Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020657476> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W2020657476 abstract "Many researchers have argued that data mining can improve the performance of intrusion detection system. So as one of important techniques of data mining, clustering is an important means for intrusion detection. Due to the disadvantages of traditional clustering methods for intrusion detection, this paper presents a graph-based intrusion detection algorithm by using outlier detection method that based on local deviation coefficient (LDCGB). Compared to other intrusion detection algorithm of clustering, this algorithm is unnecessary to initial cluster number. Meanwhile, it is robust in the outlier's affection and able to detect any shape of cluster rather that the circle one only. Moreover, it still has stable rate of detection on unknown or muted attacks. LDCGB uses graph-based cluster algorithm (GB) to get an initial partition of data set which is depended on parameter of cluster precision rather than initial cluster number. On the other hand, because of this intrusion detection model is based on mixed training dataset, so it must have high label accuracy to guarantee its performance. Therefore, in labeling phrase, the algorithm imposes outlier detection algorithm of local deviation coefficient to label the result of GB algorithm again. This measure is able to improve the labeling accuracy. The detection rate and false positive rate are obtained after the algorithm is tested by the KDDCup99 data set. The experimental result shows that the proposed algorithm could get a satisfactory performance." @default.
- W2020657476 created "2016-06-24" @default.
- W2020657476 creator A5015263485 @default.
- W2020657476 creator A5070470270 @default.
- W2020657476 creator A5077422771 @default.
- W2020657476 date "2012-07-01" @default.
- W2020657476 modified "2023-09-26" @default.
- W2020657476 title "A graph-based clustering algorithm for anomaly intrusion detection" @default.
- W2020657476 cites W1976331960 @default.
- W2020657476 cites W2016070752 @default.
- W2020657476 cites W2031862666 @default.
- W2020657476 cites W2113970724 @default.
- W2020657476 cites W2126710141 @default.
- W2020657476 cites W2147457514 @default.
- W2020657476 cites W2150847526 @default.
- W2020657476 cites W2170771030 @default.
- W2020657476 doi "https://doi.org/10.1109/iccse.2012.6295306" @default.
- W2020657476 hasPublicationYear "2012" @default.
- W2020657476 type Work @default.
- W2020657476 sameAs 2020657476 @default.
- W2020657476 citedByCount "31" @default.
- W2020657476 countsByYear W20206574762013 @default.
- W2020657476 countsByYear W20206574762014 @default.
- W2020657476 countsByYear W20206574762015 @default.
- W2020657476 countsByYear W20206574762016 @default.
- W2020657476 countsByYear W20206574762017 @default.
- W2020657476 countsByYear W20206574762018 @default.
- W2020657476 countsByYear W20206574762019 @default.
- W2020657476 countsByYear W20206574762020 @default.
- W2020657476 countsByYear W20206574762021 @default.
- W2020657476 countsByYear W20206574762022 @default.
- W2020657476 crossrefType "proceedings-article" @default.
- W2020657476 hasAuthorship W2020657476A5015263485 @default.
- W2020657476 hasAuthorship W2020657476A5070470270 @default.
- W2020657476 hasAuthorship W2020657476A5077422771 @default.
- W2020657476 hasConcept C11413529 @default.
- W2020657476 hasConcept C124101348 @default.
- W2020657476 hasConcept C153180895 @default.
- W2020657476 hasConcept C154945302 @default.
- W2020657476 hasConcept C35525427 @default.
- W2020657476 hasConcept C41008148 @default.
- W2020657476 hasConcept C58489278 @default.
- W2020657476 hasConcept C73555534 @default.
- W2020657476 hasConcept C739882 @default.
- W2020657476 hasConcept C79337645 @default.
- W2020657476 hasConceptScore W2020657476C11413529 @default.
- W2020657476 hasConceptScore W2020657476C124101348 @default.
- W2020657476 hasConceptScore W2020657476C153180895 @default.
- W2020657476 hasConceptScore W2020657476C154945302 @default.
- W2020657476 hasConceptScore W2020657476C35525427 @default.
- W2020657476 hasConceptScore W2020657476C41008148 @default.
- W2020657476 hasConceptScore W2020657476C58489278 @default.
- W2020657476 hasConceptScore W2020657476C73555534 @default.
- W2020657476 hasConceptScore W2020657476C739882 @default.
- W2020657476 hasConceptScore W2020657476C79337645 @default.
- W2020657476 hasLocation W20206574761 @default.
- W2020657476 hasOpenAccess W2020657476 @default.
- W2020657476 hasPrimaryLocation W20206574761 @default.
- W2020657476 hasRelatedWork W2090668960 @default.
- W2020657476 hasRelatedWork W2172289703 @default.
- W2020657476 hasRelatedWork W2359185137 @default.
- W2020657476 hasRelatedWork W2366051640 @default.
- W2020657476 hasRelatedWork W3152110224 @default.
- W2020657476 hasRelatedWork W3183283580 @default.
- W2020657476 hasRelatedWork W3183437131 @default.
- W2020657476 hasRelatedWork W4230206970 @default.
- W2020657476 hasRelatedWork W4250175685 @default.
- W2020657476 hasRelatedWork W2186522517 @default.
- W2020657476 isParatext "false" @default.
- W2020657476 isRetracted "false" @default.
- W2020657476 magId "2020657476" @default.
- W2020657476 workType "article" @default.