Matches in SemOpenAlex for { <https://semopenalex.org/work/W2767936830> ?p ?o ?g. }
Showing items 1 to 53 of
53
with 100 items per page.
- W2767936830 abstract "Extracting knowledge from the massive volumes of network traffic is an important challenge in network and security management. In particular, network managers require concise reports about significant changes in their network traffic. While most existing techniques focus on summarizing a single traffic dataset, the problem of finding significant differences between multiple datasets is an open challenge. In this paper, we focus on finding important differences between network traffic datasets, and preparing a summarized and interpretable report for security managers. We propose the use of contrast pattern mining, which finds patterns whose support differs significantly from one dataset to another. We show that contrast patterns are highly effective at extracting meaningful changes in traffic data. We also propose several evaluation metrics that reflect the interpretability of patterns for security managers. Our experimental results show that with the proposed unsupervised approach, the vast majority of extracted patterns are pure, i.e., most changes are either attack traffic or normal traffic, but not a mixture of both." @default.
- W2767936830 created "2017-11-17" @default.
- W2767936830 creator A5066311739 @default.
- W2767936830 creator A5070030398 @default.
- W2767936830 creator A5076014464 @default.
- W2767936830 date "2017-11-06" @default.
- W2767936830 modified "2023-09-27" @default.
- W2767936830 title "Summarizing Significant Changes in Network Traffic Using Contrast Pattern Mining" @default.
- W2767936830 cites W1991400162 @default.
- W2767936830 cites W2013525544 @default.
- W2767936830 cites W2101896525 @default.
- W2767936830 cites W2124066753 @default.
- W2767936830 cites W2161970221 @default.
- W2767936830 cites W2162034534 @default.
- W2767936830 cites W2167450247 @default.
- W2767936830 cites W4245280987 @default.
- W2767936830 doi "https://doi.org/10.1145/3132847.3133111" @default.
- W2767936830 hasPublicationYear "2017" @default.
- W2767936830 type Work @default.
- W2767936830 sameAs 2767936830 @default.
- W2767936830 citedByCount "6" @default.
- W2767936830 countsByYear W27679368302019 @default.
- W2767936830 countsByYear W27679368302020 @default.
- W2767936830 countsByYear W27679368302021 @default.
- W2767936830 crossrefType "proceedings-article" @default.
- W2767936830 hasAuthorship W2767936830A5066311739 @default.
- W2767936830 hasAuthorship W2767936830A5070030398 @default.
- W2767936830 hasAuthorship W2767936830A5076014464 @default.
- W2767936830 hasConcept C124101348 @default.
- W2767936830 hasConcept C154945302 @default.
- W2767936830 hasConcept C2776502983 @default.
- W2767936830 hasConcept C41008148 @default.
- W2767936830 hasConceptScore W2767936830C124101348 @default.
- W2767936830 hasConceptScore W2767936830C154945302 @default.
- W2767936830 hasConceptScore W2767936830C2776502983 @default.
- W2767936830 hasConceptScore W2767936830C41008148 @default.
- W2767936830 hasLocation W27679368301 @default.
- W2767936830 hasOpenAccess W2767936830 @default.
- W2767936830 hasPrimaryLocation W27679368301 @default.
- W2767936830 hasRelatedWork W1987421842 @default.
- W2767936830 hasRelatedWork W2071138464 @default.
- W2767936830 hasRelatedWork W2277695537 @default.
- W2767936830 hasRelatedWork W2346634343 @default.
- W2767936830 hasRelatedWork W2347219288 @default.
- W2767936830 hasRelatedWork W2348097614 @default.
- W2767936830 hasRelatedWork W2383121084 @default.
- W2767936830 hasRelatedWork W2396235808 @default.
- W2767936830 hasRelatedWork W3107474891 @default.
- W2767936830 hasRelatedWork W3021014378 @default.
- W2767936830 isParatext "false" @default.
- W2767936830 isRetracted "false" @default.
- W2767936830 magId "2767936830" @default.
- W2767936830 workType "article" @default.