Enhancing collaborative intrusion detection via disagreement-based semi-supervised learning in IoT environments
暂无分享,去创建一个
Man Ho Au | Weizhi Meng | Wenjuan Li | M. Au | Wenjuan Li | W. Meng
[1] Rayid Ghani,et al. Analyzing the effectiveness and applicability of co-training , 2000, CIKM '00.
[2] Horace Ho-Shing Ip,et al. PMFA: Toward Passive Message Fingerprint Attacks on Challenge-Based Collaborative Intrusion Detection Networks , 2016, NSS.
[3] Tao Xiang,et al. A training-integrity privacy-preserving federated learning scheme with trusted execution environment , 2020, Inf. Sci..
[4] Tsuhan Chen,et al. Semi-supervised co-training and active learning based approach for multi-view intrusion detection , 2009, SAC '09.
[5] Wenjuan Li,et al. Improving the Performance of Neural Networks with Random Forest in Detecting Network Intrusions , 2013, ISNN.
[6] Rich Caruana,et al. Ensemble selection from libraries of models , 2004, ICML.
[7] Yan Li,et al. Design and Evaluation of Advanced Collusion Attacks on Collaborative Intrusion Detection Networks in Practice , 2016, 2016 IEEE Trustcom/BigDataSE/ISPA.
[8] Nahid Shahmehri,et al. A Trust-Aware, P2P-Based Overlay for Intrusion Detection , 2006, 17th International Workshop on Database and Expert Systems Applications (DEXA'06).
[9] Martin Roesch,et al. Snort - Lightweight Intrusion Detection for Networks , 1999 .
[10] David J. Miller,et al. A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data , 1996, NIPS.
[11] Wenjuan Li,et al. SOOA: Exploring Special On-Off Attacks on Challenge-Based Collaborative Intrusion Detection Networks , 2017, GPC.
[12] Man Ho Au,et al. Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling , 2017, IFIPTM.
[13] David A. Landgrebe,et al. The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon , 1994, IEEE Trans. Geosci. Remote. Sens..
[14] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[15] Mikhail Belkin,et al. Semi-Supervised Learning on Riemannian Manifolds , 2004, Machine Learning.
[16] Stefan Axelsson,et al. The base-rate fallacy and the difficulty of intrusion detection , 2000, TSEC.
[17] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[18] Hervé Debar,et al. A serial combination of anomaly and misuse IDSes applied to HTTP traffic , 2004, 20th Annual Computer Security Applications Conference.
[19] Hakim Weatherspoon,et al. Netbait: a Distributed Worm Detection Service , 2003 .
[20] Raouf Boutaba,et al. Trust Management for Host-Based Collaborative Intrusion Detection , 2008, DSOM.
[21] Avrim Blum,et al. Learning from Labeled and Unlabeled Data using Graph Mincuts , 2001, ICML.
[22] Wenjuan Li,et al. Design of intelligent KNN-based alarm filter using knowledge-based alert verification in intrusion detection , 2015, Secur. Commun. Networks.
[23] Wenjuan Li,et al. Design of Intrusion Sensitivity-Based Trust Management Model for Collaborative Intrusion Detection Networks , 2014, IFIPTM.
[24] Zhi-Hua Zhou,et al. Unlabeled Data and Multiple Views , 2011, PSL.
[25] John McHugh,et al. Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory , 2000, TSEC.
[26] Marius Kloft,et al. Active learning for network intrusion detection , 2009, AISec '09.
[27] Lam-for Kwok,et al. Enhancing False Alarm Reduction Using Voted Ensemble Selection in Intrusion Detection , 2013, Int. J. Comput. Intell. Syst..
[28] Tadeusz Pietraszek,et al. Using Adaptive Alert Classification to Reduce False Positives in Intrusion Detection , 2004, RAID.
[29] Jun Zhang,et al. JFCGuard: Detecting juice filming charging attack via processor usage analysis on smartphones , 2017, Comput. Secur..
[30] Mahmoud Ammar,et al. Journal of Information Security and Applications , 2022 .
[31] Karen A. Scarfone,et al. Guide to Intrusion Detection and Prevention Systems (IDPS) , 2007 .
[32] Scott Shenker,et al. The Architecture of PIER: an Internet-Scale Query Processor , 2005, CIDR.
[33] Lam-For Kwok,et al. Adaptive False Alarm Filter Using Machine Learning in Intrusion Detection , 2011 .
[34] Giovanni Vigna,et al. NetSTAT: a network-based intrusion detection approach , 1998, Proceedings 14th Annual Computer Security Applications Conference (Cat. No.98EX217).
[35] Terran Lane,et al. A Decision-Theoritic, Semi-Supervised Model for Intrusion Detection , 2006 .
[36] Kim-Kwang Raymond Choo,et al. A bayesian inference-based detection mechanism to defend medical smartphone networks against insider attacks , 2017, J. Netw. Comput. Appl..
[37] Byung-Seo Kim,et al. Internet of Things (IoT) Operating Systems Support, Networking Technologies, Applications, and Challenges: A Comparative Review , 2018, IEEE Communications Surveys & Tutorials.
[38] Yingjie Tian,et al. Semi-supervised learning methods for network intrusion detection , 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.
[39] Yuh-Jye Lee,et al. Semi-supervised Learning for False Alarm Reduction , 2010, ICDM.
[40] Heejo Lee,et al. Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.
[41] Jun Zhang,et al. Detecting and Preventing Cyber Insider Threats: A Survey , 2018, IEEE Communications Surveys & Tutorials.
[42] Avrim Blum,et al. The Bottleneck , 2021, Monopsony Capitalism.
[43] R.K. Cunningham,et al. Evaluating intrusion detection systems: the 1998 DARPA off-line intrusion detection evaluation , 2000, Proceedings DARPA Information Survivability Conference and Exposition. DISCEX'00.
[44] Zhi-Hua Zhou,et al. Tri-training: exploiting unlabeled data using three classifiers , 2005, IEEE Transactions on Knowledge and Data Engineering.
[45] Qing-Long Han,et al. Data-Driven Cyber Security in Perspective—Intelligent Traffic Analysis , 2020, IEEE Transactions on Cybernetics.
[46] Wenjuan Li,et al. Evaluation of Detecting Malicious Nodes Using Bayesian Model in Wireless Intrusion Detection , 2013, NSS.
[47] Lam-for Kwok,et al. Intrusion Detection Using Disagreement-Based Semi-supervised Learning: Detection Enhancement and False Alarm Reduction , 2012, CSS.
[48] Wenjuan Li,et al. Enhancing Trust Evaluation Using Intrusion Sensitivity in Collaborative Intrusion Detection Networks: Feasibility and Challenges , 2013, 2013 Ninth International Conference on Computational Intelligence and Security.
[49] Erland Jonsson,et al. Using active learning in intrusion detection , 2004, Proceedings. 17th IEEE Computer Security Foundations Workshop, 2004..
[50] Saurabh Bagchi,et al. Collaborative intrusion detection system (CIDS): a framework for accurate and efficient IDS , 2003, 19th Annual Computer Security Applications Conference, 2003. Proceedings..
[51] Anup K. Ghosh,et al. Detecting anomalous and unknown intrusions against programs , 1998, Proceedings 14th Annual Computer Security Applications Conference (Cat. No.98EX217).
[52] Jiaqi Zheng,et al. MAN: Mutual Attention Neural Networks Model for Aspect-Level Sentiment Classification in SIoT , 2020, IEEE Internet of Things Journal.
[53] Salvatore J. Stolfo,et al. A data mining framework for building intrusion detection models , 1999, Proceedings of the 1999 IEEE Symposium on Security and Privacy (Cat. No.99CB36344).
[54] Zhi-Hua Zhou,et al. Semi-supervised learning by disagreement , 2010, Knowledge and Information Systems.
[55] Yan Chen,et al. Towards scalable and robust distributed intrusion alert fusion with good load balancing , 2006, LSAD '06.
[56] Vijay Varadharajan,et al. A Dynamic Trust Establishment and Management Framework for Wireless Sensor Networks , 2010, 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.
[57] Manas Ranjan Patra,et al. Semi-Naïve Bayesian Method for Network Intrusion Detection System , 2009, ICONIP.
[58] Ji Guo,et al. A New Trust Management Framework for Detecting Malicious and Selfish Behaviour for Mobile Ad Hoc Networks , 2011, 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications.
[59] Horace Ho-Shing Ip,et al. Enhancing collaborative intrusion detection networks against insider attacks using supervised intrusion sensitivity-based trust management model , 2017, J. Netw. Comput. Appl..
[60] Minghua Zhang,et al. A New Method for Filtering IDS False Positives with Semi-supervised Classification , 2012, ICIC.
[61] Vern Paxson,et al. Outside the Closed World: On Using Machine Learning for Network Intrusion Detection , 2010, 2010 IEEE Symposium on Security and Privacy.