Author
Parlak, Mehmet, Altunel, Nurkan Fatih, Akkaş, Utku Ayaz, Arıcı, Emir Tarık
Publication Date
2022
Publication Place
-
IEEE
Subject
Autonomous vehicles, Blockchain, Deep learning, Deepfake, Insurance, Insurtech, Liability, Smart contracts
Type
Document
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
978-166545198-7
Record ID
0a0afded-07e9-4e1f-8daa-ae4c97a90ed5
Library Location
Electrical & Electronics Engineering
Date
2022
Sample Text
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.
DOI
10.1109/iGETblockchain56591.2022.10087067
