Dynamic event-triggered fault detection for rotary steerable systems with unknown time-varying noise covariances

Liu, Shiyang; Gao, Ming; Feng, Yang; Sheng, Li

doi:10.1016/j.isatra.2023.08.018

Cited by 5 publications

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the covariance between certain nodes exceeds the range of

, an anomaly is considered to have occurred, potentially indicating a network attack. For example, in reference [ 34 ], a residual and an evaluation function were established for fault detection. By applying the covariance linear learning algorithm, Albalawi et al embedded feature selection to extract attributes highly correlated with IoT intrusions.…”

Section: Attack Detectionmentioning

confidence: 99%

Security Control of Cyber–Physical Systems under Cyber Attacks: A Survey

Xing,

Shen

2024

Sensors

View full text Add to dashboard Cite

Cyber–physical systems (CPSs), which combine computer science, control systems, and physical elements, have become essential in modern industrial and societal contexts. However, their extensive integration presents increasing security challenges, particularly due to recurring cyber attacks. Therefore, it is crucial to explore CPS security control. In this review, we systematically examine the prevalent cyber attacks affecting CPSs, such as denial of service, false data injection, and replay attacks, explaining their impacts on CPSs’ operation and integrity, as well as summarizing classic attack detection methods. Regarding CPSs’ security control approaches, we comprehensively outline protective strategies and technologies, including event-triggered control, switching control, predictive control, and optimal control. These approaches aim to effectively counter various cyber threats and strengthen CPSs’ security and resilience. Lastly, we anticipate future advancements in CPS security control, envisioning strategies to address emerging cyber risks and innovations in intelligent security control techniques.

show abstract

“…If the covariance between certain nodes exceeds the range of

Section: Attack Detectionmentioning

confidence: 99%