King's College London

Research portal

Towards String Sanitization

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations
Subtitle of host publicationAIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT, Rhodes, Greece, May 25-27, 2018, Proceedings
PublisherSpringer
Pages200-210
DOIs
Accepted/In press20 Mar 2018
E-pub ahead of print22 May 2018
Published2018
EventAIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT - Rhodes, Greece
Duration: 25 May 201827 May 2018

Conference

ConferenceAIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT
CountryGreece
CityRhodes
Period25/05/201827/05/2018

King's Authors

Abstract

An increasing number of applications, in domains ranging from bio-medicine to business and to pervasive computing, feature data represented as along sequence of symbols (string). Sharing these data, however, may lead to thedisclosure of sensitive patterns which are represented as substrings and modelconfidential information. Such patterns may model, for example, confidentialmedical knowledge, business secrets, or signatures of activity patterns that mayrisk the privacy of smart-phone users. In this paper, we study the novel problem of concealing a given set of sensitive patterns from a string. Our approach is based on injecting a minimal level of uncertainty to the string, by replacing selected symbols in the string with a symbol "*" that is interpreted as any symbol from the set of possible symbols that may appear in the string. To realize our approach, we propose an algorithm that efficiently detects occurrences of the sensitive patterns in the string and then sanitizes these sensitive patterns. We also present a preliminary set of experiments to demonstrate the effectiveness and efficiency of our algorithm.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454