WINDS: A Wavelet-Based Intrusion Detection System for Controller Area Network (CAN)
暂无分享,去创建一个
[1] Xiaochun Cheng,et al. A Distributed Anomaly Detection System for In-Vehicle Network Using HTM , 2018, IEEE Access.
[2] Bogdan Groza,et al. DoS Attacks on Controller Area Networks by Fault Injections from the Software Layer , 2017, ARES.
[3] Stefano Zanero,et al. A Stealth, Selective, Link-Layer Denial-of-Service Attack Against Automotive Networks , 2017, DIMVA.
[4] Christian E. Schaerer,et al. Anomaly-based Techniques for Web Attacks Detection , 2012 .
[5] Naim Asaj,et al. Entropy-based anomaly detection for in-vehicle networks , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).
[6] Kang G. Shin,et al. Fingerprinting Electronic Control Units for Vehicle Intrusion Detection , 2016, USENIX Security Symposium.
[7] Bogdan Groza,et al. Security Solutions for the Controller Area Network: Bringing Authentication to In-Vehicle Networks , 2018, IEEE Vehicular Technology Magazine.
[8] Nandi O. Leslie,et al. Estimating Attack Risk of Network Activities in Temporal Domain: A Wavelet Transform Approach , 2020, 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).
[9] Aditya Mathur,et al. Using Datasets from Industrial Control Systems for Cyber Security Research and Education , 2019, CRITIS.
[10] Bogdan Groza,et al. Efficient Intrusion Detection With Bloom Filtering in Controller Area Networks , 2019, IEEE Transactions on Information Forensics and Security.
[11] Gedare Bloom,et al. Automotive Intrusion Detection Based on Constant CAN Message Frequencies Across Vehicle Driving Modes , 2019, AutoSec@CODASPY.
[12] G. Peyré. Mathematical Foundations of Data Sciences , 2018 .
[13] D.K. Nilsson,et al. An approach to specification-based attack detection for in-vehicle networks , 2008, 2008 IEEE Intelligent Vehicles Symposium.
[14] Huy Kang Kim,et al. GIDS: GAN based Intrusion Detection System for In-Vehicle Network , 2018, 2018 16th Annual Conference on Privacy, Security and Trust (PST).
[15] Jeremy Bryans,et al. Detection of Automotive CAN Cyber-Attacks by Identifying Packet Timing Anomalies in Time Windows , 2018, 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W).
[16] Keqin Li,et al. Sliding Window Optimized Information Entropy Analysis Method for Intrusion Detection on In-Vehicle Networks , 2018, IEEE Access.
[17] D. Rincon,et al. Wavelet transforms and change-point detection algorithms for tracking network traffic fractality , 2006, 2006 2nd Conference on Next Generation Internet Design and Engineering, 2006. NGI '06..
[18] Tomas Olovsson,et al. In-Vehicle CAN Message Authentication: An Evaluation Based on Industrial Criteria , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).
[19] Vincent Nicomette,et al. A language-based intrusion detection approach for automotive embedded networks , 2015, Int. J. Embed. Syst..
[20] Jaein Kim,et al. Fuzzing CAN Packets into Automobiles , 2015, 2015 IEEE 29th International Conference on Advanced Information Networking and Applications.
[21] Je-Won Kang,et al. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security , 2016, PloS one.
[22] Nathalie Japkowicz,et al. Frequency-based anomaly detection for the automotive CAN bus , 2015, 2015 World Congress on Industrial Control Systems Security (WCICSS).
[23] Huy Kang Kim,et al. Intrusion detection system based on the analysis of time intervals of CAN messages for in-vehicle network , 2016, 2016 International Conference on Information Networking (ICOIN).
[24] Jiyoung Woo,et al. In-vehicle network intrusion detection using deep convolutional neural network , 2020, Veh. Commun..
[25] Hiroshi Ueda,et al. Anomaly-Based Intrusion Detection Using the Density Estimation of Reception Cycle Periods for In-Vehicle Networks , 2018 .
[26] Matthew Spicer,et al. Intrusion Detection System for Electronic Communication Buses: A New Approach , 2018 .
[27] Michele Colajanni,et al. Evaluation of anomaly detection for in-vehicle networks through information-theoretic algorithms , 2016, 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI).
[28] Huy Kang Kim,et al. OTIDS: A Novel Intrusion Detection System for In-vehicle Network by Using Remote Frame , 2017, 2017 15th Annual Conference on Privacy, Security and Trust (PST).
[29] Nathalie Japkowicz,et al. Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks , 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).
[30] Jerry den Hartog,et al. Evaluation Framework for Network Intrusion Detection Systems for In-Vehicle CAN , 2019, 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE).
[31] Felix C. Freiling,et al. A structured approach to anomaly detection for in-vehicle networks , 2010, 2010 Sixth International Conference on Information Assurance and Security.
[32] Reinhard German,et al. Delay Bounds for CAN Communication in Automotive Applications , 2008, MMB.
[33] Gedare Bloom,et al. SAIDuCANT: Specification-Based Automotive Intrusion Detection Using Controller Area Network (CAN) Timing , 2020, IEEE Transactions on Vehicular Technology.
[34] Tobias Hoppe,et al. Exemplary Automotive Attack Scenarios : Trojan Horses for Electronic Throttle Control System ( ETC ) and Replay Attacks on the Power Window System , 2007 .
[35] Sibylle B. Fröschle,et al. Analyzing the Capabilities of the CAN Attacker , 2017, ESORICS.
[36] Mohamed Hamdi,et al. Detecting Denial-of-Service attacks using the wavelet transform , 2007, Comput. Commun..
[37] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .