A Blockchain-Based Mutual Authentication Method to Secure the Electric Vehicles’ TPMS

Despite the widespread use of Radio Frequency Identification (RFID) and wireless connectivity such as Near Field Communication (NFC) in electric vehicles, their security and privacy implications in Ad-Hoc networks have not been well explored. This paper provides a data protection assessment of radio frequency electronic system in the Tire Pressure Monitoring System (TPMS). It is demonstrated that eavesdropping is completely feasible from a passing car, at an approximate distance up to 50 meters. Furthermore, our reverse analysis shows that the static n -bit signatures and messaging can be eavesdropped from a relatively far distance, raising privacy concerns as a vehicles' movements can be tracked by using the unique IDs of tire pressure sensors. Unfortunately, current protocols do not use authentication, and automobile technologies hardly follow routine message confirmation so sensor messages may be spoofed remotely. To improve the security of TPMS, we suggest a novel ultra-lightweight mutual authentication for the TPMS registry process in the automotive network. Our experimental results confirm the effectiveness and security of the proposed method in TPMS.©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Study on quantitative design for dynamic blockchain-based computing

This research proposes novel embedded Markovian queueing model-based quantitative models in order to establish a theoretical foundation to design a dynamic blockchain-based computing system with a specific interest in Ethereum. The proposed models commonly assume variable bulk arrivals of transactions in Poisson distribution, i.e., M^(1,n), where n the number of slots across all the mined transactions to be posted in a block or the current block. Firstly, a baseline model is proposed to have a static bulk service of transactions in exponential time, i.e., M^n, for posting the transactions in the current block, referred to as Variable Bulk Arrival and Static Bulk Service (VBASBS) queueing model of the M^(1,n)/M^n/1 type, in which note that n is fixed in order to demonstrate a static chain in terms of the size of the block. Secondly, an adaptive chain model, as a solution of dynamic blockchain in a reactive manner, is proposed based on a Variable Bulk Arrival and Variable Bulk Service (VBAVBS) queueing model of the M^(1,n)/M^(1,i,n)/1 type to provide a quantitative approach to design an adaptive chain that dynamically adapts the size of the block to varying performance trends, in which a state transitions from i back to 0, where 0<i</=n, are tracked in order to demonstrate the dynamically adaptive size of the block. Lastly, an asynchronous chain model, as a solution of dynamic blockchain in a proactive manner, is proposed based on a Variable Bulk Arrival and Asynchronous Bulk Service (VBAABS) queueing model is developed and presented to study and demonstrate the fully asynchronous and staged asynchronous chains. The analytical models are simulated extensively to compare the basic performances of the proposed models such as the average transaction waiting time, the average number of slots per block, and throughput. Further, extensive experiments are conducted in order to validate the analytical results by redesigning the source code of Ethereum to implement and demonstrate each of the proposed chains such as the baseline, the adaptive, the fully-asynchronous and the staged-asynchronous chains. The analytical results and the experimental results will be compared and discussed extensively