Abstract: In various embodiments, a Data Model Adaptive Execution System may be configured to take one or more suitable actions to remediate an identified risk in view of one or more regulations (e.g., one or more legal regulations, one or more binding corporate rules, etc.). For example, in order to ensure compliance with one or more standards related to the collection and/or storage of personal data, an entity may be required to modify one or more aspects of a way in which the entity collects, stores, and/or otherwise processes personal data (e.g., in response to a change in a legal or other requirement). In order to identify whether a particular change or other risk trigger requires remediation, the system may be configured to assess a relevance of the risk posed by the risk and identify one or more processing activities or data assets that may be affected by the risk.

Abstract: In various embodiments, a data processing consent capture system may be configured to prompt the data subject to consent to one or more types of data processing (e.g., to provide a desired consent) in response to identifying particular cookies (e.g., or types of data processing) that a data subject has not consented to. The system may, for example, substantially automatically prompt the data subject to consent for one or more particular types of data processing in response to determining that the user (e.g., data subject) has requested that a website or other system perform one or more functions that are not possible without a particular type of consent from the data subject. The system may, for example, prompt the user to consent in time for a certain interaction with the website, application, etc.

Abstract: In various embodiments, a personal data processing system may require guardian consent (e.g., parental consent) for a data subject in order to collect, store, and or process the subject's personal data. The system may prompt the data subject to initiate a request for guardian consent or the system may initiate a request for guardian consent without initiation from the data subject (e.g., in the background of a transaction). In some embodiments, the system may require guardian consent when a data subject is under the age for valid consent for the particular type of personal data that will be collected as part of a particular transaction. Data processing systems may generate and store one or more consent records memorializing valid consent for data processing from data subjects and/or from guardians on their behalf (e.g., in the case of a minor data subject).

Abstract: Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

Abstract: In particular embodiments, computer-implemented data processing, systems, and method configured to: receive a request to initiate a transaction between an entity and a data subject, generate (i) a consent receipt for the transaction comprising at least a unique subject identifier and a unique consent receipt key and (ii) a unique cookie to identify the data subject's transaction initiated by the data subject, store the consent receipt for the transaction and the unique cookie, receive a data subject access request from the data subject, verify an identity of the data subject based at least in part on the unique cookie process the request, process the request by identifying one or more pieces of personal data associated with the data subject, and taking one or more actions based at least in part on the data subject access request.

Abstract: In particular embodiments, a Personal Data Deletion System is configured to: (1) at least partially automatically identify and delete personal data that an entity is required to erase under one or more of the conditions discussed above; and (2) perform one or more data tests after the deletion to confirm that the system has, in fact, deleted any personal data associated with the data subject. The system may, for example, be configured to test to ensure the data has been deleted by: (1) submitting a unique token of data through a form to a system; (2) in response to passage of an expected data retention time, test the system by calling into the system after the passage of the data retention time to search for the unique token.

Abstract: Data stored on a data asset may be migrated to another data asset while maintaining compliance to applicable regulations. A data asset may experience a failure. Based on the type of data stored by that data asset and the applicable regulations, requirements, and/or restrictions that relate to a transfer of that type data from that data asset, a target data asset may be determined. The data stored on the data asset may then be transferred to the target data asset. The disclosed systems may use data models and/or data maps in determining the requirements for a data transfer and selecting target data assets.

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: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for mapping various questions regarding a data breach from a master questionnaire to a plurality of territory-specific data breach disclosure questionnaires. The answers to the questions in the master questionnaire are used to populate the territory-specific data breach disclosure questionnaires and determine whether disclosure is required in territory. The system can automatically notify the appropriate regulatory bodies for each territory where it is determined that data breach disclosure is required.

Abstract: Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for performing a process of procuring a vendor and sub-processes associated therewith, such as performing vendor risk assessments and providing training specific to the procurement of that particular vendor. Training requirements for the user procuring the vendor and/or for the vendor itself are determined and any deficiencies in current, valid training requirements are identified. Training to address any identified deficiencies is provided as part of the vendor procurement process. Training may be customized based on trainee and/or organization attributes to improve the effectiveness of such training.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for mapping various questions regarding a data breach from a master questionnaire to a plurality of territory-specific data breach disclosure questionnaires. The answers to the questions in the master questionnaire are used to populate the territory-specific data breach disclosure questionnaires and determine whether disclosure is required in territory. The system can automatically notify the appropriate regulatory bodies for each territory where it is determined that data breach disclosure is required.

Abstract: In various embodiments, before a data subject request can be processed, the data subject's identity may need to be verified. In various embodiments, the system provides a mechanism to automatically detect the type of authentication required for a particular data subject based on the type of Data Subject Access Request being made and automatically issues a request to the data subject to verify their identity against that form of identification. For example, a subject rights request might only require two types of authentication, but a deletion request may require four types of data to verify authentication. The system may automatically detect which is type of authentication is required based on the DSAR and send an appropriate request to the data subject to verify their identity.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include any entity that collects, processes, contains, and/or transfers personal data (e.g., a software application, database, website, server, etc.). A data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc. The system may then utilize the generated model to fulfil a data subject access request.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). The system may be configured to identify particular data assets and/or personal data in data repositories using any suitable intelligent identity scanning technique.

Abstract: A consent receipt management system may include one or more consent validity scoring systems. In various embodiments, a consent validity scoring system may be configured to detect a likelihood that a user is correctly consenting via a web form. The system may be configured to determine such a likelihood based at least in part on one or more data subject behaviors while the data subject is completing the web form in order to provide consent. In various embodiments, the system is configured to monitor the data subject behavior based on, for example: mouse speed; mouse hovering; mouse position; keyboard inputs; an amount of time spent completing the web form; etc. The system may be further configured to calculate a consent validity score for each generated consent receipt based at least in part on an analysis of the data subject's behavior.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for performing a process of procuring a vendor and sub-processes associated therewith, such as performing vendor risk assessments and providing training specific to the procurement of that particular vendor. Training requirements for the user procuring the vendor and/or for the vendor itself are determined and any deficiencies in current, valid training requirements are identified. Training to address any identified deficiencies is provided as part of the vendor procurement process. Training may be customized based on trainee and/or organization attributes to improve the effectiveness of such training.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.

Abstract: In particular embodiments, an Orphaned Data Action System is configured to analyze one or more data systems (e.g., data assets), identify one or more pieces of personal data that are one or more pieces of personal data that are not associated with one or more privacy campaigns of the particular organization, and notify one or more individuals of the particular organization of the one or more pieces of personal data that are one or more pieces of personal data that are not associated with one or more privacy campaigns of the particular organization.