Government agencies always need to carefully consider potential risks of disclosure whenever they publish statistics based on their data or give external researchers access to the collected data. For this reason, research on disclosure avoiding techniques has a long tradition at statistical agencies. In this context, the promise of formal privacy guarantees offered by concepts such as differential privacy seem to be the panacea enabling the agencies to exactly quantify and control the privacy loss incurred by any data release. Still, despite the excitement in academia and industry, most agencies-with the prominent exception of the U.S. Census Bureau-have been reluctant to even consider the concept for their data release strategy. This paper aims to shed some light on potential reasons for this. We argue that the requirements when implementing differential privacy approaches at government agencies are often fundamentally different from the requirements in industry. This raises many challenging problems and open questions that still need to be addressed before the concept might be used as an overarching principle when sharing data with the public. The paper will not offer any solutions to these challenges. Instead, we hope to stimulate some collaborative research efforts, as we believe that many of the problems can only be addressed by inter-disciplinary collaborations.
翻译:政府各机构在根据数据公布统计数据或让外部研究人员查阅所收集的数据时,总是需要仔细考虑披露的潜在风险。因此,统计机构对避免披露技术的研究具有悠久的传统。在这方面,差异隐私等概念所提供的正式隐私保障承诺似乎是使各机构能够精确量化和控制任何数据发布造成的隐私损失的灵丹妙药。尽管学术界和工业界感到兴奋,但大多数机构(美国人口普查局除外)一直不愿意考虑其数据发布战略的概念。本文旨在说明这方面的潜在原因。我们认为,在政府机构实施差异隐私做法时的要求往往与行业的要求大不相同。这提出了许多难题和开放的问题,在将这一概念用作与公众分享数据的总体原则之前,还需要加以解决。该文件不会为这些挑战提供任何解决办法。相反,我们希望鼓励一些合作研究努力,因为我们认为许多问题只能通过跨学科合作来解决。