Enhancing vulnerability scoring for information security in intelligent computers

Abstract

Rapid computer and internet technology advancements have catalyzed continuous breakthroughs and innovations in related fields, significantly impacting social production and individual lifestyles. A critical challenge addressed here is the inadequacy of existing methods for assessing computer vulnerabilities. The vulnerability scoring model for intelligent vehicles (VSMIV) is proposed to solve the issue in intelligent computers. A key aspect involves optimizing the attack vector and attack complexity of common vulnerabilities and exposures (CVEs) to align with the specific behaviour of intelligent computers. The model's effectiveness is enhanced by integrating four distinct indicators: property security, privacy security, functional security, and life security. The diversity ratings indicate that the VSMIV scoring system has the highest diversity of system distribution at 95%, followed by CVSS_IoT at 88%, and CVSS with a slightly lower diversity score of 85%. The proposed methodology holds promise in establishing a new paradigm for strengthening the security of computer systems, thereby stimulating their flexibility in the face of emerging threats.