Agility maneuvers to mitigate inference attacks on sensed location data

摘要: Sensed location data is subject to inference attacks by cybercriminals that aim obtain the exact position of sensitive locations, such as victim's home and work launch a variety different attacks. Various Location-Privacy Preserving Mechanisms (LPPMs) exist reduce probability success on data. However, mechanisms have been shown be less effective when adversary informed protection mechanism adopted, also known white-box We propose novel approach makes use targeted agility maneuvers more robust defense against Agility are systematically activated in response specific system events rapidly continuously control rate change configurations increase diversity space readings, which would decrease an adversary. Experimental results, performed real set, show adoption reduces 2.68% average, compared 56.92% using state-of-the-art LPPMs.