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P1 Continuous compliance

持续合规
ASE Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering2020匹配度 5/10 · 该论文关注用自动化/静态分析替代人工源码合规审计,属于程序分析在安全与工业场景的应用,与用户对静态分析、工业落地和问题驱动研究的兴趣部分重合;但它不涉及 LLM/Agent、浮点程序分析或贝叶斯程序分析,未命中当前核心追踪方向。引用 18 inbox
Martin Kellogg, Martin Schäf, Serdar Tasiran, Michael D. Ernst
crossref: 2026-09-12

AI 速览

一句话:指出现有合规认证依赖人工审计源代码,成本高、易错、不完整且易回归,主张以持续自动化检查替代。

本文关注大型企业与政府供应商所需的合规认证问题。目前行业标准是由审计员手工审计源代码来证明软件满足 SOC、PCI DSS 等合规制度,以保护敏感数据的隐私与安全。这种手工审计成本高、易出错、覆盖不完整,且难以防止回归。摘要未详述具体方法,但从标题“持续合规”可推断,论文主张以持续、自动化的合规检查替代一次性人工审计,从而降低成本、提高覆盖率并避免回归。评估方面摘要未提供信息。

问题
手工审计源代码以获取合规证书成本高、易错、不完整且易回归。
方法
摘要未给出具体方法;标题暗示以持续性的自动化合规检查替代一次性人工审计。
评估
摘要未提供评估细节。
原文摘要(Abstract)

Vendors who wish to provide software or services to large corporations and governments must often obtain numerous certificates of compliance. Each certificate asserts that the software satisfies a compliance regime, like SOC or the PCI DSS, to protect the privacy and security of sensitive data. The industry standard for obtaining a compliance certificate is an auditor manually auditing source code. This approach is expensive, error-prone, partial, and prone to regressions.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot5929,
  title = {Continuous compliance},
  author = {Martin Kellogg and Martin Schäf and Serdar Tasiran and Michael D. Ernst},
  booktitle = {ASE},
  year = {2020},
  doi = {10.1145/3324884.3416593}
}