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.
[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).