paper-with-me

Papers

Soft Computing Techniques for Dependable Cyber-Physical Systems

2018-01-25 · Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas

Cyber-Physical Systems (CPS) allow us to manipulate objects in the physical world by providing a communication bridge between computation and actuation elements. In the current scheme of things, this sought-after control is marred by limitations inherent in the underlying communication network(s) as well as by the uncertainty found in the physical world. These limitations hamper fine-grained control of elements that may be separated by large-scale distances. In this regard, soft computing is an emerging paradigm that can help to overcome the vulnerabilities, and unreliability of CPS by using techniques including fuzzy systems, neural network, evolutionary computation, probabilistic reasoning and rough sets. In this paper, we present a comprehensive contemporary review of soft computing techniques for CPS dependability modeling, analysis, and improvement. This paper provides an overview of CPS applications, explores the foundations of dependability engineering, and highlights the potential role of soft computing techniques for CPS dependability with various case studies, while identifying common pitfalls and future directions. In addition, this paper provides a comprehensive survey on the use of various soft computing techniques for making CPS dependable.

📄 PDF Abstract BibTeX arXiv:1801.10472

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Falsification of Cyber-Physical Systems Using Deep Reinforcement Learning

2018-05-01 · Takumi Akazaki, Shuang Liu, Yoriyuki Yamagata, Yihai Duan 외

With the rapid development of software and distributed computing, Cyber-Physical Systems (CPS) are widely adopted in many application areas, e.g., smart grid, autonomous automobile. It is difficult to detect defects in C…

Deep Reinforcement LearningDistributed Computingreinforcement-learningReinforcement Learning+1

Enhanced FIWARE-Based Architecture for Cyberphysical Systems With Tiny Machine Learning and Machine Learning Operations: A Case Study on Urban Mobility Systems

2024-11-16 · Javier Conde, Andrés Munoz-Arcentales, Álvaro Alonso, Joaquín Salvachúa 외

The rise of AI and the Internet of Things is accelerating the digital transformation of society. Mobility computing presents specific barriers due to its real-time requirements, decentralization, and connectivity through…

Edge-computingManagement

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

2024-11-17 · Danial Abshari, Peiran Shi, Chenglong Fu, Meera Sridhar 외

Cyber-Physical Systems (CPS) are vulnerable to cyber-physical attacks that violate physical laws. While invariant-based anomaly detection is effective, existing methods are limited: data-driven approaches lack semantic c…

Anomaly DetectionHallucinationRAGRetrieval-augmented Generation

A Formal Resilience Framework for Cyber-Physical Embodied Systems under Device-Level Cyberattacks

2026-06-15 · Alberto Giaretta arxiv

In cyber-physical systems (CPSs), fault tolerance is traditionally achieved by analysing sensor and actuator outputs, detecting progressive drift or sudden failures, and initiating suitable tolerance mechanisms. Reasonab…

Robust Perception Architecture Design for Automotive Cyber-Physical Systems

2022-05-17 · Joydeep Dey, Sudeep Pasricha

In emerging automotive cyber-physical systems (CPS), accurate environmental perception is critical to achieving safety and performance goals. Enabling robust perception for vehicles requires solving multiple complex prob…

object-detectionObject DetectionSensor Fusion