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New Frameworks for Detecting and Minimizing Information Leakage in Anonymized Network Data

机译：用于检测和最小化匿名网络数据中信息泄漏的新框架

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The availability of realistic network data plays a significant role in fostering collaboration and ensuring U.S. technical leadership in network security research. Unfortunately, a host of technical, legal, policy, and privacy issues limit the ability of operators to produce data sets for information security testing. In an effort to help overcome these limitations, the Department of Homeland Security (DHS) has endeavored to create a national repository of network traces under the Protected Repository for the Defense of Infrastructure against Cyber Threats (PREDICT) program. A key technique used in this program to assure low-risk, high-value data is that of trace anonymization- a process of sanitizing data before release so that information of concern cannot be extracted. Indeed, many believe that proven anonymization techniques are the missing link that will enable cyber security researchers to tap real Internet traffic and develop effective solutions tailored to current risks.

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