Towards Effective Identification and Rating of Automotive Vulnerabilities

Autor: Pranshu Bajpai, Richard Enbody
Rok vydání: 2020
Předmět:
Zdroj: AutoSec@CODASPY
DOI: 10.1145/3375706.3380556
Popis: Cybersecurity is a paramount concern in automobiles since deficiencies in security controls put human lives at risk. Some security vulnerabilities are more critical than others and demand immediate attention. Therefore, it is imperative to quantify associated risks by means of rating security vulnerabilities on a scale of severity which has proven to be a useful tool for traditional IT security in comprehending the real risk associated with a vulnerability. In this paper, we present a methodology for adapting the proven CVSS scoring system to automobiles and illustrate the notion with several examples of real-world automotive security vulnerabilities. We also propose a CVV naming system, that is based on the existing CVE system by MITRE, to assign unique identifiers to these vulnerabilities which permits efficient tracking and analysis of automotive vulnerabilities.
Databáze: OpenAIRE