User biometric pattern learning and prediction

US9336373B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9336373-B2
Application numberUS-201414253068-A
CountryUS
Kind codeB2
Filing dateApr 15, 2014
Priority dateApr 15, 2014
Publication dateMay 10, 2016
Grant dateMay 10, 2016

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

A user device collects timing data that indicates screen touch timing behavior during multiple touch events associated with at least one of a hold time for a particular button or a transition time between two particular buttons. The user device also collects force data indicating screen touch force behavior during the multiple touch events. The user device identifies a user biometric pattern for the touch event based on the timing data and the force data, and stores the user biometric pattern.

First claim

Opening claim text (preview).

What is claimed is: 1. A method, comprising: collecting, by a user device, timing data that indicates screen touch timing behavior during multiple touch events for a sequence of keys, wherein the timing data for each of the multiple touch events is associated with at least one of a hold time for a particular button or a transition time between two particular buttons; collecting, by the user device, force data indicating screen touch force behavior during the multiple touch events, wherein the force data for each of the multiple touch events includes acceleration values and orientation values for the user device, wherein the acceleration values includes three directional acceleration values that are captured independently and the orientation values include three directional orientation values that are captured independently; identifying, by the user device, a user biometric pattern for the multiple touch events, wherein the user biometric pattern is based on the timing data and the force data and includes, for each of the multiple touch events, a time interval, the acceleration values over the time interval, a first order acceleration derivative, a second order acceleration derivative, the orientation values over the time interval, a first order orientation derivative, and a second order orientation derivative; storing, by the user device, the user biometric pattern associated with the multiple touch events; presenting, by the user device, a challenge to solicit new touch events for the sequence of keys; obtaining, by the user device, new timing data for the new touch events; obtaining, by the user device, new force data for the new touch events; comparing, by the user device, the new timing data and the new force data to the user biometric pattern; determining, by the user device and based on the comparing, if the new timing data and the new force data correspond to the user biometric pattern; and preventing access to one of the user device or an application stored on the user device when the new timing data and the new force data do not correspond to the user biometric pattern. 2. The method of claim 1 , wherein the identifying further comprises: generating a directed graph corresponding to a particular keypad arrangement, and identifying clusters for each vertex and each edge in the directed graph. 3. The method of claim 1 , wherein the determining includes identifying an overall confidence value based on the new timing data and the new force data. 4. The method of claim 3 , wherein identifying the overall confidence value includes: identifying a confidence value for each of the multiple touch events, and averaging the confidence values to generate the overall confidence value. 5. The method of claim 1 , wherein the timing data for each of the multiple touch events includes: a timestamp of a down click and a timestamp of an up click for a single button, or a timestamp of an up click for a first button and a timestamp of a down click for a second button. 6. The method of claim 1 , wherein the identifying the user biometric pattern includes, for each of the multiple touch events, constructing a cluster of the timing data and constructing a cluster of the force data. 7. The method of claim 6 , wherein the identifying the user biometric pattern further includes identifying a centroid and a radius for each cluster of the timing data and each cluster of the force data. 8. The method of claim 1 , wherein presenting the challenge to solicit new touch events includes: soliciting one of a password, a secret code, or an input pattern; or display an alphanumeric sequence that has to be entered by the user. 9. The method of claim 8 , wherein determining if the new timing data and the new force data correspond to the user biometric pattern further comprises: comparing content of the new touch events with content of the sequence of keys. 10. A device, comprising: a memory configured to store a plurality of instructions; and a processor configured to execute instructions in the memory to: collect timing data that indicates screen touch timing behavior during multiple touch events for a sequence of keys, wherein the timing data for each of the multiple touch events is associated with at least one of a hold time for a particular button or a transition time between two particular buttons, collect force data indicating screen touch force behavior during the multiple touch events, wherein the force data for each of the multiple touch events includes acceleration values and orientation values for the device, wherein the acceleration values includes three directional acceleration values that are captured independently and the orientation values include three directional orientation values that are captured independently, identify a user biometric pattern for the multiple touch events, wherein the user biometric pattern is based on the timing data and the force data and includes, for each of the multiple touch events, a time interval, the acceleration values over the time interval, a first order acceleration derivative, a second order acceleration derivative, the orientation values over the time interval, a first order orientation derivative, and a second order orientation derivative, store the user biometric pattern associated with the multiple touch events, present a challenge to solicit new touch events for the sequence of keys, obtain new timing data for the new touch events, obtain new force data for the new touch events, compare the new timing data and the new force data to the user biometric pattern, determine, based on the comparing, if the new timing data and the new force data correspond to the user biometric pattern, and prevent access to one of the device or an application stored on the device when the new timing data and the new force data do not correspond to the user biometric pattern. 11. The device of claim 10 , wherein, when identifying the user biometric pattern, the processor is further configured to: generate a directed graph corresponding to a particular keypad arrangement, and identify clusters for each vertex and each edge in the directed graph. 12. The device of claim 10 , wherein when determining if the new timing data and the new force data correspond to the user biometric pattern, the processor is further configured to: identify an overall confidence value based on the new timing data and the new force data. 13. The device of claim 12 , wherein when identifying the overall confidence value, the processor is further configured to: identify a confidence value for each of the multiple touch events, and average the confidence values. 14. The device of claim 10 , wherein the timing data for each of the multiple touch events includes at least one of: a timestamp of a down click and a timestamp of an up click for a single button, or a timestamp of an up click for a first button and a timestamp of a down click for a second button. 15. The device of claim 10 , wherein, when identifying the user biometric pattern, the processor is further configured to: construct, for each of the multiple touch events, a timing cluster of the timing data that identifies a centroid and a radius of the timing cluster, and construct, for each of the multiple touch events, a force cluster of the force data that identifies a centroid and a radius of the force cluster. 16. A non-transitory computer-readable medium storing instructions executable by a computational device to: collect timing data that indicates screen touch timing behavior during multiple touch even

Assignees

Inventors

Classifications

  • for inputting data by handwriting, e.g. gesture or text · CPC title

  • G06F21/32Primary

    using biometric data, e.g. fingerprints, iris scans or voiceprints · CPC title

  • using force sensing means to determine a position · CPC title

  • by observing the pattern of computer usage, e.g. typical user behaviour · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US9336373B2 cover?
A user device collects timing data that indicates screen touch timing behavior during multiple touch events associated with at least one of a hold time for a particular button or a transition time between two particular buttons. The user device also collects force data indicating screen touch force behavior during the multiple touch events. The user device identifies a user biometric pattern fo…
Who is the assignee on this patent?
Verizon Patent & Licensing Inc
What technology area does this patent fall under?
Primary CPC classification G06F21/32. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue May 10 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).