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This work presents a systematic study of the problem of protecting general proximity privacy, with findings applicable to most existing data models. Our contributions are multi-folded: we highlighted and formulated proximity privacy breaches in a data-model-neutral manner; we proposed a new privacy principle (epsiv,delta)k-dissimilarity, with theoretically guaranteed protection against linking attacks...
User profile data (for example, age and sex) is usually self-reported by users, so it is prone to human errors or biases. For example, a user can be reluctant to provide a company with private information such as his/her actual age upon subscription, thus the user either does not fill in the age column or put in some random numbers to avoid unwanted privacy intrusion. However, inaccurate or uncertain...
Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured...
Directions search returns the shortest path from a source to a destination on a road network. However, the search interests of users may be exposed to the service providers, thus raising privacy concerns. For instance, a path query that finds a path from a resident address to a clinic may lead to a deduction about "who is related to what disease". To protect user privacy from accessing directions...
Database developers today use data access APIs such as ADO.NET to execute SQL queries from their application. These applications often have security problems such as SQL injection vulnerabilities and performance problems such as poorly written SQL queries. However today's compilers have little or no understanding of data access APIs or DBMS, and hence the above problems can go undetected until much...
We study the following problem: A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data is leaked and found in an unauthorized place (e.g., on the Web or somebody's laptop). The distributor must assess the likelihood that the leaked data came from one or more agents, as opposed to having been independently gathered by other means. We propose...
Location cloaking has been proposed and well studied to protect user privacy. It blurs the accurate user location (i.e., a point with coordinates) and replaces it with a well-shaped cloaked region (usually a circle or a rectangle). However, to obtain such a cloaked region, all existing cloaking algorithms require to know the accurate locations of all users. Since such information is exactly what the...
The following topics are dealt with: data privacy; World Wide Web; data security; data uncertainty; data mining; query optimization; XML; social networking; and data warehousing.
In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster operation. Unfortunately, today's large-scale cluster systems are still vulnerable to various software and hardware problems. System administrators are often overwhelmed by the tasks of correcting various system anomalies such...
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