The extensive collection and processing of personal information in big data analytics has
given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling …

In recent years, privacy-preserving data mining has been studied extensively, because of
the wide proliferation of sensitive information on the internet. A number of algorithmic …

摘要批处理, 流式计算和机器学习等分布式的大数据计算环境在云上的广泛部署与应用,
为云用户带来了极大的便利, 但随之带来的隐私数据泄露事件愈演愈烈. 如何在这种云上部署的 …

Privacy is an important issue when one wants to make use of data that involves individuals'
sensitive information. Research on protecting the privacy of individuals and the …

A vast amount of valuable data is produced and is becoming available for analysis as a
result of advancements in smart cyber-physical systems. The data comes from various …

The proper protection of data privacy is a complex task that requires a careful analysis of
what actually has to be kept private. Several definitions of privacy have been proposed over …

The widespread use of the Internet of Things (IoT) has raised many concerns, including the
protection of private information. Existing privacy preservation methods cannot provide a …

Privacy Preserving Data Mining (PPDM) addresses the problem of developing accurate
models about aggregated data without access to precise information in individual data …

In this paper we study the trade-offs between time series compressibility and partial
information hiding and their fundamental implications on how we should introduce …

Research on the anonymization of static data has made great progress in recent years.
Generalization and suppression are two common technologies for quasi-identifiers' …