Jpmorgan Chase Bank, N.a.

Mcafee, Inc.

Jeremy F Bennett

Tuan Q Dao

Ralph Darmo

Rod Bachelor

Howard Spector

Andrew Grignon

Michelle M Bonat

Pavan Mummareddi

Christopher Choi

Jeffrey E Miller

Hallie Huggins

Kathleen Moynahan

Igor Tatourian

Dattatraya Kulkarni

Yi Zheng

Carl D Woodward

Raj Vardhan

Jennifer Eligius Mankin

Neeta Srivastava

Samrat Chitta

Muralitharan Chithanathan

Roderic Bachelor

Reji Gopalakrishnan

Systems and methods for protection of data across multiple users and devices are disclosed. According to one embodiment, in privacy server comprising at least one computer processor, a method for protection of data across multiple users and devices may include: (1) receiving, from a first user device, a data sharing permission for the first user device and a data sharing permission for a second user device, the first user device and the second user device associated with the same user; (2) provisioning the data sharing permission for the second user device; and (3) communicating the provisioned data sharing permission to the second user device, wherein the second user device shares data with the first user device according to the provisioned data sharing permission.

Systems and methods for protection of data across multiple users and devices

Systems, methods, and devices for tracking and managing data shared with third parties are disclosed. In one embodiment, a method including: retrieving data collection and usage policies of an entity; processing the data collection and usage policies with a natural language processing (NLP) model; generating, by the NLP model, predictive data collection and data usage attributes; generating a feature vector from the predictive data collection and data usage attributes; processing the feature vector with a graph neural network; storing data structured as a graph including the entity and the predictive data collection and data usage attributes; and processing the data structured as a graph with a classifier model that labels the entity as a first node in the data structured as a graph and predicts an edge to a second node in the data structured as a graph based on the predictive data collection and data usage attributes.

Systems and methods for tracking data shared with third parties using artificial intelligence-machine learning

Systems, methods, and devices for managing privacy policies are disclosed. In one embodiment, a method for management of a user's privacy preferences may include: identifying a computer application installed on a user electronic device, or a website accessed using a browser executed by the user electronic device; retrieving a privacy policy document analysis for a privacy policy document associated with the computer application or the website, the privacy policy document analysis comprising a valuation of a plurality of privacy policy segments within the privacy policy document; receiving a privacy preference analysis for the user, the privacy preference analysis comprising a valuation of a plurality of privacy preferences for the user; identifying a recommended action in response to the valuation of one of the privacy policy segments being outside the scope of the valuation of one of the plurality of privacy preferences; and executing the recommended action.

Systems and methods for managing privacy policies using machine learning

Systems, methods, and devices for obfuscation of browser fingerprint data are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method may include: (1) receiving an electronic communication from an electronic device to a destination; (2) identifying a raw device fingerprint value in the electronic communication from an electronic device; (3) selecting at least one replacement value for the raw device fingerprint value; (4) replacing the raw device fingerprint value with the replacement value in the electronic communication; and (5) sending the electronic communication with the replacement value to the destination.

Systems, methods, and devices for obfuscation of browser fingerprint data on the world wide web

Systems, methods, and devices for privacy-protecting data logging that can log user behavior (e.g., web browsing) without creating a user-specific list of browsed URLs are disclosed. In one embodiment, in an information processing apparatus comprising at least a token server, a privacy service, and a data store, a method for privacy logging may include: (1) providing, by the token server, a token to a privacy application executed on an electronic device and to a privacy service; (2) receiving, by the privacy service, browsing traffic from a browser or application executed by the electronic device; (3) associating, by the privacy service, the browsing traffic with the token; and (4) storing, by the data store, the associated browsing traffic with the token.

Systems, methods, and devices for privacy-protecting data logging

In an example, there is disclosed a computing apparatus, including a user notification interface; a context interface; and one or more logic elements forming a contextual privacy engine operable to: receive a notification; receive a context via the context interface; apply the context to the notification via a notification rule; and take an action via the user notification interface based at least in part on the applying. The contextual privacy engine may also be operable to mathematically incorporate user feedback into the notification rule. There is also described a method of providing a contextual privacy engine, and one or more computer-readable storage mediums having stored thereon executable instructions for providing a contextual privacy engine.

Contextual privacy engine for notifications

There is disclosed in one example, a computing apparatus, including: first one or more logic elements providing a code module, the code module comprising a member having a branching policy designating either a public or private member; second one or more logic elements providing a policy engine, operable to: receive a first branch instruction to the member; determine that the branch instructions does not meet the policy; and take a security action. There is also disclosed a method of providing a policy engine, and a computer-readable medium having stored thereon executable instructions for providing a policy engine.

Hardware-enforced code paths

In an example, a system and method are provided for validating the sender of a message, such as an e-mail, text message, voice mail, network message, internet posting, or other electronic message. An authenticity server engine may first prescreen the message with anti-spam, anti-malware, and other filters. The screened message is then provided to the end user. If the end user deems the message suspicious, he may request additional validation. The authenticity server engine may then apply an example four-phase validation scheme, including analyzing header data for consistency with the message body, analyzing public data sources, analyzing private data sources, and receiving a result of an off-channel challenge to the sender. The server may then assign the message a sender validity confidence score.

Message sender authenticity validation

Growing community of inventors

San Carlos, CA, United States of America

Jeremy F Bennett