Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Certain embodiments of this disclosure include methods and devices for adjusting the precision of location information. According to one embodiment, a method is provided. The method may include: obtaining a request for location information from an application; determining that the location information needs to be adjusted; obtaining the location information; adjusting the location information, wherein the adjusting includes: (i) adding noise to the location information to obtain noisy location information, (ii) discretizing the noisy location information to obtain discretized location information, and (iii) hysteresizing the discretized location information to obtain adjusted location information. The adjusted location information may then be provided to the requesting application.
Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.
Abstract:
Methods and systems for grouping computing devices together based on the devices being colocated with one another or being associated with complementary usage contexts, and then using the location or usage context of one device in the group to estimate the location or usage context of another device in the group are described. An example method may include receiving first sensor data from sensors of a first computing device; receiving second sensor data from sensors of a second computing device; determining, based on the received sensor data, that the first and second computing devices are colocated with one another; identifying, based on the first sensor data, a context associated with the first computing device; and determining, based at least in part on the context associated with the first computing device, a context associated with the second computing device.
Abstract:
Methods and systems for grouping computing devices together based on the devices being colocated with one another or being associated with complementary usage contexts, and then using the location or usage context of one device in the group to estimate the location or usage context of another device in the group are described. An example method may include receiving first sensor data from sensors of a first computing device; receiving second sensor data from sensors of a second computing device; determining, based on the received sensor data, that the first and second computing devices are colocated with one another; identifying, based on the first sensor data, a context associated with the first computing device; and determining, based at least in part on the context associated with the first computing device, a context associated with the second computing device.