In a case of receiving an access request to a target image, an image access management device can provide an appropriate access right holder with an appropriate range of information by determining a browsing level with respect to the target image according to an access authority or purpose included in the access request to the target image, by an access management unit, by generating a final image that corresponds to the access authority by processing the feature vector according to the browsing level, and providing the generated final image as a response to the access request, by an image generation unit.

An application programming interface (API) is provided to an application configured to cause display of a user interface (UI). An item of targeted content and metadata corresponding to the item of targeted content is received. The item is rendered in the UI and a call to the API is initiated based on the metadata, the call causing the UI to render a UI feature concurrently within the item. Interaction with the UI feature causes the application to display additional UI features that identify the provider of the item and user information it possesses, the information comprising a reason for the item being provided. Further UI features may be rendered that enable a user to manage such information. In another aspect, the application may comprise a web browser and UI features rendered using the API may comprise a tracker information UI that enables the user to control use of browser trackers.

The disclosure herein describes a method and a system for providing data privacy based on customized cookie consent. The proposed customized cookie consent system enables user's data privacy by facilitating the user to customize a plurality of features for each individual cookie, wherein a cookie is customized for multiple features that includes a consent and expiry customization, a drill down at individual cookie, an online masking unmasking cookie data—an offline masking-unmasking cookie data, a consent lineage and a data subject rights for cookie data that further include data access, data portability, right to erasure based on machine learning techniques. Further the customized cookie consent system also provides recommendation for data privacy and obscured cookies using machine learning techniques.

A process of requesting and providing an anonymization service for sharing images or videos capturing identity of persons. An anonymization server receives a request including information corresponding to an identifier identifying the image or the video, a region within the image or video in which an identity of a person is captured, an encryption key used to encrypt the region of the image or the video, and contact information of the person. When the anonymization server receives a request from the second agency to share an encryption key for decrypting the region, the server transmits a request to the person to provide a permission to deanonymize the identity of the person captured in the image or video. The anonymization server transmits a response including the encryption key to the second agency when a response indicating a permission is received from the person.

Embodiments seek to protect privacy of potentially sensitive client resources in web transactions using crowd-disambiguation. Crowd-disambiguation machines can aggregate information about resources from multiple clients as resource fingerprints, and can use the fingerprints to provide crowd-sourced services in a privacy-protected manner. For example, embodiments can communicate a resource fingerprint as a fully ambiguated resource instance (FARI) and a partially disambiguated resource instance (PDRI). When one (or few) clients communicates the resource fingerprint, the identity of the resource remains obfuscated from the crowd-disambiguation machine. As more clients communicate fingerprints for the same resource (e.g., identified by the matching FARIs), respective, differently generated PDRIs of those fingerprints enable the crowd-disambiguation machine to resolve further portions of the resource, ultimately permitting the resource to be revealed and considered non-private (e.g., for use in hint generation or other crowd-sourced services).

The present invention discloses a privacy masking method using format-preserving encryption in an image security system, and a recording medium for performing the method. In a privacy masking method using format-preserving encryption in an image security system according to an aspect of the present invention, an image corresponding to a privacy region is encrypted using format-preserving encryption, so that it is possible to prevent waste of additional storage space required for encryption and to solve a problem of exposure of personal information.

Embodiments described herein are directed to intelligently classifying Web trackers in a privacy preserving manner and mitigating the effects of such Web trackers. As users browse the Web and encounter various Web sites, tracker-related metrics are determined. The metrics are obfuscated to protect the privacy of the user. The obfuscated metrics are provided as inputs to a machine learning model, which is configured to output a classification for the Web trackers associated with the Web sites visited by the user. Depending on the classification, the effects of the Web trackers are mitigated by placing restrictions on the Web trackers. The restrictions for a particular Web tracker may be relaxed based on a level of user engagement a user has with respect to the tracker's associated Web site. By doing so, the compatibility risks associated with tracking prevention are mitigated for Web sites that are relatively important to the user.

Techniques are disclosed relating to methods that include receiving an indication of an access by a user to a web page that includes a beacon, and calculating a readiness score for triggering the beacon. The methods may also include determining, based on the readiness score, whether to perform a client-side or server-side triggering of the beacon. The triggering causes data associated with the access to be transmitted to a third-party computer system.

The disclosed computer-implemented method may include receiving, from a third party, a portion of data or computer-executable logic that is part of a specified model. Each model may include various portions of independently verifiable computer-executable logic. The method may further include receiving data at a processing engine. The processing engine may be configured to apply the specified model to the received data. The method may then execute the specified model at the processing engine to modify the received data and send the modified data to an application that is configured to process the modified data. Various other methods, systems, and computer-readable media are also disclosed.

Methods and systems for recommending content to a client device operated by a user include receiving a set of ratings for each of a first set of content items by a user from a client device for use in a factor model. The set of ratings is not maintained in the server for longer than necessary to calculate a rating vector and/or to update a matrix factor defined by the rank of the factor model and a total number of content items eligible for ranking.