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.
|Title of host publication||Artificial Intelligence Applications and Innovations|
|Subtitle of host publication||AIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT, Rhodes, Greece, May 25-27, 2018, Proceedings|
|Publication status||Published - 2018|
|Event||AIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT - Rhodes, Greece|
Duration: 25 May 2018 → 27 May 2018
|Conference||AIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT|
|Period||25/05/2018 → 27/05/2018|