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Elisabeth Wehrle

dblp:76/1228 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1982
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection
confidentiality protection
0.011982
Memoryless Inference Controls for Statistical Databases · S&P 1982
Privacy and data protection › statistical database privacy
inference control
0.011982
Memoryless Inference Controls for Statistical Databases · S&P 1982
Privacy and data protection
statistical database privacy
0.011982
Memoryless Inference Controls for Statistical Databases · S&P 1982
YearPublicationVenuePosition
1982 Memoryless Inference Controls for Statistical Databases
abstract
Statistical databases aim to provide frequencies, averages, and other statistics about groups of persons (or organizations), while protecting the confidentiality of the individuals represented in the database. This objective is difficult to achieve, as users of statistical databases have a host of inference techniques at their disposal for retrieving information about identifiable persons (e.g., see [36,15,16,14,17,26, 31].) There are two broad categories of inference controls: controls that place restrictions on the set of allowable statistics, and controls that add noise to the data or to the released statistics. This paper focuses on restriction techniques.
Dorothy E. Denning, Jan Schlörer, Elisabeth Wehrle
S&P3