Inference attack

An Inference Attack is a data mining technique performed by analyzing data in order to illegitimately gain knowledge about a subject or database.^[1] A subject's sensitive information can be considered as leaked if an adversary can infer its real value with a high confidence.^[2] This is an example of breached information security. An Inference attack occurs when a user is able to infer from trivial information more robust information about a database without directly accessing it.^[3] The object of Inference attacks is to piece together information at one security level to determine a fact that should be protected at a higher security level.^[4]

While inference attacks were originally discovered as a threat in statistical databases,^[5] today they also pose a major privacy threat in the domain of mobile and IoT sensor data. Data from accelerometers, which can be accessed by third-party apps without user permission in many mobile devices,^[6] has been used to infer rich information about users based on the recorded motion patterns (e.g., driving behavior, level of intoxication, age, gender, touchscreen inputs, geographic location).^[7] Highly sensitive inferences can also be derived, for example, from eye tracking data,^[8][9] smart meter data^[10][11] and voice recordings (e.g., smart speaker voice commands).^[12]