Proceedings ArticleDOI
An Intrusion-Detection Model
Dorothy E. Denning
- pp 118-118
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TLDR
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.Abstract:
A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage. The model includes profiles for representing the behavior of subjects with respect to objects in terms of metrics and statistical models, and rules for acquiring knowledge about this behavior from audit records and for detecting anomalous behavior. The model is independent of any particular system, application environment, system vulnerability, or type of intrusion, thereby providing a framework for a general-purpose intrusion-detection expert system.read more
Citations
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Discovering the potential for advancements in intrusion detection systems
TL;DR: This paper demonstrates that there is still potential for futher exploration into the development of intrusion detection systems as there are still many unanswered questions in regards to its future use.
Proceedings ArticleDOI
System for Intrusion Detection with Artificial Neural Network
TL;DR: This research aims to solve a multi class problem in which the type of attack is also detected by the neural network, and shows that the designed system is capable of classifying records with about 91% accuracy with two hidden layers of neurons in the Neural network.
Proceedings ArticleDOI
Unsupervised Learning: A Fusion of Rough Sets and Fuzzy Ants Clustering for Anomaly Detection System
S. Srinoy,W. Kurutach +1 more
TL;DR: An intrusion detection method that proposes rough set based feature selection heuristics and using fuzzy ants for clustering data and the experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) dataset.
DissertationDOI
Detecting Misbehaviour in a Complex System-of-Systems Environment
TL;DR: A novel misbehaviour detection framework specifically developed for operation in a SoS environment, able to cope with monitoring the dynamic behaviour and suddenly occurring changes that affect threshold reliability and increased efficiency and reduced false positive rates, false negative rates, resource usage and run-time requirements.
Dissertation
Audit et monitorage de la sécurité
TL;DR: In this paper, the authors present an approche pro-active elevee for the detection of failles de securite par un processus de type "fuzzing", which permet la prise en compte du comportement d'une souche protocolaire.