Journal ArticleDOI
Anomaly-based network intrusion detection: Techniques, systems and challenges
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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
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Two Layers Trust-Based Intrusion Prevention System for Wireless Sensor Networks
TL;DR: A trust-based model is presented to detect intrusions to the network and it is shown that the model will be suitable with combination of weights in S2 with small networks but when the scale of the network increases, the set ofweights in S3 are best with the model.
Proceedings ArticleDOI
Classification of network anomalies in flow level network traffic using Bayesian networks
M. J. Vargas-Munoz,Rafael Martínez-Peláez,Pablo Velarde-Alvarado,E. Moreno-Garcia,Deni Torres-Roman,J. J. Ceballos-Mejia +5 more
TL;DR: This work proposes a Bayesian network classifier, which can detect normal or anomalous traffic, and focuses on network worms and brute force attacks, using the datasets of UNB ISCX IDS 2012 and UAN W32.
Journal ArticleDOI
Implementation of hybrid P2P networking distributed web crawler using AWS for smart work news big data
TL;DR: The hybrid P2P networking distributed web crawler using AWS (HP2PNC-AWS) is applied to collecting news on Korea’s current smart work lifestyle from three portal sites and it was confirmed that the hybrid P1P networking system could work efficiently in web Crawler architectures.
Proceedings ArticleDOI
Detecting Anomaly Teletraffic Using Stochastic Self-Similarity Based on Hadoop
TL;DR: This paper presents for detecting anomaly teletraffic using stochastic self-similarity based on Hadoop, and shows that the values of the estimated Hurst parameter obtained from the anomaly te letraffic are much higher when compared to ordinary local area network traffic.
Journal ArticleDOI
Multivariate correlation analysis and geometric linear similarity for real-time intrusion detection systems
TL;DR: Comparison study shows that the proposed IDS achieves the best tradeoff between detection rate (99.76%) and false positive rate (0.6%).
References
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Journal ArticleDOI
LOF: identifying density-based local outliers
TL;DR: This paper contends that for many scenarios, it is more meaningful to assign to each object a degree of being an outlier, called the local outlier factor (LOF), and gives a detailed formal analysis showing that LOF enjoys many desirable properties.
Book ChapterDOI
Fast effective rule induction
TL;DR: This paper evaluates the recently-proposed rule learning algorithm IREP on a large and diverse collection of benchmark problems, and proposes a number of modifications resulting in an algorithm RIPPERk that is very competitive with C4.5 and C 4.5rules with respect to error rates, but much more efficient on large samples.
Book
Outliers in Statistical Data
Vic Barnett,Toby Lewis +1 more
TL;DR: In this article, the authors present an updated version of the reference work on outliers, including new areas of study such as outliers in direction data as well as developments in fields such as discordancy tests for univariate and multivariate samples.
Journal ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.