Abstract: A privacy-related consent extension and data processing system may be configured to automatically extend one or more privacy-related consents for a user of a first computing device to a second computing device. In various embodiments, the system is configured to provide a computer-readable indicium (indicia) on a previously unknown computing device upon initiation of a transaction between a user and an entity collecting and processing privacy data. In response to a user using a known computing device to scan the computer-readable indicium, in various embodiments, the system may provide the ability to share user consent data provided by the first known device to the second unknown device, allowing the user to provide consent without manually re-entering privacy and consent preferences.

Abstract: A privacy-related consent extension and data processing system may be configured to automatically extend one or more privacy-related consents for a user of a first computing device to a second computing device. In various embodiments, the system is configured to provide a computer-readable indicium(indicia) on a previously unknown computing device upon initiation of a transaction between a user and an entity collecting and processing privacy data. In response to a user using a known computing device to scan the computer-readable indicium, in various embodiments, the system may provide the ability to share user consent data provided by the first known device to the second unknown device, allowing the user to provide consent without manually re-entering privacy and consent preferences.

Abstract: A mobile application privacy analysis system is described, where the system scans a mobile device to identify files associated with a particular SDK and generates a tokenized name for the SDK. The tokenized name includes tokens representing the SDK vendor and one or more functions of the SDK. Using the tokenized name, the system then determines corresponding categories for each functionality token and score for each such category. Based on the scores, the system determines the most significant category and assigns that category to the SDK for use in privacy analysis. The system may also, or instead, determine a vendor category using the vendor token and assign that category to the SDK. Weighting factors may be applied to the scores for the categories associated with the functionality tokens and vendor tokens.

Abstract: A mobile application privacy analysis system is described, where the system scans a mobile device to identify files associated with a particular SDK and generates a tokenized name for the SDK. The tokenized name includes tokens representing the SDK vendor and one or more functions of the SDK. Using the tokenized name, the system then determines corresponding categories for each functionality token and score for each such category. Based on the scores, the system determines the most significant category and assigns that category to the SDK for use in privacy analysis. The system may also, or instead, determine a vendor category using the vendor token and assign that category to the SDK. Weighting factors may be applied to the scores for the categories associated with the functionality tokens and vendor tokens.

Abstract: A mobile application privacy analysis system is described, where the system scans a mobile device to identify files associated with a particular SDK and generates a tokenized name for the SDK. The tokenized name includes tokens representing the SDK vendor and one or more functions of the SDK. Using the tokenized name, the system then determines corresponding categories for each functionality token and score for each such category. Based on the scores, the system determines the most significant category and assigns that category to the SDK for use in privacy analysis. The system may also, or instead, determine a vendor category using the vendor token and assign that category to the SDK. Weighting factors may be applied to the scores for the categories associated with the functionality tokens and vendor tokens.

Abstract: A mobile application privacy analysis system is described, where the system scans a mobile device to identify files associated with a particular SDK and generates a tokenized name for the SDK. The tokenized name includes tokens representing the SDK vendor and one or more functions of the SDK. Using the tokenized name, the system then determines corresponding categories for each functionality token and score for each such category. Based on the scores, the system determines the most significant category and assigns that category to the SDK for use in privacy analysis. The system may also, or instead, determine a vendor category using the vendor token and assign that category to the SDK. Weighting factors may be applied to the scores for the categories associated with the functionality tokens and vendor tokens.

Abstract: A mobile application privacy analysis system is described, where the system scans a mobile device to identify files associated with a particular SDK and generates a tokenized name for the SDK. The tokenized name includes tokens representing the SDK vendor and one or more functions of the SDK. Using the tokenized name, the system then determines corresponding categories for each functionality token and score for each such category. Based on the scores, the system determines the most significant category and assigns that category to the SDK for use in privacy analysis. The system may also, or instead, determine a vendor category using the vendor token and assign that category to the SDK. Weighting factors may be applied to the scores for the categories associated with the functionality tokens and vendor tokens.