Publication | Closed Access
Detecting privacy leaks using corpus-based association rules
61
Citations
17
References
2008
Year
Unknown Venue
Privacy ProtectionEngineeringInformation SecurityInformation ForensicsAssociation Rule MiningCorpus LinguisticsText MiningNatural Language ProcessingInformation RetrievalData ScienceData MiningComputational LinguisticsPrivacy SystemReference CorpusKnowledge DiscoveryData PrivacyTerminology ExtractionComputer ScienceInference DetectionInformation ExtractionPrivacyPrivacy LeakageData SecurityWeb MiningAssociation RuleKeyword ExtractionPrivacy Leaks
Detecting inferences in documents is critical for ensuring privacy when sharing information. In this paper, we propose a refined and practical model of inference detection using a reference corpus. Our model is inspired by association rule mining: inferences are based on word co-occurrences. Using the model and taking the Web as the reference corpus, we can find inferences and measure their strength through web-mining algorithms that leverage search engines such as Google or Yahoo!.
| Year | Citations | |
|---|---|---|
Page 1
Page 1