Journal ArticleDOI
Anomaly-based network intrusion detection: Techniques, systems and challenges
Reads0
Chats0
TLDR
The main challenges to be dealt with for the wide scale deployment of anomaly-based intrusion detectors, with special emphasis on assessment issues are outlined.About:
This article is published in Computers & Security.The article was published on 2009-02-01. It has received 1712 citations till now. The article focuses on the topics: Anomaly-based intrusion detection system & Intrusion detection system.read more
Citations
More filters
Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
TL;DR: The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.
Journal ArticleDOI
Review: Intrusion detection system: A comprehensive review
TL;DR: Through the extensive survey and sophisticated organization, this work proposes the taxonomy to outline modern IDSs and tries to give a more elaborate image for a comprehensive review.
Proceedings Article
Deep One-Class Classification
Lukas Ruff,Robert A. Vandermeulen,Nico Goernitz,Lucas Deecke,Shoaib Ahmed Siddiqui,Alexander Binder,Emmanuel Müller,Marius Kloft +7 more
TL;DR: This paper introduces a new anomaly detection method—Deep Support Vector Data Description—, which is trained on an anomaly detection based objective and shows the effectiveness of the method on MNIST and CIFAR-10 image benchmark datasets as well as on the detection of adversarial examples of GTSRB stop signs.
Journal ArticleDOI
Network Anomaly Detection: Methods, Systems and Tools
TL;DR: This paper provides a structured and comprehensive overview of various facets of network anomaly detection so that a researcher can become quickly familiar with every aspect of network anomalies detection.
Journal ArticleDOI
Andromaly: a behavioral malware detection framework for android devices
TL;DR: Empirical results suggest that the proposed framework, Andromaly, is effective in detecting malware on mobile devices in general and on Android in particular.
References
More filters
Proceedings ArticleDOI
Stateful intrusion detection for high-speed network's
TL;DR: A partitioning approach to network security, analysis that supports in-depth, stateful intrusion detection on high-speed links that is centered around a slicing mechanism that divides the overall network traffic into subsets of manageable size.
Proceedings ArticleDOI
ADMIT: anomaly-based data mining for intrusions
TL;DR: This paper deals with the problem of differentiating between masqueraders and the true user of a computer terminal by creating user profiles using semi-incremental techniques and suggests ideas for dealing with concept drift.
Fuzzy data mining and genetic algorithms applied to intrusion detection
TL;DR: A prototype intelligent intrusion detection system that combines both anomaly based intrusion detection using fuzzy data mining techniques and misuse detection using traditional rule-based expert system techniques is developed.
Proceedings ArticleDOI
Fuzzy network profiling for intrusion detection
TL;DR: This paper describes the components in the FIRE architecture and explains their roles, with particular attention given to explaining the benefits of data mining and how this can improve the meaningfulness of the fuzzy sets.