Journal ArticleDOI
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
TLDR
A new hybrid model can be used to estimate the intrusion scope threshold degree based on the network transaction data’s optimal features that were made available for training and revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale.About:
This article is published in Journal of Computational Science.The article was published on 2017-03-22. It has received 484 citations till now. The article focuses on the topics: Anomaly-based intrusion detection system & Intrusion detection system.read more
Citations
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Proceedings ArticleDOI
An Intrusion Detection System Using Apache Log Files
Cemile Ince,Zeki Omaç +1 more
TL;DR: In this study, an attack detection system (STS) has been developed by using Inonu University web page log files and was trained using artificial neural network (ANN) and attacks were detected with 99.3% success.
Posted Content
A concise method for feature selection via normalized frequencies.
TL;DR: In this article, a fusion of the filter method and the wrapper method is proposed for feature selection in the context of intrusion detection, which uses normalized frequencies to assign a value to each feature, which will be used to find the optimal feature subset.
Journal ArticleDOI
An Effective Method to Extract Web Content Information
Suhan Pan,Zhiqiang Li,Juan Dai +2 more
TL;DR: The TPDT method effectively solves the problem of noisy information filtering and text content extraction without the training and manual processing.
Crime Prediction and Intrusion Detection with IoT and Machine Learning
TL;DR: In this paper, the authors have designed a prototype that helps the police in detecting crime locations by using a digital camera which is attached with an IoT device and GPS will be used for location detection, this whole matter will directly connect the police with crime location which ease the police can reach that location.
References
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Proceedings ArticleDOI
Multi-column deep neural networks for image classification
TL;DR: In this paper, a biologically plausible, wide and deep artificial neural network architectures was proposed to match human performance on tasks such as the recognition of handwritten digits or traffic signs, achieving near-human performance.
Proceedings Article
Bro: a system for detecting network intruders in real-time
TL;DR: Bro as mentioned in this paper is a stand-alone system for detecting network intruders in real-time by passively monitoring a network link over which the intruder's traffic transits, which emphasizes high-speed (FDDI-rate) monitoring, realtime notification, clear separation between mechanism and policy and extensibility.
Journal ArticleDOI
Bro: a system for detecting network intruders in real-time
Vern Paxson,Vern Paxson +1 more
TL;DR: An overview of the Bro system's design, which emphasizes high-speed (FDDI-rate) monitoring, real-time notification, clear separation between mechanism and policy, and extensibility, is given.
Journal ArticleDOI
Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory
TL;DR: The purpose of this article is to attempt to identify the shortcomings of the Lincoln Lab effort in the hope that future efforts of this kind will be placed on a sounder footing.
Proceedings 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.
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