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A Flow Based Horizontal Scan Detection Using Genetic Algorithm Approach

Barati, Morteza, Hakimi, Zahra, Javadi, Amir-Homayoun (2013) A Flow Based Horizontal Scan Detection Using Genetic Algorithm Approach. Life Science Journal, 10 (8s). pp. 331-335. ISSN 1097-8135. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:52623)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.

Abstract

An attacker has to 'scan' susceptible points of a network before attacking. There are several methods of detection of such behavior which are mostly based on thresholding. As the performance of these methods is highly dependent on the value of threshold, it is crucial to adjust this value appropriately. This adjustment is not always trivial. In this study we proposed a new method to optimize the parameters of the system using genetic algorithms (GA) based on network flows. Subsequently we compared our method with Snort. The results showed a superior performance as measured by the sensitivity index of d'.

Item Type: Article
Uncontrolled keywords: flow,genetic algorithm,horizontal scan attack,intrusion detection,threshold
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Amir-Homayoun Javadi
Date Deposited: 13 Dec 2015 13:43 UTC
Last Modified: 05 Nov 2024 10:39 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/52623 (The current URI for this page, for reference purposes)

University of Kent Author Information

Javadi, Amir-Homayoun.

Creator's ORCID: https://orcid.org/0000-0003-0569-6441
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