发表机构
Microsoft（微软）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对共形预测在进攻性安全领域应用的空白，探索其在隐私保护机器学习、网络流量分析中的进攻性应用，填补了该方向的研究缺失。
AI 中文摘要
尽管共形预测（Conformal Prediction, CP）早在四分之一多世纪前就已被提出，但迄今为止在网络安全领域的应用却少得惊人。我们观察到，CP虽在近年诸多研究中被用作防御手段，但其在进攻性安全（即实施攻击）中的应用却鲜有文献记载。我们针对这一空白展开探索，呈现了在进攻性安全的两个关键领域——隐私保护机器学习与网络流量分析中的初步研究结果。
英文摘要
Despite its introduction more than a quarter century ago, Conformal Prediction (CP) has seen surprisingly few applications to the cyber security world thus far. In particular, we observe that, while CP has been employed as a defensive measure in many recent works, its use for carrying out attacks (i.e., for offensive security) is hard to trace in the literature. We explore this gap, by presenting initial findings in two key areas of offensive security: Privacy-Preserving Machine Learning, and network traffic analysis.
DOI：10.1007/978-3-032-15120-9_14
