Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring

Name: Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring
Author: Parlak, Mehmet, Altunel, Nurkan Fatih, Akkaş, Utku Ayaz, Arıcı, Emir Tarık

İsim	Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring
Yazar	Parlak, Mehmet, Altunel, Nurkan Fatih, Akkaş, Utku Ayaz, Arıcı, Emir Tarık
Basım Tarihi:	2022
Basım Yeri	- IEEE
Konu	Autonomous vehicles, Blockchain, Deep learning, Deepfake, Insurance, Insurtech, Liability, Smart contracts
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-166545198-7
Kayıt Numarası	0a0afded-07e9-4e1f-8daa-ae4c97a90ed5
Lokasyon	Electrical & Electronics Engineering
Tarih	2022
Örnek Metin	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

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Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring

Yazar Parlak, Mehmet, Altunel, Nurkan Fatih, Akkaş, Utku Ayaz, Arıcı, Emir Tarık

Basım Tarihi 2022

Basım Yeri - IEEE

Konu Autonomous vehicles, Blockchain, Deep learning, Deepfake, Insurance, Insurtech, Liability, Smart contracts

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-166545198-7

Kayıt Numarası 0a0afded-07e9-4e1f-8daa-ae4c97a90ed5

Lokasyon Electrical & Electronics Engineering

Tarih 2022

Örnek Metin 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