Abstract: An approach is provided for data-preserving trajectory anonymization. The approach involves, for example, processing a plurality of location trajectories to determine one or more exchange twists. The plurality of location trajectories are respectively a sequence of locations points determined by a location sensor of a device, and the one or more exchange twists are one or more locations at which at least two trajectories of the plurality of location trajectories match based on a matching criterion. The approach also involves initiating a swapping of one or more trajectory identifiers among the plurality of location trajectories based on the one or more exchange twists to generate anonymized trajectory data. The approach further involves providing the anonymized trajectory data as an output to a location-based service.

Abstract: An approach is provided for probe trajectory anonymization using based on a negative gap. The approach involves, for example, receiving a probe trajectory generated from at least one sensor of a probe device. The approach also involves processing the probe trajectory to segment the probe trajectory into a first subtrajectory and a second subtrajectory based on a negative gap between the first subtrajectory and the second subtrajectory. The negative gap specifies an amount of overlap between the end of the first subtrajectory and the beginning of the second subtrajectory. The approach further involves assigning a first pseudonym (e.g., a first new probe identifier) to the first subtrajectory, and a second pseudonym (e.g., a second new probe identifier) to the second subtrajectory. The approach then involves providing the first subtrajectory and the second subtrajectory as a trajectory anonymization output.

Abstract: An approach is provided for device-side probe trajectory anonymization based on negative gapping. The approach involves, for example, collecting a probe trajectory stream from a sensor of a probe device, wherein the probe trajectory stream comprises a time-sequence of location data points representing a sensed movement of the probe device. The approach also involves generating a plurality of subtrajectory streams from the probe trajectory stream. The approach further involves processing the plurality of subtrajectory streams to create a negative gap between the plurality of subtrajectory streams. The approach further involves providing the plurality of subtrajectory streams as an output in place of the probe trajectory.

Abstract: A method, apparatus and computer program product are provided to determine a semantic privacy index that quantifies the risk associated with re-identification of a trajectory following anonymization of the trajectory. In the context of a method, information regarding a trajectory is received. After the trajectory has been map matched to a portion of a road network, the method associates contextual information comprising one or more map features with the trajectory. The method also provides the information regarding the trajectory and the contextual information comprising the one or more map features to a risk estimation model in order to generate the semantic privacy index.

Abstract: An approach is disclosed for estimating population density change where dynamic signals are not available or are not dense enough to be representative. The approach involves, for example, determining map features of a first map space. The approach also involves identifying partitions of the first map space based on the identified partitions (i) having features that are substantially similar, and (ii) having respective change functions that are substantially similar. The approach further involves determining an estimated change function based on one or more of the respective change functions that are substantially similar and that are associated with the first map space. The approach further involves using the estimated change function for at least one partition of a second map space based on the at least one partition of the second map space and at least one map partition of the first map space having map features that are substantially similar.

Abstract: An approach is provided for data-preserving trajectory anonymization. The approach involves, for example, processing a plurality of location trajectories to determine one or more exchange twists. The plurality of location trajectories are respectively a sequence of locations points determined by a location sensor of a device, and the one or more exchange twists are one or more locations at which at least two trajectories of the plurality of location trajectories match based on a matching criterion. The approach also involves initiating a swapping of one or more trajectory identifiers among the plurality of location trajectories based on the one or more exchange twists to generate anonymized trajectory data. The approach further involves providing the anonymized trajectory data as an output to a location-based service.

Abstract: An approach is provided for probe trajectory anonymization using based on a negative gap. The approach involves, for example, receiving a probe trajectory generated from at least one sensor of a probe device. The approach also involves processing the probe trajectory to segment the probe trajectory into a first subtrajectory and a second subtrajectory based on a negative gap between the first subtrajectory and the second subtrajectory. The negative gap specifies an amount of overlap between the end of the first subtrajectory and the beginning of the second subtrajectory. The approach further involves assigning a first pseudonym (e.g., a first new probe identifier) to the first subtrajectory, and a second pseudonym (e.g., a second new probe identifier) to the second subtrajectory. The approach then involves providing the first subtrajectory and the second subtrajectory as a trajectory anonymization output.

Abstract: An approach is provided for device-side probe trajectory anonymization based on negative gapping. The approach involves, for example, collecting a probe trajectory stream from a sensor of a probe device, wherein the probe trajectory stream comprises a time-sequence of location data points representing a sensed movement of the probe device. The approach also involves generating a plurality of subtrajectory streams from the probe trajectory stream. The approach further involves processing the plurality of subtrajectory streams to create a negative gap between the plurality of subtrajectory streams. The approach further involves providing the plurality of subtrajectory streams as an output in place of the probe trajectory.

Abstract: A method, apparatus, and computer program product are provided for estimating parking availability in an area based on probe data points in response to a request while maintaining data privacy. A method may include: receiving probe data associated with a plurality of vehicles; determining, from the probe data, location information, parking event information, and a timestamp; receiving a parking availability query, where the parking availability query includes a location; generating and transmitting a request for parking availability information corresponding to the location; receiving a plurality of partial results in response to the request for parking availability information corresponding to the location; determining, from the plurality of partial results, parking availability information corresponding to the location; and providing the parking availability information corresponding to the location responsive to the parking availability query.

Abstract: A method, apparatus and computer program product are provided to determine a semantic privacy index that quantifies the risk associated with re-identification of a trajectory following anonymization of the trajectory. In the context of a method, information regarding a trajectory is received. After the trajectory has been map matched to a portion of a road network, the method associates contextual information comprising one or more map features with the trajectory. The method also provides the information regarding the trajectory and the contextual information comprising the one or more map features to a risk estimation model in order to generate the semantic privacy index.