论文标题
压缩分析和隐私的未来
Compressive analysis and the Future of Privacy
论文作者
论文摘要
压缩分析是将原始数据映射到其较小表示的技术家族的名称。在很大程度上，这包括数据压缩，数据编码，数据加密和哈希。在本文中，我们分析了这些技术在实现可自定义的个人隐私方面的前景。我们要求可怕的需要建立隐私保护框架和政策，以及个人如何在直观的数字服务合奏及其隐私的舒适度之间取消权衡。我们检查了当前正在实施的技术，并提出了压缩分析的关键优势。
Compressive analysis is the name given to the family of techniques that map raw data to their smaller representation. Largely, this includes data compression, data encoding, data encryption, and hashing. In this paper, we analyse the prospects of such technologies in realising customisable individual privacy. We enlist the dire needs to establish privacy preserving frameworks and policies and how can individuals achieve a trade-off between the comfort of an intuitive digital service ensemble and their privacy. We examine the current technologies being implemented, and suggest the crucial advantages of compressive analysis.
