相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Computer Science, Hardware & Architecture
Chuan Sheng et al.
Summary: This paper proposes a cyber-physical model for detecting intrusions and evaluating risk levels in SCADA systems, with comprehensive performance evaluation on public SCADA network datasets showing that the proposed method outperforms existing methods.
Article
Computer Science, Information Systems
Xiaoxue Liu et al.
Summary: This paper presents a unified methodology for quantitatively and automatically analyzing cyber-physical attacks on ICSs. By defining the weighted colored Petri net and basic cyber-physical attack models, as well as proposing a method to calculate weights in attack models, the study shows stable weights and establishes threat propagation matrix and security state vector. Additionally, a cyber-physical attack path analysis algorithm is designed to discover possible attack paths with specific attack losses.
COMPUTERS & SECURITY
(2021)
Article
Engineering, Electrical & Electronic
Hossein Darvishi et al.
Summary: This article introduces a machine-learning-based sensor validation architecture that uses neural network estimators and a classifier to detect and isolate faulty sensors for reliable digital twins. Results show that the proposed architecture performs well under different real-world datasets and synthetically-generated faults.
IEEE SENSORS JOURNAL
(2021)
Article
Automation & Control Systems
Bilal Hussain et al.
Summary: The article proposes a comprehensive framework utilizing deep convolutional neural networks and real network data for early detection of DDoS attacks orchestrated by botnets, achieving over 91% accuracy in detecting normal and under attack cells.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Green & Sustainable Science & Technology
Kai Ding et al.
Summary: Manufacturers collaborate with equipment providers and customers to produce customer-centered individualized products, using new technologies such as Cyber-Physical System (CPS) and advanced business models such as Product-Service System (PSS). A Cyber-Physical Production Monitoring Service System (CPPMSS) is proposed to support service-oriented collaborative manufacturing operations, which can satisfy the collaborative manufacturing operations among different stakeholders in the mass individualization environment.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Automation & Control Systems
Mei Zhou et al.
Summary: Replay attack detection in industrial CPSs, especially using data-based methods, has not been well-studied. A permutation entropy based detection scheme is proposed to distinguish historical measurements and current measurements in replay attacks, showing effectiveness in testing. The method utilizes support vector data description (SVDD) and wavelet analysis to classify and denoise measurements, demonstrating accurate detection of replay attacks in a semi-physical simulation testbed.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Mathematical & Computational Biology
Nhat-Duc Hoang
Summary: The study aims to develop neural computing models for automatic impervious surface area detection at a regional scale, using advanced optimizers. Experimental results on remotely sensed images from the Sentinel-2 satellite over Da Nang city in Vietnam demonstrate that the Nadam optimizer-based neural computing model achieved the most desired predictive accuracy.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2021)
Article
Computer Science, Information Systems
Robertas Damasevicius et al.
Summary: The paper proposes an ensemble classification-based methodology for malware detection, with the first-stage classification performed by a stacked ensemble of dense and convolutional neural networks, and the final stage classification performed by a meta-learner. Experimental results show that an ensemble of five dense and CNN neural networks, along with the ExtraTrees classifier as a meta-learner, achieves the best performance.
Article
Computer Science, Hardware & Architecture
Soumyadeep Thakur et al.
Summary: This paper proposes a model that extracts useful features from given features and uses a deep learning algorithm to classify intrusions. Specific domains and generic network intrusions typically require different features for classification. The proposed method achieves new benchmark results on the CICIDS2017 dataset.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Myeong-Hun Jeong et al.
Summary: Movement analytics and mobility insights are essential in urban planning and transportation management. In this study, a GRU neural network is used to predict highway speed based on digital tachograph data, outperforming other models in terms of prediction accuracy with lower computational cost. This approach has potential applications in traffic prediction and intelligent transportation systems.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Marcin Wozniak et al.
Summary: The security of networking in cyber-physical systems is crucial, and this article proposes a solution based on a deep learning model for analyzing network traffic. The model efficiently evaluates information and makes security decisions, achieving over 99% accuracy even with a reduced number of features evaluated.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Xiaokang Zhou et al.
Summary: This article proposes a few-shot learning model with Siamese convolutional neural network (FSL-SCNN) to enhance the accuracy of intelligent anomaly detection in industrial cyber-physical systems by alleviating over-fitting issues. Experimental results demonstrate that the proposed model can significantly improve the false alarm rate (FAR) and F1 scores in detecting intrusion signals for industrial CPS security protection.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Beibei Li et al.
Summary: The study introduces a novel federated deep learning scheme named DeepFed for detecting cyber threats against industrial CPSs. By designing a new intrusion detection model and federated learning framework, the research successfully achieves secure detection of various cyber threats.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Theory & Methods
Gia Nhu Nguyen et al.
Summary: This paper proposes a secure intrusion detection with blockchain-based data transmission and classification model for CPS in healthcare sector. The model utilizes deep belief network (DBN) model for intrusion detection and multiple share creation (MSC) model for privacy and security.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2021)
Article
Computer Science, Information Systems
Amir Namavar Jahromi et al.
Summary: The article introduces a two-level ensemble attack detection and attribution framework designed for cyber-physical systems, which outperforms other competing methods.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Abdullah Alharbi et al.
Summary: A novel method for effectively detecting botnet attacks in the IoT environment was proposed in this study, achieving efficient detection and classification through the use of bat algorithm and neural networks. Experimental results demonstrated the superior performance of the LGBA-NN algorithm in multi-class botnet attack detection.
Article
Computer Science, Information Systems
Nojood O. Aljehane
Summary: Cyber physical systems (CPS) are complex systems composed of networked computation and physical elements like sensors and actuators, crucial for daily human life and future smart devices. However, security threats related to CPS utilization are a global issue, prompting the research focus on developing a secure and effective CPS. An intrusion detection system (IDS) based on deep learning called PT-DSAE is proposed to protect CPS by detecting anomalies and optimizing parameters through experiments with sensor data. The experimental results demonstrate the superior performance of the PT-DSAE model compared to existing methods.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Social Sciences, Interdisciplinary
Eirini Anthi et al.
Summary: This article introduces a three-tiered intrusion detection system for industrial control systems networks, which can effectively distinguish malicious activities and classify attack types, improving the response speed to network security incidents.
JOURNAL OF CYBERSECURITY
(2021)
Article
Mathematical & Computational Biology
Huang Chen et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2020)
Article
Engineering, Marine
Zhen Zhang et al.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2020)
Article
Computer Science, Artificial Intelligence
Jinping Liu et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Article
Computer Science, Information Systems
V Porkodi et al.
Article
Ilayaraja Murugan et al.
Recent Advances in Computer Science and Communications
(2019)
Article
Computer Science, Artificial Intelligence
Derui Ding et al.
