In less than a decade, blockchain has emerged as one of the most disruptive technologies in the present scenario. The underlying architecture behind cryptocurrencies has been integral across countless professional sectors as well as research. In fact, a recent blockchain-based innovation proposes using the technology to ensure data veracity and integrity in vehicular forensics.
Challenges in Fully Autonomous Vehicles
There has been considerable progress in fully autonomous vehicle(FAV) development. However, it has also led to rising concerns regarding the efficacy of existing forensics processes in case of FAVs. The current process often blames the vehicle driver. However, the same is not possible for FAVs, and the blame mostly shifts towards the automobile manufacturer for product defects(if traceable). Service technicians are blamed if service faults persist, while the vehicle owner may be held accountable for negligence.
In the case of autonomous vehicles, evidence is captured from nearby in-vehicle sensors. A chain of occurrences eventually leading to the accident is considered. The sensors collect pertinent information including location, video, speed, safety system data and more.
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Blockchain Advantages
The implementation of blockchain technology in the auto forensics domain is gaining significant traction across the globe owing to its decentralized structure and immutability. The decentralization feature allows multiple network members(nodes) to access, maintain and manage the data record. Meanwhile, the immutability feature preserves the integrity of evidence data. This is crucial in determining liability decisions.
The WIDE Architecture
The blockchain technology is incorporated in WItness based Data priority mEchanism(WIDE) through a reputation management system. The system ensures the veracity of data, using sensor-data exclusively from cars with high reputations for liability decision-making. The proposed innovation also identifies and addresses potential attacks, in addition to showcasing latency and reputation.
WIDE Components
Primary Vehicles: The primary vehicles are the ones directly involved in the crash. When an accident occurs, the vehicles transmit and relay a safety message. The transmission alerts and signals witness vehicles within the vicinity. The primary vehicles then record and save the data for liability attribution afterwards.
Witness Vehicles: Cars in close proximity to the primary accident vehicles receive notifications in the event of a crash. This activates their recording sensors which store accident details of the primary car. The information is transferred to a roadside unit to contribute evidence for evaluating reputation.
Roadside Units(RSU): Roadside units have a lot of functions, from assessing data integrity, behavior profile identification and calculating a reputation score for the car. The behavior profile is key in determining the performance (pass/fail) of a vehicle in integrity assessment, underlining reputation management.
Transport Authorities: Transport authorities are the authorized figures for RSU installation and maintenance. The identification of rogue RSU during credibility assessment leads to information broadcasting across the blockchain, and later rectification of the defective RSU.
Law Enforcement: The enforcement authorities receive complimentary evidence through the blockchain. They also use vehicle reputation scores to identify credible sources and witnesses.
BRMS: Blockchain Reputation Management System is maintained by RSUs, and stores integrity assessment outcomes churned by them. It offers vehicle credibility profiles, capturing a proportion or ratio time each profile fails or passes integrity assessment. This way, it expresses the credibility since inception i.e. the entire operational life cycle.
Wrapping Up
The WIDE vehicular forensics application presents one more application of the seemingly limitless potential application of blockchain. Reputation management presents an efficient method of data authentication through witness vehicles, RSUS, blockchain and more.
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