Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington MA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Bellevue WA, US
Assignee:
Elwha LLC - Bellevue WA
International Classification:
H04L 9/32
US Classification:
713182, 726 28
Abstract:
Behavioral fingerprints hold gathered data related to users' interactions with a device or devices, inter alia. Behavioral fingerprints may be used to at least partially determine a level of accessibility of the device or of an aspect of the device for the user; provide a current status of a network-accessible user associated with the device; activate or deactivate functions, programs or features of the device; generate alerts regarding the user's interaction with the device; assist in identifying a current device as a device being currently used by a network-accessible user, etc. Behavioral fingerprints may include statistical calculations on social network collected data, user input, sensor-provided data as provided by GPS, accelerometers, microphones, cameras, timers, touch-panels, or other indication or combination of the foregoing, whether originating from the device or the network. Anomalous activity associated with the device may be detected without user intervention at least in part with behavioral fingerprints.
Alexander J. Cohen - Mill Valley CA, US Geoffrey F. Deane - Bellevue WA, US Daniel A. Gerrity - Kirkland WA, US Edward K.Y. Jung - Bellevue WA, US Royce A. Levien - Lexington MA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US William Henry Mangione-Smith - Kirkland WA, US Nathan Pegram - Bellevue WA, US Phillip Rutschman - Seattle WA, US Clarence T. Tegreene - Bellevue WA, US Debra M. Warden - Edmonds WA, US
International Classification:
H04R 3/00 G06F 17/00
US Classification:
381122, 700 94
Abstract:
Certain aspects relate to providing an at least one audio source to at least one user. Certain aspects relate to selectively modifying an at least one first sound source to be provided to the at least one user, wherein the at least one first sound source is combined with an at least one second sound source, and wherein the selectively modifying is performed relative to the at least one audio source based at least in part on at least some specific information of the at least one first sound source. Other aspects relate to selectively modifying the at least one first sound source to be provided to the at least one user relative to the at least one second sound source based at least in part on at least some specific information of the at least one first sound source.
Alexander J. Cohen - Mill Valley CA, US Geoffrey F. Deane - Bellevue WA, US Daniel A. Gerrity - Kirkland WA, US Royce A. Levien - Lexington MA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US William Henry Mangione-Smith - Kirkland WA, US Nathan Pegram - Bellevue WA, US Phillip Rutschman - Seattle WA, US Clarence T. Tegreene - Bellevue WA, US Debra M. Warden - Edmonds WA, US
International Classification:
H04B 3/00
US Classification:
381 77
Abstract:
Certain aspects relate to providing an at least one audio source to at least one user. Certain aspects relate to selectively modifying an at least one first sound source to be provided to the at least one user, wherein the at least one first sound source is combined with an at least one second sound source, and wherein the selectively modifying is performed relative to the at least one audio source based at least in part on at least some specific information of the at least one first sound source. Other aspects relate to selectively modifying the at least one first sound source to be provided to the at least one user relative to the at least one second sound source based at least in part on at least some specific information of the at least one first sound source.
Behavioral Fingerprint Controlled Theft Detection And Recovery
Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington MA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Bellevue WA, US
International Classification:
G06F 21/20
US Classification:
726 3
Abstract:
A computationally implemented method includes, but is not limited to: determining a behavioral fingerprint associated with a network accessible user of one or more devices, the behavioral fingerprint providing a current status of the network accessible user; and disabling the one or more devices automatically as a function of the determined behavioral fingerprint. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.
Trust Verification Schema Based Transaction Authorization
Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington MA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Bellevue WA, US
International Classification:
G06F 21/00 H04L 9/32
US Classification:
726 7
Abstract:
A computationally implemented method includes, but is not limited to: for determining one or more behavioral fingerprints associated with one or more network accessible users; relationally mapping the one or more behavioral fingerprints to generate a trust verification schema associated with the one or more network accessible users; and determining whether to authenticate one or more transactions via the trust verification schema. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.
Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington MA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Bellevue WA, US
International Classification:
H04L 29/06 H04L 9/32
US Classification:
726 5
Abstract:
A computationally-implemented method, for certain example embodiments, may include, but is not limited to: determining that a first user of a computing device is associated with the computing device; and determining a level of authentication associated with the first user via the computing device, the level of authentication at least partially based on a behavioral fingerprint. In addition to the foregoing, other example aspects are described in the claims, drawings, and written description forming a part of the present disclosure.
Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington MA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Bellevue WA, US
International Classification:
G06F 21/20
US Classification:
726 3
Abstract:
A computationally implemented method includes, but is not limited to: determining a behavioral fingerprint associated with a network-accessible user, the behavioral fingerprint providing a current status of the network-accessible user; and controlling one or more devices automatically as a function of the determined behavioral fingerprint and a direction received from the network-accessible user. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.
Marc E. Davis - San Francisco CA, US Matthew G. Dyor - Bellevue WA, US Daniel A. Gerrity - Seattle WA, US Xuedong Huang - Bellevue WA, US Roderick A. Hyde - Redmond WA, US Royce A. Levien - Lexington WA, US Richard T. Lord - Tacoma WA, US Robert W. Lord - Seattle WA, US Mark A. Malamud - Seattle WA, US Nathan P. Myhrvold - Bellevue WA, US Clarence T. Tegreene - Mercer Island WA, US
International Classification:
G06F 21/31
US Classification:
726 7
Abstract:
A computationally-implemented method, in accordance with certain example embodiments, may include, but is not limited to: receiving at a computer device one or more behavioral fingerprints associated with one or more network accessible users; receiving an authentication request at the computer device, the authentication request associated with one or more proposed transactions of the one or more network accessible users; and transmitting from the computer device a decision associated with the authentication request, the decision based at least partially on a trust verification schema generated from a relational mapping of the one or more behavioral fingerprints associated with the one or more network accessible users. In addition to the foregoing, other aspects are presented in the claims, drawings, and written description forming a part of the present disclosure.
Dan Gerrity (1982-1987), Carol Sites (1964-1970), Ann Skuba (1964-1969), Michelle Dudley (1979-1984), Paula Carter (1966-1970), Wendy Allen (1980-1986)
Despite a greater prevalence of BA.2, an easily transmissible variant, there have not been greater concentrations of coronavirus in wastewater in Southern Nevada, said Daniel Gerrity, principal research microbiologist for the Southern Nevada Water Authority.