P M V U Auth: Physical Unclonable Function and Machine Learning based
Zero Knowledge Internet of Vehicle Unlock and Authentication Framework
Abstract
Comfort has become a requirement in our modern world. This level of
comfort, particularly in automobiles, can only be accomplished by
outfitting the vehicle with additional electrical equipment. Some
electronic equipment must communicate with one another, which
necessitates the use of a data transmission. Nowadays, it is challenging
to sell a new automobile that includes traditional keys. Now, a
sophisticated remote locking system is used to lock and unlock
autonomous vehicles (AV). A remote unlocking system consists of a
transponder that wirelessly connects with the automobile transmitter to
lock/unlock the automobile. Unfortunately, wireless communication
methods of the internet of vehicle (IoV) face a number of threats. This
study provides a safe solution for the automobile unlocking system that
uses dynamically generated temporary keys to meet the future demands of
smart cars driven by the Internet of Things. To maintain security,
machine learning (ML) and physical unclonable function (PUF) are used to
permit auto locking and unlocking capability in this work. The technique
has exhibited 99.91\% accuracy, which proves the
reliability of securing the automobile unlocking system. Moreover, the
computation cost is 3.8 ms and communication overhead is 176 bytes for
unlocking by the owner and 144 bytes when the car will be unlocked by
other than the owner. Furthermore, both formal (Burrows–Abadi–Needham
(BAN) logic) and informal security analysis of the proposed method are
provided.