• Publications
  • Influence
Mondrian Multidimensional K-Anonymity
TLDR
A new multidimensional model is proposed, which provides an additional degree of flexibility not seen in previous (single-dimensional) approaches, which leads to higher-quality anonymizations, as measured both by general-purpose metrics and more specific notions of query answerability. Expand
Incognito: efficient full-domain K-anonymity
TLDR
A set of algorithms for producing minimal full-domain generalizations are introduced, and it is shown that these algorithms perform up to an order of magnitude faster than previous algorithms on two real-life databases. Expand
Privacy wizards for social networking sites
TLDR
A template for the design of a social networking privacy wizard based on an active learning paradigm called uncertainty sampling, which is able to recommend high-accuracy privacy settings using less user input than existing policy-specification tools. Expand
Workload-aware anonymization
TLDR
A suite of anonymization algorithms that produce an anonymous view based on a target class of workloads, consisting of one or more data mining tasks, as well as selection predicates are provided. Expand
Limiting Disclosure in Hippocratic Databases
TLDR
Through a comprehensive set of performance experiments, it is shown that the cost of privacy enforcement is small, and scalable to large databases. Expand
Workload-aware anonymization techniques for large-scale datasets
TLDR
This article provides a suite of anonymization algorithms that incorporate a target class of workloads, consisting of one or more data mining tasks as well as selection predicates, and describes two extensions that allow the algorithms to scale to datasets much larger than main memory. Expand
Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge
TLDR
A novel multidimensional approach to quantifying an adversary's external knowledge is proposed, which allows the publishing organization to investigate privacy threats and enforce privacy requirements in the presence of various types and amounts of external knowledge. Expand
GraSS: Graph Structure Summarization
TLDR
This paper proposes a formal semantics for answering queries on summaries of graph structures based on a random worlds model, and shows that important graph-structure queries can be answered efficiently and in closed form using these semantics. Expand
The PViz comprehension tool for social network privacy settings
TLDR
PViz allows the user to understand the visibility of her profile according to automatically-constructed, natural sub-groupings of friends, and at different levels of granularity, an interface and system that corresponds more directly with how users model groups and privacy policies applied to their networks. Expand
Multidimensional K-Anonymity
TLDR
It is proved that optimal multidimensional anonymization is NP-hard (like previous k-anonymity models), but a simple, scalable, greedy algorithm is introduced that produces anonymizations that are a constantfactor approximation of optimal. Expand
...
1
2
3
4
5
...