提高智能计算机信息安全漏洞评分

Qingkun Zhu
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引用次数: 0

摘要

计算机和互联网技术的快速发展推动了相关领域的不断突破和创新,对社会生产和个人生活方式产生了重大影响。这里解决的一个关键挑战是评估计算机漏洞的现有方法不足。针对智能计算机中的漏洞问题,提出了智能汽车漏洞评分模型(VSMIV)。一个关键方面涉及优化常见漏洞和暴露(CVE)的攻击向量和攻击复杂性,以符合智能计算机的特定行为。该模型的有效性通过整合四个不同的指标来增强:财产安全、隐私安全、功能安全和生命安全。多样性评级表明,VSMIV评分系统的系统分布多样性最高,为95%,其次是CVSSIoT,为88%,CVSS的多样性得分略低,为85%。所提出的方法有望建立一种新的模式来加强计算机系统的安全性,从而激发它们在面对新出现的威胁时的灵活性。
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Enhancing vulnerability scoring for information security in intelligent computers

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 CVSSIoT 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.

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