An Ensemble Deep Learning-Based Cyber-Attack Detection in Industrial Control System
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Hadis Karimipour | Reza M. Parizi | Ali Dehghantanha | Abdulrahman Al-Abassi | R. Parizi | A. Dehghantanha | H. Karimipour | Abdulrahman Al-Abassi
[1] Scott A. Wallace,et al. Fast Sequence Component Analysis for Attack Detection in Synchrophasor Networks , 2015, ArXiv.
[2] Avi Ostfeld,et al. Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks , 2018, Journal of Water Resources Planning and Management.
[3] Dhananjay Kumar,et al. An efficient system for anomaly detection using deep learning classifier , 2017, Signal Image Video Process..
[4] Louis Wehenkel. Machine-Learning Approaches to Power-System Security Assessment , 1997, IEEE Expert.
[5] Tingting Li,et al. Multi-level Anomaly Detection in Industrial Control Systems via Package Signatures and LSTM Networks , 2017, 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).
[6] Hadis Karimipour,et al. An improved two-hidden-layer extreme learning machine for malware hunting , 2020, Comput. Secur..
[7] Shing-Tung Yau,et al. Geometric Understanding of Deep Learning , 2018, ArXiv.
[8] D. Prince Winston,et al. An enhanced optimization based algorithm for intrusion detection in SCADA network , 2017, Comput. Secur..
[9] David Hutchison,et al. Evaluation of Anomaly Detection techniques for SCADA communication resilience , 2016, 2016 Resilience Week (RWS).
[10] Florian Skopik,et al. Combating advanced persistent threats: From network event correlation to incident detection , 2015, Comput. Secur..
[11] Henry Leung,et al. Relaxation-based anomaly detection in cyber-physical systems using ensemble kalman filter , 2019, IET Cyper-Phys. Syst.: Theory & Appl..
[12] Lav Gupta,et al. Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things , 2019, IEEE Internet of Things Journal.
[13] Igor Nai Fovino,et al. Modbus/DNP3 State-Based Intrusion Detection System , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.
[14] Ulf Lindqvist,et al. Using Model-based Intrusion Detection for SCADA Networks , 2006 .
[15] Hadis Karimipour,et al. Robust Massively Parallel Dynamic State Estimation of Power Systems Against Cyber-Attack , 2018, IEEE Access.
[16] Ali Dehghantanha,et al. Fuzzy pattern tree for edge malware detection and categorization in IoT , 2019, J. Syst. Archit..
[17] Ali Dehghantanha,et al. A survey on internet of things security: Requirements, challenges, and solutions , 2019, Internet Things.
[18] Yuefei Zhu,et al. A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks , 2017, IEEE Access.
[19] Karen A. Scarfone,et al. Guide to Industrial Control Systems (ICS) Security , 2015 .
[20] Thomas H. Morris,et al. Developing a Hybrid Intrusion Detection System Using Data Mining for Power Systems , 2015, IEEE Transactions on Smart Grid.
[21] Qi Shi,et al. A Deep Learning Approach to Network Intrusion Detection , 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.
[22] Venkata Dinavahi,et al. Extended Kalman Filter-Based Parallel Dynamic State Estimation , 2016, IEEE Transactions on Smart Grid.
[23] H. Vincent Poor,et al. Machine Learning Methods for Attack Detection in the Smart Grid , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[24] Venkata Dinavahi,et al. Parallel Domain-Decomposition-Based Distributed State Estimation for Large-Scale Power Systems , 2016, IEEE Transactions on Industry Applications.
[25] Liang Chen,et al. Dynamic State Estimation of Generators Under Cyber Attacks , 2019, IEEE Access.
[26] Jamie B. Coble,et al. Multilayer Data-Driven Cyber-Attack Detection System for Industrial Control Systems Based on Network, System, and Process Data , 2019, IEEE Transactions on Industrial Informatics.
[27] Ali Dehghantanha,et al. Security Aspects of Internet of Things aided Smart Grids: a Bibliometric Survey , 2019, Internet Things.
[28] Leandros A. Maglaras,et al. Intrusion detection in SCADA systems using machine learning techniques , 2014, 2014 Science and Information Conference.
[29] Sakir Sezer,et al. Towards A Stateful Analysis Framework for Smart Grid Network Intrusion Detection , 2016, ICS-CSR.
[30] Qin Lin,et al. TABOR: A Graphical Model-based Approach for Anomaly Detection in Industrial Control Systems , 2018, AsiaCCS.
[31] Jun Sun,et al. Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning , 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).
[32] Asaf Shabtai,et al. Detecting Cyber Attacks in Industrial Control Systems Using Convolutional Neural Networks , 2018, CPS-SPC@CCS.
[33] Thiago Alves,et al. Embedding Encryption and Machine Learning Intrusion Prevention Systems on Programmable Logic Controllers , 2018, IEEE Embedded Systems Letters.
[34] Chunjie Zhou,et al. Anomaly Detection Based on Zone Partition for Security Protection of Industrial Cyber-Physical Systems , 2018, IEEE Transactions on Industrial Electronics.
[35] Panos J. Antsaklis,et al. Risk-Sensitive Control Under Markov Modulated Denial-of-Service (DoS) Attack Strategies , 2015, IEEE Transactions on Automatic Control.
[36] Dechang Pi,et al. HML-IDS: A Hybrid-Multilevel Anomaly Prediction Approach for Intrusion Detection in SCADA Systems , 2019, IEEE Access.
[37] Ali Dehghantanha,et al. A deep unsupervised representation learning approach for effective cyber-physical attack detection and identification on highly imbalanced data , 2019, CASCON.
[38] Ling Shi,et al. Optimal DoS Attack Scheduling in Wireless Networked Control System , 2016, IEEE Transactions on Control Systems Technology.
[39] Hans D. Schotten,et al. Anomaly-based Intrusion Detection in Industrial Data with SVM and Random Forests , 2019, 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM).
[40] Wen-Chiao Hsu,et al. Anomaly Detection for Industrial Control Systems Using K-Means and Convolutional Autoencoder , 2019, 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM).
[41] Dmitry Shalyga,et al. Anomaly Detection for Water Treatment System based on Neural Network with Automatic Architecture Optimization , 2018, ArXiv.
[42] Hadis Karimipour,et al. Cyber intrusion detection by combined feature selection algorithm , 2019, J. Inf. Secur. Appl..