Abstract: A computer system implements a method to provide secure multiparty location based services. A user input is received from a user device of a user. The user input contains user location information. Based on the location information, a model is retrieved. The model is a constraint satisfaction problem defined by a set of variables and mapping functions. The set of variables and mapping functions are into multiple shares. Each share is distributed to one of agents in finding a solution to the constraint satisfaction problem. Once a solution is computed, a demographic profile is predicted based on the solution. The solution does not contain the user location information.

Abstract: A computer system implements a method to provide a class membership probability prediction based on collected usage data from a user device of a user. After device usage data, which contains location information, is collected from the user device, the collected usage data is processed to generate a predictive model by utilizing a machine learning algorithm. In response to a user input, a class membership probability estimation is produced by processing the user input through the probability predictive model. The resulted class membership probability estimation can then be used as a prediction of a demographic profile of the user.

Abstract: A system for shredding data in NAND memory can comprise a database and a device controller. The database may be configured to store the data. The device controller may be configured to receive a shred command, overwrite the data within at least a portion of the NAND memory pursuant to the shred command, generate a flag that indicates the at least the portion of the NAND memory was overwritten, and store the flag in a secure storage.