Matches in SemOpenAlex for { <https://semopenalex.org/work/W2925211097> ?p ?o ?g. }
Showing items 1 to 55 of
55
with 100 items per page.
- W2925211097 abstract "<p>High and low-intensity attacks are two common Distributed Denial of Service (DDoS) attacks that disrupt Internet users and their daily operations. Detecting these attacks is important to ensure that communication, business operations, and education facilities can run smoothly. Many DDoS attack detection systems have been proposed in the past but still lack performance, scalability, and information sharing ability to detect both high and low-intensity DDoS attacks accurately and early. To combat these issues, this thesis studies the use of Software-Defined Networking technology, entropy-based features, and machine learning classifiers to develop three useful components, namely a good system architecture, a useful set of features, and an accurate and generalised traffic classification scheme. The findings from the experimental analysis and evaluation results of the three components provide important insights for researchers to improve the overall performance, scalability, and information sharing ability for building an accurate and early DDoS attack detection system.</p>" @default.
- W2925211097 created "2019-04-01" @default.
- W2925211097 creator A5054372628 @default.
- W2925211097 date "2021-12-07" @default.
- W2925211097 modified "2023-10-12" @default.
- W2925211097 title "Detecting High and Low Intensity Distributed Denial of Service (DDoS) Attacks" @default.
- W2925211097 cites W1857789879 @default.
- W2925211097 doi "https://doi.org/10.26686/wgtn.17135222.v1" @default.
- W2925211097 hasPublicationYear "2021" @default.
- W2925211097 type Work @default.
- W2925211097 sameAs 2925211097 @default.
- W2925211097 citedByCount "0" @default.
- W2925211097 crossrefType "dissertation" @default.
- W2925211097 hasAuthorship W2925211097A5054372628 @default.
- W2925211097 hasBestOaLocation W29252110971 @default.
- W2925211097 hasConcept C110875604 @default.
- W2925211097 hasConcept C111919701 @default.
- W2925211097 hasConcept C120865594 @default.
- W2925211097 hasConcept C136764020 @default.
- W2925211097 hasConcept C167272206 @default.
- W2925211097 hasConcept C31258907 @default.
- W2925211097 hasConcept C38652104 @default.
- W2925211097 hasConcept C38822068 @default.
- W2925211097 hasConcept C41008148 @default.
- W2925211097 hasConcept C43639116 @default.
- W2925211097 hasConcept C48044578 @default.
- W2925211097 hasConceptScore W2925211097C110875604 @default.
- W2925211097 hasConceptScore W2925211097C111919701 @default.
- W2925211097 hasConceptScore W2925211097C120865594 @default.
- W2925211097 hasConceptScore W2925211097C136764020 @default.
- W2925211097 hasConceptScore W2925211097C167272206 @default.
- W2925211097 hasConceptScore W2925211097C31258907 @default.
- W2925211097 hasConceptScore W2925211097C38652104 @default.
- W2925211097 hasConceptScore W2925211097C38822068 @default.
- W2925211097 hasConceptScore W2925211097C41008148 @default.
- W2925211097 hasConceptScore W2925211097C43639116 @default.
- W2925211097 hasConceptScore W2925211097C48044578 @default.
- W2925211097 hasLocation W29252110971 @default.
- W2925211097 hasLocation W29252110972 @default.
- W2925211097 hasOpenAccess W2925211097 @default.
- W2925211097 hasPrimaryLocation W29252110971 @default.
- W2925211097 hasRelatedWork W2036735483 @default.
- W2925211097 hasRelatedWork W2187421104 @default.
- W2925211097 hasRelatedWork W2314185362 @default.
- W2925211097 hasRelatedWork W2353151461 @default.
- W2925211097 hasRelatedWork W2360429410 @default.
- W2925211097 hasRelatedWork W2376172429 @default.
- W2925211097 hasRelatedWork W2783826416 @default.
- W2925211097 hasRelatedWork W3142394876 @default.
- W2925211097 hasRelatedWork W2186749541 @default.
- W2925211097 hasRelatedWork W2189542741 @default.
- W2925211097 isParatext "false" @default.
- W2925211097 isRetracted "false" @default.
- W2925211097 magId "2925211097" @default.
- W2925211097 workType "dissertation" @default.