tyagi²,

Kumar³

et al. 2022

IJEAST

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Blockchain has grown in popularity as a crypto currency in recent years. It can also be used to secure IoT devices, helping to keep personal information private. Cities are becoming smarter these days thanks to IT and IoT devices, yet the data they generate is insecure due to IoT devices' limited processing capability. This is where blockchain comes in to secure the IoT data it generates. Blockchain and smart cities are still in their infancy, thus further study is required to integrate them. This study examines the challenges of implementing IoT security in smart cities using blockchain.

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Section: Components Of Blockchain: -mentioning

confidence: 99%

Review on Smart City Iot Security Using Blockchain

Dhanju¹,

Tyagi²,

Kumar³

et al. 2022

IJEAST

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show abstract

“…Because of that, the attack can be easily detected by control-theoretic fault detection techniques [36]. Authors have systematized existing CPS security research analyzing the taxonomy of threats, vulnerabilities, and attacks from the CPS components perspective, with a special focus on cyber components [37] and cyber adversaries [8].…”

Section: Adversary Modelsmentioning

confidence: 99%

Cyber-Resilience Evaluation of Cyber-Physical Systems

Segovia

Rubio‐Hernan

Cavalli

et al. 2020

2020 IEEE 19th International Symposium on Network Computing and Applications (NCA)

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Concerns for the resilience of Cyber-Physical Systems (CPS) in critical infrastructure are growing. CPS integrate sensing, computation, control and networking into physical objects and mission-critical services, connecting traditional infrastructure to internet technologies.While this integration increases service efficiency, it has to face the possibility of new threats posed by the new functionalities. This leads to cyber-threats, such as denial-of-service, modification of data, information leakage, spreading of malware, and many others.Cyber-resilience refers to the ability of a CPS to prepare, absorb, recover, and adapt to the adverse effects associated with cyber-threats, e.g., physical degradation of the CPS performance resulting from a cyber-attack. Cyber-resilience aims at ensuring CPS survival, by keeping the core functionalities of the CPS in case of extreme events. The literature on cyber-resilience is rapidly increasing, leading to a broad variety of research works addressing this new topic. In this article, we create a systematization of knowledge about existing scientific efforts of making CPS cyber-resilient. We systematically survey recent literature addressing cyber-resilience with a focus on techniques that may be used on CPS. We first provide preliminaries and background on CPS and threats, and subsequently survey state-of-the-art approaches that have been proposed by recent research work applicable to CPS. In particular, we aim at differentiating research work from traditional risk management approaches, based on the general acceptance that it is unfeasible to prevent and mitigate all possible risks threatening a CPS. We also discuss questions and research challenges, with a focus on the practical aspects of cyber-resilience, such as the use of metrics and evaluation methods, as well as testing and validation environments.

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“…In the cyber-physical systems (CPS) security literature, recent studies [15], [26], [36]- [39], list possible cyber-attacks and discuss their detection and mitigation techniques. In these studies, abstract cyber-physical models for smart cars are also presented.…”

Section: B V2i Cyber-attacks In a CV Environmentmentioning

confidence: 99%

Change Point Models for Real-time Cyber Attack Detection in Connected Vehicle Environment

Comert¹,

Rahman²,

Islam³

et al. 2020

Preprint

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Connected vehicle (CV) systems are cognizant of potential cyber attacks because of increasing connectivity between its different components such as vehicles, roadside infrastructure, and traffic management centers. However, it is a challenge to detect security threats in real-time and develop appropriate or effective countermeasures for a CV system because of the dynamic behavior of such attacks, high computational power requirement, and a historical data requirement for training detection models. To address these challenges, statistical models, especially change point models, have potentials for real-time anomaly detections. Thus, the objective of this study is to investigate the efficacy of two change point models, Expectation Maximization (EM) and two forms of Cumulative Summation (CUSUM) algorithms (i.e., typical and adaptive), for real-time V2I cyber attack detection in a CV Environment. To prove the efficacy of these models, we evaluated these two models for three different type of cyber attack, denial of service (DOS), impersonation, and false information, using basic safety messages (BSMs) generated from CVs through simulation. Results from numerical analysis revealed that EM, CUSUM, and adaptive CUSUM could detect these cyber attacks, DOS, impersonation, and false information, with an accuracy of (99%, 100%, 100%), (98%, 100%, 100%), and (100%, 98%, 100%) respectively.

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Cyber-Physical Systems Security -- A Survey

Cited by 7 publications

References 58 publications

Review on Smart City Iot Security Using Blockchain

Review on Smart City Iot Security Using Blockchain

Cyber-Resilience Evaluation of Cyber-Physical Systems

Change Point Models for Real-time Cyber Attack Detection in Connected Vehicle Environment

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