Joel T Trunick

US Patent:

8069181, Nov 29, 2011

Filed:

Jun 20, 2006

Appl. No.:

11/455957

Inventors:

Gopal Krishnan - Austin TX, US
Chaitanya Laxminarayan - Austin TX, US
Matthew Sanchez - Round Rock TX, US
Manoj Saxena - Austin TX, US
Joel Trunick - Austin TX, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 7/00

US Classification:

707769, 709203, 709246

Abstract:

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.

US Patent:

20200099684, Mar 26, 2020

Filed:

Sep 19, 2019

Appl. No.:

16/576312

Inventors:

- San Francisco CA, US
Nagaveera Venkata Su Tavvala - Cedar Park TX, US
Jose Rios Trevino - Austin TX, US
Vamshi Ramarapu - Austin TX, US
Swapneel Mahajan - Cupertino CA, US
Joel Trunick - Austin TX, US
Shalini Mayor - Foster City CA, US
James Myers - Round Rock TX, US
Raymond Scott Brammer - Round Rock TX, US
Ireneusz Pazdzierniak - Foster City CA, US
Shashi Velur - Austin TX, US
Feng Chi Wang - Austin TX, US
Vincent Hesener - Foster City CA, US

International Classification:

H04L 29/06
H04L 9/32
G06F 21/45

Abstract:

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.