Affiliation
University of BedfordshireIssue Date
2020-04-02Subjects
autonomous vehiclescyber security
sensors
application programming interface keys
API keys
smart cities
Internet of Things
smart city infrastructure
Metadata
Show full item recordAbstract
Autonomous vehicles (AVs) are capable of sensing their environment and navigating without any human inputs. When accidents occur between AVs, road infrastructures, or human subjects, liability is decided based on accident forensics. This accident forensics is carried out by the acquisition of sensor data generated within the AVs and through its communication between vehicles to a vehicle (V2V) and vehicle to infrastructure (V2I) with a centralised data hub in smart cities that collects and stores this data thereby aiding the relevant authorities in informed decision making. However, practices mostly employed in extracting this information are unprofessional when compared to other areas of digital forensics. In this paper, we designed and implemented a non-invasive mechanism for the collection and storage of forensic data from AVs within smart cities. This mechanism is efficient, secure, and preserves the privacy of data generated by the AV.Citation
Feng X, Dawam ES, Li D (2019) 'Autonomous vehicles' forensics in smart cities', IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation - Leicester, Institute of Electrical and Electronics Engineers Inc..Additional Links
https://ieeexplore.ieee.org/document/9060127Type
Conference papers, meetings and proceedingsLanguage
enISBN
9781728140346ae974a485f413a2113503eed53cd6c53
10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00301