Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring
dc.contributor.author | Parlak, Mehmet | |
dc.contributor.author | Altunel, Nurkan Fatih | |
dc.contributor.author | Akkaş, Utku Ayaz | |
dc.contributor.author | Arıcı, Emir Tarık | |
dc.date.accessioned | 2023-08-03T11:59:39Z | |
dc.date.available | 2023-08-03T11:59:39Z | |
dc.date.issued | 2022 | |
dc.identifier.isbn | 978-166545198-7 | |
dc.identifier.uri | http://hdl.handle.net/10679/8556 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/10087067 | |
dc.description.abstract | In case of an accident between two autonomous vehicles equipped with emerging technologies, how do we apportion liability among the various players? A special liability regime has not even yet been established for damages that may arise due to the accidents of autonomous vehicles. Would the immutable, time-stamped sensor records of vehicles on distributed ledger help define the intertwined relations of liability subjects right through the accident? What if the synthetic media created through deepfake gets involved in the insurance claims? While integrating AI-powered anomaly or deepfake detection into automated insurance claims processing helps to prevent insurance fraud, it is only a matter of time before deepfake becomes nearly undetectable even to elaborate forensic tools. This paper proposes a blockchain-based insurtech decentralized application to check the authenticity and provenance of the accident footage and also to decentralize the loss-adjusting process through a hybrid of decentralized and centralized databases using smart contracts. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | 2022 IEEE 1st Global Emerging Technology Blockchain Forum: Blockchain & Beyond (iGETblockchain) | |
dc.rights | restrictedAccess | |
dc.title | Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring | en_US |
dc.type | Conference paper | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0003-0276-9289 & YÖK ID 378703) Parlak, Mehmet | |
dc.contributor.ozuauthor | Parlak, Mehmet | |
dc.identifier.wos | WOS:000984502600009 | |
dc.identifier.doi | 10.1109/iGETblockchain56591.2022.10087067 | en_US |
dc.subject.keywords | Autonomous vehicles | en_US |
dc.subject.keywords | Blockchain | en_US |
dc.subject.keywords | Deep learning | en_US |
dc.subject.keywords | Deepfake | en_US |
dc.subject.keywords | Insurance | en_US |
dc.subject.keywords | Insurtech | en_US |
dc.subject.keywords | Liability | en_US |
dc.subject.keywords | Smart contracts | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85153847456 | |
dc.contributor.ozugradstudent | Altunel, Nurkan Fatih | |
dc.contributor.ozugradstudent | Akkaş, Utku Ayaz | |
dc.contributor.ozugradstudent | Arıcı, Emir Tarık | |
dc.relation.publicationcategory | Conference Paper - International - Institutional Academic Staff and Undergraduate Student |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
Share this page