Abstract: A method of limiting data usage for certified purposes by using functional encryption, comprising: receiving from a software publisher an application code and declared privacy information, the declared privacy information specifies at least one declared usage for at least one data type; analyzing the application's usage of data collected by the application, to identify an actual usage of the at least one data type by a function; identifying when the actual usage is compliant with the at least one declared usage according to the analysis; in response to the identification, creating a pair of a public key and a master private key; creating a function private key for the function using the master private key; and sending the function private key to the software publisher to be used for operating the function on data which is encrypted using the public key.

Abstract: A method of limiting data usage for certified purposes by using functional encryption, comprising: receiving from a software publisher an application code and declared privacy information, the declared privacy information specifies at least one declared usage for at least one data type; analyzing the application's usage of data collected by the application, to identify an actual usage of the at least one data type by a function; identifying when the actual usage is compliant with the at least one declared usage according to the analysis; in response to the identification, creating a pair of a public key and a master private key; creating a function private key for the function using the master private key; and sending the function private key to the software publisher to be used for operating the function on data which is encrypted using the public key.

Abstract: A method, apparatus and a product for data generalization for predictive models. The method comprising: based on a labeled dataset, determining a plurality of buckets, each of which has an associated label; determining a plurality of clusters, grouping similar instances in the same bucket; based on the plurality of clusters, determining an alternative set of features comprising a set of generalized features, wherein each generalized feature corresponds to a cluster of the plurality of clusters, wherein a generalized feature that corresponds to a cluster is indicative of the instance being mapped to the corresponding cluster; obtaining a second instance; determining a generalized second instance that comprises a valuation of the alternative set of features for the second instance; and based on the generalized second instance, determining a label for the second instance.

Abstract: A method, apparatus and a product for data generalization for predictive models. The method comprising: obtaining a training dataset that comprises a plurality of training instances and predicted labels thereof, wherein each training instance is a valuation of a set of features, wherein the set of features comprises a feature having a domain, wherein the predicted label of each training instance is a label predicted thereto by a predictive model; training an auxiliary model using the training dataset; based on the auxiliary model, determining an alternative set of features that is a generalization of the set of features, wherein the alternative set of features comprises a generalized feature having a generalized domain, wherein each value in the generalized domain corresponds to one or more values in the domain; obtaining a generalized instance having a valuation of the alternative set of features; and determining a label for the generalized instance.