Publicación: PROTECTING QUERY PRIVACY THROUGH SEMANTIC CACHING IN LOCATION-BASED SERVICES
Fecha
2020
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Editor
COLLABORATIVE TECHNOLOGIES AND DATA SCIENCE IN ARTIFICIAL INTELLIGENCE APPLICATIONS
Resumen
WE PLAN TO ADDRESS THE PROBLEM OF PROCESSING LOCATION-BASED QUERIES (LBQ) IN A MANET FOR PRESERVING QUERY PRIVACY AS MUCH AS POSSIBLE. OUR IDEA IS THAT MOBILE USERS WILL FIRST ASK THEMSELVES FOR SOLVING A QUERY BEFORE ANY USER DECIDES TO SUBMIT ITS QUERY TO AN UNTRUSTED LBS. OUR FIRST GOAL IS TO DEFINE A COLLABORATIVE CACHING STRATEGY TO BE RUN BY THE MOBILE USERS THEMSELVES THAT EXPLOIT THE GEOGRAPHIC AND SEMANTIC SIMILARITIES AMONG THE LBQS TO PERFORM EFFICIENT PROCESSING OF LCQS. OUR SECOND GOAL
TO PROTECT A USER?S QUERY PRIVACY WHEN ANY USER SUBMITS AN LBQ TO THE LBS; WE ARE PLANNING TO DEVELOP A DISTRIBUTED ALGORITHM TO PROVIDE L-DIVERSITY ONLY WHEN THIS PROTECTION IS USEFUL. EXISTING CACHING TECHNIQUES FOR MANET DO NOT EXPLOIT SEMANTIC AND GEOGRAPHIC SIMILARITIES AMONG THE LBQS, AND THEY ASSUME MOBILE USERS HAVE ACCESS TO SOME STORAGE INFRASTRUCTURE TO MAINTAIN GLOBAL INFORMATION TO COMPUTE L-DIVERSITY.
