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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Journal ArticleDOI
A Review of Anomaly Detection Systems in Cloud Networks and Survey of Cloud Security Measures in Cloud Storage Applications
TL;DR: This review paper exposes and focuses on different IDS in cloud networks through different categorizations and conducts comparative study on the security measures of Dropbox, Google Drive and iCloud, to illuminate their strength and weakness in terms of security.
Proceedings ArticleDOI
Quantitative Network Monitoring with NetQRE
TL;DR: The authors' evaluation results demonstrate that NetQRE results in high performance that is comparable with optimized manually-written low-level code and is significantly more efficient than alternative solutions, and can provide timely enforcement of network policies that require quantitative network monitoring.
Journal ArticleDOI
Network Intrusion Detection Based on Novel Feature Selection Model and Various Recurrent Neural Networks
TL;DR: The experimental results show the proposed models achieve significantly improved accuracy detection rate as well as attack types classification and this approach can reduce the computation time by memory profilers measurement.
Journal ArticleDOI
A framework for anomaly detection and classification in Multiple IoT scenarios
Francesco Cauteruccio,Luca Cinelli,Enrico Corradini,Giorgio Terracina,Domenico Ursino,Luca Virgili,Claudio Savaglio,Antonio Liotta,Giancarlo Fortino +8 more
TL;DR: A new methodological framework is proposed that can make future investigations in this research field easier, coherent, and uniform in the context of anomaly detection in an MIoT, and the so-called "forward problem” and "inverse problem" are defined.
Journal ArticleDOI
Feature selection techniques for intrusion detection using non-bio-inspired and bio-inspired optimization algorithms
TL;DR: This work provides a survey of feature selection techniques for IDS, including bio-inspired algorithms, includingBio-inspired optimization algorithms have been used for feature selection.
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.