Methods and systems for automated anonymous crowdsourcing of characterized device behaviors

摘要

Methods, and devices implementing the methods, use device-specific classifiers in a privacy-preserving behavioral monitoring and analysis system for crowd-sourcing of device behaviors. Diverse devices having varying degrees of “smart” capabilities may monitor operational behaviors. Gathered operational behavior information may be transmitted to a nearby device having greater processing capabilities than a respective collecting device, or may be transmitted directly to an “always on” device. The behavior information may be used to generate behavior vectors, which may be analyzed for anomalies. Vectors containing anomaly flags may be anonymized to remove any user-identifying information and subsequently transmitted to a remote recipient such as a service provider or device manufacture. In this manner, operational behavior information may be gathered about different devices from a large number of users, to obtain statistical analysis of operational behavior for specific makes and models of devices, without divulging personal information about device users.