Reconstructing Classification to Enhance Machine-Learning Based Network Intrusion Detection by Embracing Ambiguity

[1]  Terran Lane,et al.  An Application of Machine Learning to Anomaly Detection , 1999 .

[2]  Sumeet Dua,et al.  Data Mining and Machine Learning in Cybersecurity , 2011 .

[3]  Christopher Krügel,et al.  Using Decision Trees to Improve Signature-Based Intrusion Detection , 2003, RAID.

[4]  Tom M. Mitchell,et al.  Machine Learning and Data Mining , 2012 .

[5]  Tai-Myoung Chung,et al.  Effective Value of Decision Tree with KDD 99 Intrusion Detection Datasets for Intrusion Detection System , 2008, 2008 10th International Conference on Advanced Communication Technology.

[6]  J. Friedman.  Greedy function approximation: A gradient boosting machine. , 2001 .

[7]  Gerhard Widmer,et al.  Learning in the Presence of Concept Drift and Hidden Contexts , 1996, Machine Learning.

[8]  Aiko Pras,et al.  An Overview of IP Flow-Based Intrusion Detection , 2010, IEEE Communications Surveys & Tutorials.

[9]  Vern Paxson,et al.  Bro: a system for detecting network intruders in real-time , 1998, Comput. Networks.

[10]  L. Breiman.  OUT-OF-BAG ESTIMATION , 1996 .

[11]  Yi Peng,et al.  Network intrusion detection , 1994, IEEE Netw..

[12]  Gabriel Maciá-Fernández,et al.  Anomaly-based network intrusion detection: Techniques, systems and challenges , 2009, Comput. Secur..

[13]  Lior Rokach,et al.  Ensemble-based classifiers , 2010, Artificial Intelligence Review.

[14]  Gary McGraw,et al.  Detecting Anomalous and Unknown Intrusions against Programs in Real-Time. , 1997 .

[15]  Jugal K. Kalita,et al.  Network Anomaly Detection: Methods, Systems and Tools , 2014, IEEE Communications Surveys & Tutorials.

[16]  Wolfgang Banzhaf,et al.  The use of computational intelligence in intrusion detection systems: A review , 2010, Appl. Soft Comput..

[17]  Shailendra Sahu,et al.  Network intrusion detection system using J48 Decision Tree , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[18]  Hirofumi Yamaki,et al.  Unknown Attacks Detection Using Feature Extraction from Anomaly-Based IDS Alerts , 2012, 2012 IEEE/IPSJ 12th International Symposium on Applications and the Internet.

[19]  Fabio Roli,et al.  Fusion of multiple classifiers for intrusion detection in computer networks , 2003, Pattern Recognit. Lett..

[20]  J. Friedman.  Stochastic gradient boosting , 2002 .

[21]  Carla E. Brodley,et al.  Approaches to Online Learning and Concept Drift for User Identification in Computer Security , 1998, KDD.

[22]  Dorothy E. Denning,et al.  An Intrusion-Detection Model , 1987, IEEE Transactions on Software Engineering.

[23]  Oliver W. W. Yang,et al.  Contention avoidance and resolution schemes in bufferless all-optical packet-switched networks: a survey , 2008, IEEE Communications Surveys & Tutorials.

[24]  Anup K. Ghosh,et al.  Detecting anomalous and unknown intrusions against programs , 1998, Proceedings 14th Annual Computer Security Applications Conference (Cat. No.98EX217).

[25]  Erhan Guven,et al.  A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection , 2016, IEEE Communications Surveys & Tutorials.

[26]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[27]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[28]  Mohammad Zulkernine,et al.  Random-Forests-Based Network Intrusion Detection Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[29]  James Cannady,et al.  Artificial Neural Networks for Misuse Detection , 1998 .

[30]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[31]  Grenville J. Armitage,et al.  A survey of techniques for internet traffic classification using machine learning , 2008, IEEE Communications Surveys & Tutorials.

[32]  Vern Paxson,et al.  Outside the Closed World: On Using Machine Learning for Network Intrusion Detection , 2010, 2010 IEEE Symposium on Security and Privacy.

[33]  Zied Elouedi,et al.  Naive Bayes vs decision trees in intrusion detection systems , 2004, SAC '04.

[34]  Sara Matzner,et al.  An application of machine learning to network intrusion detection , 1999, Proceedings 15th Annual Computer Security Applications Conference (ACSAC'99).

[35]  R. Polikar,et al.  Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.

[36]  Martin Roesch,et al.  Snort - Lightweight Intrusion Detection for Networks , 1999 .

[37]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[38]  Sandeep Kumar,et al.  A Software Architecture to Support Misuse Intrusion Detection , 1995 .

[39]  Richard A. Kemmerer,et al.  State Transition Analysis: A Rule-Based Intrusion Detection Approach , 1995, IEEE Trans. Software Eng..

[40]  Manas Ranjan Patra,et al.  NETWORK INTRUSION DETECTION USING NAÏVE BAYES , 2007 .

[41]  Hiroki Takakura,et al.  Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation , 2011, BADGERS '11.

[42]  Todd L. Heberlein,et al.  Network intrusion detection , 1994, IEEE Network.