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Naslov:Design & analysis of clustering based intrusion detection schemes for e-governance
Avtorji:ID Gupta, Rajan (Avtor)
ID Muttoo, Sunil K. (Avtor)
ID Pal, Saibal K. (Avtor)
Datoteke:URL https://doi.org/10.1007/978-3-319-47952-1_36
 
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:UNG - Univerza v Novi Gorici
Opis:The problem of attacks on various networks and information systems is increasing. And with systems working in public domain like those involved under E-Governance are facing more problems than others. So there is a need to work on either designing an altogether different intrusion detection system or improvement of the existing schemes with better optimization techniques and easy experimental setup. The current study discusses the design of an Intrusion Detection Scheme based on traditional clustering schemes like K-Means and Fuzzy C-Means along with Meta-heuristic scheme like Particle Swarm Optimization. The experimental setup includes comparative analysis of these schemes based on a different metric called Classification Ratio and traditional metric like Detection Rate. The experiment is conducted on a regular Kyoto Data Set used by many researchers in past, however the features extracted from this data are selected based on their relevance to the E-Governance system. The results shows a better and higher classification ratio for the Fuzzy based clustering in conjunction with meta-heuristic schemes. The development and simulations are carried out using MATLAB.
Ključne besede:particle swarm optimization, intrusion detection, anomaly detection, intrusion detection system, network intrusion detection
Leto izida:2016
Št. strani:Str. 461-471
PID:20.500.12556/RUNG-6425 Novo okno
COBISS.SI-ID:58232579 Novo okno
UDK:004
DOI:10.1007/978-3-319-47952-1_36 Novo okno
NUK URN:URN:SI:UNG:REP:M9ZZ5O7R
Datum objave v RUNG:02.04.2021
Število ogledov:2020
Število prenosov:9
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del monografije

Naslov:Intelligent Systems Technologies and Applications 2016
Uredniki:Juan Manuel Corchado
Kraj izida:Cham
Založnik:Springer Nature
ISBN:978-3-319-47952-1
COBISS.SI-ID:58232067 Novo okno
Naslov zbirke:Advances in intelligent systems and computing (Internet)
Številčenje v zbirki:530
ISSN zbirke:2194-5365

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Naslov:Design and analysis of clustering based intrusion detection schemes for e-governance


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