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Differential privacy

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更新于 : Mar 29, 2017
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
Mar 2017
Assess ? 在了解它将对你的企业产生什么影响的前提下值得探索

It has long been known that "anonymized" bulk data sets can reveal information about individuals, especially when multiple data sets are cross-referenced together. With increasing concern over personal privacy, some companies—including Apple and Google—are turning to differential privacy techniques in order to improve individual privacy while retaining the ability to perform useful analytics on large numbers of users. Differential privacy is a cryptographic technique that attempts to maximize the accuracy of statistical queries from a database while minimizing the chances of identifying its records. These results can be achieved by introducing a low amount of "noise" to the data, but it's important to note that this is an ongoing research area. Apple has announced plans to incorporate differential privacy into its products—and we wholeheartedly applaud its commitment to customers' privacy—but the usual Apple secrecy has left some security experts scratching their heads. We continue to recommend Datensparsamkeit as an alternative approach: simply storing the minimum data you actually need will achieve better privacy results in most cases.

Nov 2016
Assess ? 在了解它将对你的企业产生什么影响的前提下值得探索

It has long been known that "anonymized" bulk data sets can reveal information about individuals, especially when multiple data sets are cross-referenced together. With increasing concern over personal privacy, some companies—including Apple and Google—are turning to differential privacy techniques in order to improve individual privacy while retaining the ability to perform useful analytics on large numbers of users. Differential privacy is a cryptographic technique that attempts to maximize the accuracy of statistical queries from a database while minimizing the chances of identifying its records. These results can be achieved by introducing a low amount of "noise" to the data, but it’s important to note that this is an ongoing research area. Apple has announced plans to incorporate differential privacy into its products—and we wholeheartedly applaud its commitment to customers' privacy—but the usual Apple secrecy has left some security experts scratching their heads. We continue to recommend Datensparsamkeit as an alternative approach: simply storing the minimum data you actually need will achieve better privacy results in most cases.

发布于 : Nov 07, 2016

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