Visa International Service Association

International Business Machines Corporation

Joel Trunick

Keeshini Manivannan

Dipeshkumar Patel

Manan Lalaji

Matthew Sanchez

Manoj Saxena

Feng Chi Wang

Shalini Mayor

Vinjith Nagaraja

Chaitanya Laxminarayan

Gopal Krishnan

Shashi Velur

Raymond Brammer

Jose Rios Trevino

James Myers

Vamshi Ramarapu

Nagaveera Venkata Su Tavvala

Swapneel Mahajan

Ireneusz Pazdzierniak

Vincent Hesener

Raymond Scott Brammer

A processor-implemented method for improving computer identification comprising transmitting a browser fingerprinting test to one or more computing devices and receiving test data from the one more computing devices that includes at least an elapsed processing time and a hash code. The method includes determining an average elapsed processing time and determining a uniqueness level for the browser fingerprinting test by comparing the hash codes for each computing device with one another.

Systems and methods for improving computer identification

Techniques for securely generating and using a 'fingerprint' for authentication. A server computer receives a first data set from a user device (including a first fuzzy hash of first user data on the user device). The server computer generates a first fingerprint value based on the first data set. The server computer detects an event corresponding to a user in association with the user device. The server computer identifies a baseline fingerprint value (generated based on a baseline fuzzy hash of user data on the user device). The server computer compares the first fingerprint value to the baseline fingerprint value to generate a similarity score. The server computer may determine that the similarity score exceeds a threshold value but does not represent an exact match, and, based on the similarity score, authenticate the user and update the baseline fingerprint value based on the first fingerprint value.

Dynamic and private security fingerprinting

An autodiscovery feature with an easy-to-use interface is provided to automatically collect metadata about electronic services for use within a business enterprise and to store that metadata in a metadata repository. The autodiscovery feature is used to create autodiscovery queries that are sent to electronic services to collect from the services' digests specified metadata useful for identifying the functionality of those services and integrating the services into business processes. Digests, such as RSS feeds and Atom feeds, are typically created by services to include useful metadata, such as the title of a service, the URL link to a description of the service, a brief description of the service, the publication date of the service, and other data. Autodiscovery queries can thus collect services' relevant metadata and store it in a business enterprise's metadata repository, so that the services' functionality can be quickly identified and used for business processes.

Autodiscovery of business services

Growing community of inventors

Austin, TX, United States of America

Joel Trunick