Matches in SemOpenAlex for { <https://semopenalex.org/work/W3197788255> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W3197788255 endingPage "748" @default.
- W3197788255 startingPage "730" @default.
- W3197788255 abstract "Modern vehicle is considered as a system vulnerable to attacks because it is connected to the outside world via a wireless interface. Although, connectivity provides more convenience and features to the passengers, however, it also becomes a pathway for the attackers targeting in-vehicle networks. Research in vehicle security is getting attention as in-vehicle attacks can impact human life safety as modern vehicle is connected to the outside world. Controller area network (CAN) is used as a legacy protocol for in-vehicle communication, However, CAN suffers from vulnerabilities due to lack of authentication, as the information about sender is missing in CAN message. In this paper, a new CAN intrusion detection system (IDS) is proposed, the CAN messages are converted to temporal graphs and CAN intrusion is detected using machine learning algorithms. Seven graph-based properties are extracted and used as features for detecting intrusions utilizing two machine learning algorithms which are support vector machine (SVM) & k-nearest neighbors (KNN). The performance of the IDS was evaluated over three CAN bus attacks are denial of service (DoS), fuzzy & spoofing attacks on real vehicular CAN bus dataset. The experimental results showed that using graph-based features, an accuracy of 97.92% & 97.99% was achieved using SVM & KNN algorithms respectively, which is better than using traditional machine learning CAN bus features." @default.
- W3197788255 created "2021-09-13" @default.
- W3197788255 creator A5000755585 @default.
- W3197788255 creator A5033599238 @default.
- W3197788255 creator A5071065536 @default.
- W3197788255 creator A5081212446 @default.
- W3197788255 date "2021-08-07" @default.
- W3197788255 modified "2023-09-27" @default.
- W3197788255 title "Detecting CAN Bus Intrusion by Applying Machine Learning Method to Graph Based Features" @default.
- W3197788255 cites W1544448511 @default.
- W3197788255 cites W1629374427 @default.
- W3197788255 cites W1713583684 @default.
- W3197788255 cites W1964940342 @default.
- W3197788255 cites W2000687288 @default.
- W3197788255 cites W2045633722 @default.
- W3197788255 cites W2059362538 @default.
- W3197788255 cites W2067431706 @default.
- W3197788255 cites W2088252378 @default.
- W3197788255 cites W2129315144 @default.
- W3197788255 cites W2414564754 @default.
- W3197788255 cites W2499581503 @default.
- W3197788255 cites W2506734067 @default.
- W3197788255 cites W2590573807 @default.
- W3197788255 cites W2591133720 @default.
- W3197788255 cites W2746620120 @default.
- W3197788255 cites W2771179281 @default.
- W3197788255 cites W2893123663 @default.
- W3197788255 cites W2898623510 @default.
- W3197788255 cites W2914769175 @default.
- W3197788255 cites W2945012921 @default.
- W3197788255 cites W2948384692 @default.
- W3197788255 cites W2959120033 @default.
- W3197788255 cites W2964052849 @default.
- W3197788255 cites W2970148885 @default.
- W3197788255 cites W3000946945 @default.
- W3197788255 cites W3009513989 @default.
- W3197788255 cites W3009593792 @default.
- W3197788255 cites W3010821038 @default.
- W3197788255 cites W3042693420 @default.
- W3197788255 cites W3081977072 @default.
- W3197788255 cites W3091724539 @default.
- W3197788255 cites W3092232275 @default.
- W3197788255 cites W3094137245 @default.
- W3197788255 cites W3102406764 @default.
- W3197788255 doi "https://doi.org/10.1007/978-3-030-82199-9_49" @default.
- W3197788255 hasPublicationYear "2021" @default.
- W3197788255 type Work @default.
- W3197788255 sameAs 3197788255 @default.
- W3197788255 citedByCount "8" @default.
- W3197788255 countsByYear W31977882552021 @default.
- W3197788255 countsByYear W31977882552022 @default.
- W3197788255 countsByYear W31977882552023 @default.
- W3197788255 crossrefType "book-chapter" @default.
- W3197788255 hasAuthorship W3197788255A5000755585 @default.
- W3197788255 hasAuthorship W3197788255A5033599238 @default.
- W3197788255 hasAuthorship W3197788255A5071065536 @default.
- W3197788255 hasAuthorship W3197788255A5081212446 @default.
- W3197788255 hasConcept C110875604 @default.
- W3197788255 hasConcept C119857082 @default.
- W3197788255 hasConcept C12267149 @default.
- W3197788255 hasConcept C124101348 @default.
- W3197788255 hasConcept C136764020 @default.
- W3197788255 hasConcept C154945302 @default.
- W3197788255 hasConcept C167900197 @default.
- W3197788255 hasConcept C201762086 @default.
- W3197788255 hasConcept C31258907 @default.
- W3197788255 hasConcept C35525427 @default.
- W3197788255 hasConcept C38822068 @default.
- W3197788255 hasConcept C41008148 @default.
- W3197788255 hasConceptScore W3197788255C110875604 @default.
- W3197788255 hasConceptScore W3197788255C119857082 @default.
- W3197788255 hasConceptScore W3197788255C12267149 @default.
- W3197788255 hasConceptScore W3197788255C124101348 @default.
- W3197788255 hasConceptScore W3197788255C136764020 @default.
- W3197788255 hasConceptScore W3197788255C154945302 @default.
- W3197788255 hasConceptScore W3197788255C167900197 @default.
- W3197788255 hasConceptScore W3197788255C201762086 @default.
- W3197788255 hasConceptScore W3197788255C31258907 @default.
- W3197788255 hasConceptScore W3197788255C35525427 @default.
- W3197788255 hasConceptScore W3197788255C38822068 @default.
- W3197788255 hasConceptScore W3197788255C41008148 @default.
- W3197788255 hasLocation W31977882551 @default.
- W3197788255 hasOpenAccess W3197788255 @default.
- W3197788255 hasPrimaryLocation W31977882551 @default.
- W3197788255 hasRelatedWork W1554572329 @default.
- W3197788255 hasRelatedWork W2115282466 @default.
- W3197788255 hasRelatedWork W3043172660 @default.
- W3197788255 hasRelatedWork W3088680045 @default.
- W3197788255 hasRelatedWork W3091724539 @default.
- W3197788255 hasRelatedWork W3092232275 @default.
- W3197788255 hasRelatedWork W3194539120 @default.
- W3197788255 hasRelatedWork W4287662260 @default.
- W3197788255 hasRelatedWork W4362468232 @default.
- W3197788255 hasRelatedWork W4379143340 @default.
- W3197788255 isParatext "false" @default.
- W3197788255 isRetracted "false" @default.
- W3197788255 magId "3197788255" @default.
- W3197788255 workType "book-chapter" @default.