Matches in SemOpenAlex for { <https://semopenalex.org/work/W2524929627> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W2524929627 abstract "A fault-tracking (bug-tracking) system such as Bugzilla contains fault reports (FRs) collected from various sources such as development teams, test teams, and end-users. Software or security engineers manually analyze the FRs to label the subset of FRs that are security fault reports (SFRs), which indicate a security problem. These SFRs generally deserve higher priority in fault fixing than the not-security fault reports (NSFRs). However, this manual process is time consuming and error-prone (e.g. mislabeling an SFR as an NSFR). To address these important issues, we developed a new approach that applies text mining natural-language descriptions of FRs to train a statistical model on already manually-labeled FRs to identify unlabeled SFRs or SFRs that are manually-mislabeled as NSFRs. A security team can use the model to automate the classification of FRs for large fault databases to reduce the time that they spend on searching for SFRs. We evaluated the model's predictions on a large Cisco software system with over ten million source lines of code. Among a sample of FRs that Cisco software engineers manually labeled as NSFRs, our model successfully classified a high percentage (78%) of the SFRs as verified by a Cisco security team, and predicted their classification as SFRs with a probability of at least 0.98. Our results also indicate that a high percentage (77%) of the SFRs identified by our model is associated with software components that a code-level statistical model predicted to be attack-prone. Such findings provided valuable insights for calling for a future combined approach that exploits both textual information of FRs and code-level information of their associated software components." @default.
- W2524929627 created "2016-10-07" @default.
- W2524929627 creator A5004814257 @default.
- W2524929627 creator A5048118068 @default.
- W2524929627 creator A5055497143 @default.
- W2524929627 date "2009-01-01" @default.
- W2524929627 modified "2023-09-27" @default.
- W2524929627 title "Identifying security fault reports via text mining" @default.
- W2524929627 cites W1531064568 @default.
- W2524929627 cites W1565377632 @default.
- W2524929627 cites W1660390307 @default.
- W2524929627 cites W180288257 @default.
- W2524929627 cites W1965061793 @default.
- W2524929627 cites W2060291526 @default.
- W2524929627 cites W2079317829 @default.
- W2524929627 cites W2090094826 @default.
- W2524929627 cites W2112770261 @default.
- W2524929627 cites W2113693268 @default.
- W2524929627 cites W2156633971 @default.
- W2524929627 cites W2156833313 @default.
- W2524929627 cites W2158133897 @default.
- W2524929627 cites W2160517961 @default.
- W2524929627 cites W2165022036 @default.
- W2524929627 cites W2915874497 @default.
- W2524929627 cites W2966207845 @default.
- W2524929627 cites W87331621 @default.
- W2524929627 hasPublicationYear "2009" @default.
- W2524929627 type Work @default.
- W2524929627 sameAs 2524929627 @default.
- W2524929627 citedByCount "0" @default.
- W2524929627 crossrefType "journal-article" @default.
- W2524929627 hasAuthorship W2524929627A5004814257 @default.
- W2524929627 hasAuthorship W2524929627A5048118068 @default.
- W2524929627 hasAuthorship W2524929627A5055497143 @default.
- W2524929627 hasConcept C111919701 @default.
- W2524929627 hasConcept C114289077 @default.
- W2524929627 hasConcept C124101348 @default.
- W2524929627 hasConcept C127313418 @default.
- W2524929627 hasConcept C154945302 @default.
- W2524929627 hasConcept C165205528 @default.
- W2524929627 hasConcept C175551986 @default.
- W2524929627 hasConcept C177264268 @default.
- W2524929627 hasConcept C199360897 @default.
- W2524929627 hasConcept C2776760102 @default.
- W2524929627 hasConcept C2777904410 @default.
- W2524929627 hasConcept C41008148 @default.
- W2524929627 hasConcept C98045186 @default.
- W2524929627 hasConceptScore W2524929627C111919701 @default.
- W2524929627 hasConceptScore W2524929627C114289077 @default.
- W2524929627 hasConceptScore W2524929627C124101348 @default.
- W2524929627 hasConceptScore W2524929627C127313418 @default.
- W2524929627 hasConceptScore W2524929627C154945302 @default.
- W2524929627 hasConceptScore W2524929627C165205528 @default.
- W2524929627 hasConceptScore W2524929627C175551986 @default.
- W2524929627 hasConceptScore W2524929627C177264268 @default.
- W2524929627 hasConceptScore W2524929627C199360897 @default.
- W2524929627 hasConceptScore W2524929627C2776760102 @default.
- W2524929627 hasConceptScore W2524929627C2777904410 @default.
- W2524929627 hasConceptScore W2524929627C41008148 @default.
- W2524929627 hasConceptScore W2524929627C98045186 @default.
- W2524929627 hasLocation W25249296271 @default.
- W2524929627 hasOpenAccess W2524929627 @default.
- W2524929627 hasPrimaryLocation W25249296271 @default.
- W2524929627 hasRelatedWork W1572830337 @default.
- W2524929627 hasRelatedWork W2071909685 @default.
- W2524929627 hasRelatedWork W2126895252 @default.
- W2524929627 hasRelatedWork W2356122642 @default.
- W2524929627 hasRelatedWork W2378975050 @default.
- W2524929627 hasRelatedWork W2388239784 @default.
- W2524929627 hasRelatedWork W2460246490 @default.
- W2524929627 isParatext "false" @default.
- W2524929627 isRetracted "false" @default.
- W2524929627 magId "2524929627" @default.
- W2524929627 workType "article" @default.