Abstract: A computer-implemented method (and structure) includes receiving information. The received information is converted into a strictly hierarchical data format. A precision for a releasing the strictly hierarchical data is calculated based on privacy protection levels and a reward for different precision levels. The strictly hierarchical data is sequentially released at the calculated precision.

Abstract: Aspects of the invention include receiving, using a processing system, an actual user location trajectory that includes a plurality of geographic locations of places visited by a user. It is determined that at least one of the plurality of places visited by the user has been identified as a sensitive place. An obfuscated user location trajectory is created that preserves the privacy of the sensitive places that is consistent with the actual user location trajectory that conforms to a valid street route on a map, preserves spatiotemporal correlation between geographic locations, and is consistent with geographic locations visited by the user in the past. Contents of the obfuscated user location trajectory are output to an application in place of contents of the actual user location trajectory.

Abstract: Aspects of the invention include receiving, using a processing system, a geographic location of a user. A trust level of an application is determined. Based at least in part on the trust level of the application meeting a threshold, the geographic location of the user is transmitted to the application. Based at least in part on the trust level of the application not meeting the threshold, a semantic label associated with the geographic location of the user is determined. The semantic label describes a type of place located at the geographic location of the user. An obfuscated geographic location that preserves the privacy of the geographic location of the user and is associated with a semantic label consistent with the semantic label associated with the geographic location of the user is generated. The obfuscated geographic location is transmitted to the application in place of the geographic location of the user.

Abstract: Aspects of the invention include receiving, using a processing system, an actual user location trajectory that includes a plurality of geographic locations of places visited by a user. It is determined that at least one of the plurality of places visited by the user has been identified as a sensitive place. An obfuscated user location trajectory is created that preserves the privacy of the sensitive places that is consistent with the actual user location trajectory that conforms to a valid street route on a map, preserves spatiotemporal correlation between geographic locations, and is consistent with geographic locations visited by the user in the past. Contents of the obfuscated user location trajectory are output to an application in place of contents of the actual user location trajectory.

Abstract: Techniques for performing root cause analysis in dynamic software testing via probabilistic modeling are provided. In one example, a computer-implemented method comprises initializing, by a system operatively coupled to a processor, a threshold value, a defined probability value, and a counter value. The computer-implemented method also includes, in response to determining, by the system, that a probability value assigned to a candidate payload of one or more candidate payloads exceeds the defined probability value, and in response to determining, by the system, that the counter value exceeds the threshold value: determining, by the system, that a match exists between the candidate payload and an input point based on an application of the candidate payload to the input point resulting in a defined condition, wherein the one or more candidate payloads are represented by population data accessed by the system.

Abstract: Techniques for synthesizing security exploits via self-amplifying deep learning are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a probabilistic model based on an evaluation of one or more first payloads included in a first group of payloads. The computer implemented method can also comprise determining, by the system, based on the probabilistic model, that at least one first payload from the first group of payloads is invalid. Additionally, the computer implemented method can comprise, generating, by the system, a second group of payloads based on removing the at least one invalid first payload from the first group of payloads.

Abstract: Techniques for performing root cause analysis in dynamic software testing via probabilistic modeling are provided. In one example, a computer-implemented method includes initializing, by a system operatively coupled to a processor, a threshold value, a defined probability value, and a counter value. The computer-implemented method also includes, in response to determining, by the system, that a probability value assigned to a candidate payload of one or more candidate payloads exceeds the defined probability value, and in response to determining, by the system, that the counter value exceeds the threshold value: determining, by the system, that a match exists between the candidate payload and an input point based on an application of the candidate payload to the input point resulting in a defined condition, wherein the one or more candidate payloads are represented by population data accessed by the system.

Abstract: Aspects of the invention include receiving, using a processing system, a geographic location of a user. A trust level of an application is determined. Based at least in part on the trust level of the application meeting a threshold, the geographic location of the user is transmitted to the application. Based at least in part on the trust level of the application not meeting the threshold, a semantic label associated with the geographic location of the user is determined. The semantic label describes a type of place located at the geographic location of the user. An obfuscated geographic location that preserves the privacy of the geographic location of the user and is associated with a semantic label consistent with the semantic label associated with the geographic location of the user is generated. The obfuscated geographic location is transmitted to the application in place of the geographic location of the user.

Abstract: A first set of data associated with one or more data stores is received. A distance from a representation of a subset of the first set of data to at least a second representation of another set of data in vector space is identified. In response to the identifying of the distance, the first set of data is anonymized. The anonymizing includes adding noise to at least some of the first set of data.

Abstract: Embodiments of the present disclosure include a method, computer program product, and system for determining to push a data packet to a device. A processor may receive a first data packet. The processor may execute the first data packet in a secure environment. The secure environment may simulate a first state of a device. The device may include a firewall. The processor may determine, from the execution of the first data packet, that the first state changed to a second state. The processor may identify that the second state is a predetermined secure state. The processor may push the data packet to the device in response to identifying that the second state is the predetermined secure state.

Abstract: A path computing method, system, and computer program product, include extracting unpleasant data from a database to create a multivariate spatia-temporal density function, collecting a tolerance level of a user, and computing a path for the user based on the tolerance level and the density function.

Abstract: An output time-series of a cell of a neural network is captured. A subset of a set of data points of the output time-series is consolidated into a singular data point. The singular data point is fitted in a data representation to form a quantified aggregated data point. The quantified aggregated data point is included in an intermediate time-series. Using the intermediate time-series as an input at an intermediate layer of the neural network, an anonymized output time-series is produced from the neural network.

Abstract: A path computing method, system, and computer program product, include extracting unpleasant data from a database to create a multi-variate spatio-temporal density function, collecting a tolerance level of a user, and computing a path for the user based on the tolerance level and the density function.

Abstract: Aspects of the invention include receiving, using a processing system, a geographic location of a user. A trust level of an application is determined. Based at least in part on the trust level of the application meeting a threshold, the geographic location of the user is transmitted to the application. Based at least in part on the trust level of the application not meeting the threshold, a semantic label associated with the geographic location of the user is determined. The semantic label describes a type of place located at the geographic location of the user. An obfuscated geographic location that preserves the privacy of the geographic location of the user and is associated with a semantic label consistent with the semantic label associated with the geographic location of the user is generated. The obfuscated geographic location is transmitted to the application in place of the geographic location of the user.

Abstract: Aspects of the invention include receiving, using a processing system, an actual user location trajectory that includes a plurality of geographic locations of places visited by a user. It is determined that at least one of the plurality of places visited by the user has been identified as a sensitive place. An obfuscated user location trajectory is created that preserves the privacy of the sensitive places that is consistent with the actual user location trajectory that conforms to a valid street route on a map, preserves spatiotemporal correlation between geographic locations, and is consistent with geographic locations visited by the user in the past. Contents of the obfuscated user location trajectory are output to an application in place of contents of the actual user location trajectory.

Abstract: Aspects of the invention include receiving, using a processing system, an actual user location trajectory that includes a plurality of geographic locations of places visited by a user. It is determined that at least one of the plurality of places visited by the user has been identified as a sensitive place. An obfuscated user location trajectory is created that preserves the privacy of the sensitive places that is consistent with the actual user location trajectory that conforms to a valid street route on a map, preserves spatiotemporal correlation between geographic locations, and is consistent with geographic locations visited by the user in the past. Contents of the obfuscated user location trajectory are output to an application in place of contents of the actual user location trajectory.

Abstract: Aspects of the invention include receiving, using a processing system, a geographic location of a user. A trust level of an application is determined. Based at least in part on the trust level of the application meeting a threshold, the geographic location of the user is transmitted to the application. Based at least in part on the trust level of the application not meeting the threshold, a semantic label associated with the geographic location of the user is determined. The semantic label describes a type of place located at the geographic location of the user. An obfuscated geographic location that preserves the privacy of the geographic location of the user and is associated with a semantic label consistent with the semantic label associated with the geographic location of the user is generated. The obfuscated geographic location is transmitted to the application in place of the geographic location of the user.

Abstract: A computer-implemented method (and structure) includes receiving information. The received information is converted into a strictly hierarchical data format. A precision for a releasing the strictly hierarchical data is calculated based on privacy protection levels and a reward for different precision levels. The strictly hierarchical data is sequentially released at the calculated precision.

Abstract: A path computing method, system, and computer program product, include extracting unpleasant data from a database to create a multi-variate spatio-temporal density function, collecting a tolerance level of a user, and computing a path for the user based on the tolerance level and the density function.

Abstract: Techniques for synthesizing security exploits via self-amplifying deep learning are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a probabilistic model based on an evaluation of one or more first payloads included in a first group of payloads. The computer implemented method can also comprise determining, by the system, based on the probabilistic model, that at least one first payload from the first group of payloads is invalid. Additionally, the computer implemented method can comprise, generating, by the system, a second group of payloads based on removing the at least one invalid first payload from the first group of payloads.