With the release of ChatGPT in 2022, generative AI has significantly lowered the cost of polishing and rewriting text. Due to its widespread usage, conference organizers instated specific requirements researchers need to adhere to when using GenAI. When asked to rewrite text, GenAI can introduce stylistic changes, often concentrated to a handful of ``marker words`` commonly associated with AI usage. Prior large-scale studies in preprints and biomedical science report post-2022 discontinuities of those marker words and broad linguistic features. This paper investigates whether similar patterns appear in top-tier cybersecurity conference papers (NDSS, USENIX Security, IEEE S\&P, and ACM CCS) over the period 2000-2025. Using text extracted from paper PDFs, we compute lexical and syntactic metrics and track curated marker-word usage. Our findings reveal a gradual long-run drift toward higher lexical complexity and a pronounced post-2022 increase in marker-word usage across all venues showing an emerging trend towards more complex language in cybersecurity papers possibly hindering accessibility.

翻译：随着2022年ChatGPT的发布，生成式人工智能显著降低了润色和改写文本的成本。由于其广泛使用，会议组织者制定了研究人员在使用GenAI时必须遵守的具体要求。当被要求改写文本时，GenAI可能会引入风格上的变化，这些变化通常集中在少数几个常与AI使用相关的“标记词”上。先前针对预印本和生物医学科学的大规模研究报告了2022年后这些标记词和广泛语言特征的突变。本文研究了在2000-2025年期间，顶级网络安全会议论文（NDSS、USENIX Security、IEEE S&P和ACM CCS）中是否出现类似模式。通过从论文PDF中提取文本，我们计算了词汇和句法指标，并追踪了精心挑选的标记词的使用情况。我们的研究结果揭示了一个逐渐向更高词汇复杂性演变的长期趋势，以及所有会议中标记词使用在2022年后的显著增加，这表明网络安全论文中出现了向更复杂语言发展的新兴趋势，这可能阻碍了可读性。