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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: 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  COBISS.SI-ID: 58232579  UDK: 004 DOI: 10.1007/978-3-319-47952-1_36  NUK URN: URN:SI:UNG:REP:M9ZZ5O7R Datum objave v RUNG: 02.04.2021 Število ogledov: 2986 Število prenosov: 10 Metapodatki:    Citiraj gradivo Navadno besedilo BibTeX EndNote XML EndNote/Refer RIS ABNT ACM Ref AMA APA Chicago 17th Author-Date Harvard IEEE ISO 690 MLA Vancouver : Kopiraj citat

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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
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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