Device, system, and method of detecting user identity based on inter-page and intra-page navigation patterns

Patent metadata

Field	Value
Publication number	US-9665703-B2
Application number	US-201414320656-A
Country	US
Kind code	B2
Filing date	Jul 1, 2014
Priority date	Nov 29, 2010
Publication date	May 30, 2017
Grant date	May 30, 2017

Abstract

Systems, devices, and methods for detecting identity of a user of an electronic device, and for determining whether or not an electronic device is being used by a fraudulent user; as well as for detecting identity of a user based on inter-page and intra-page navigation patterns. A method includes: during a first session of a user, who utilizes a pointing device and a keyboard for interacting with a computerized service, monitoring pointing device dynamics and gestures and keystrokes of the user; analyzing the monitored pointing device dynamics and gestures and keystrokes, in relation to (a) state and context of the computerized service, and (b) user interface elements displayed by the computerized service; generating a user-specific biometric trait indicating a user-specific service usage pattern, which includes at least one of: a user-specific inter-application usage pattern, and a user-specific intra-application usage pattern.

First claim

What is claimed is:

1. A method comprising:
(A) during multiple usage sessions of multiple users with a particular computerized financial service, wherein each one of said users utilizes a pointing device and a keyboard for interacting with said particular computerized service, monitoring pointing device dynamics and gestures and keystrokes of each one of said users across multiple different pages of said particular computerized financial service;
(B) differentiating between (i) a legitimate user of said particular computerized financial service, and (ii) an illegitimate user of said particular computerized financial service, based on an aggregate combination of:
(I) a first unique sequence in which each user visits multiple web-pages of said particular financial computerized service, and
(II) a second unique sequence in which each user engages with on-screen user interface (UI) elements within a single web-page of said particular computerized financial service, and
(III) a unique transition pattern in which each user transitions from a first on-screen component of a first web-page to a second on-screen component of a second web-page of said particular computerized financial service;

(C) based on said differentiating, flagging a particular financial transaction of a particular user of said particular computerized financial service as possibly-fraudulent.

2. The method of claim 1 , comprising:
monitoring whether said user more frequently utilizes the pointing device or the keyboard in order to perform a particular type of interaction with said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

3. The method of claim 1 , comprising:
based on analysis of user interactions, determining whether (A) said user utilizes the pointing device more frequently than the keyboard in order to submit a format said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

4. The method of claim 1 , comprising:
monitoring whether said user more frequently utilizes the pointing device or the keyboard in order to fill-in data in a form at said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

5. The method of claim 1 , comprising:
monitoring whether said user more frequently utilizes the pointing device or the keyboard in order to move a cursor between fields at said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

6. The method of claim 1 , comprising:
monitoring whether said user more frequently utilizes the pointing device or the keyboard in order to paste data into a particular field at said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

7. The method of claim 1 , comprising:
monitoring whether said user more frequently (a) pastes data into a particular field at said particular computerized financial service, or (b) types data into said particular field at said particular computerized financial service;
based on said monitoring, generating a user-specific intra-application usage pattern associated with said user.

8. The method of claim 1 , comprising:
determining a user-specific inter-application usage pattern that indicates that said user, in most of its interactions with said particular computerized financial service, performs a first particular action prior to performing a second particular action;
based on said user-specific inter-application usage pattern, determining whether a subsequent user of said particular computerized financial service is the same person as said user.

9. The method of claim 1 , comprising:
determining a user-specific inter-application usage pattern that indicates that said user, in most of its interactions with said particular computerized financial service, spends a first period of time at a first particular page of said particular computerized financial service prior to spending a second period of time at a second particular page of said particular computerized financial service;
based on said user-specific inter-application usage pattern, determining whether a subsequent user of said particular computerized financial service is the same person as said user.

10. The method of claim 1 , comprising:
monitoring for each field in a said particular computerized financial service, mouse dynamics and gestures for that field;
based on said monitoring, generating a user-specific field-usage pattern associated with said user and with said financial service.

11. The method of claim 1 , comprising:
monitoring for each field in said particular computerized financial service, (a) a mouse angle of approach to the field, (b) a mouse angle of exit from the field, (c) velocities of mouse approach and mouse exit, (d) time period spent within the field, and (e) location of a mouse click event within the field;
based on said monitoring, generating a user-specific field-usage pattern associated with said user.

12. The method of claim 1 , comprising:
based on monitored pointing device dynamics and gestures and based on monitored keystrokes of said user, estimating a user-specific behavioral trait of multiple-field-usage stream pattern of said user in relation to multiple fields on a particular page of said particular computerized financial service;
based on the estimated user-specific behavioral trait of multiple-field-usage stream pattern of said user, differentiating between said user and another user interacting with said particular computerized financial service.

13. The method of claim 1 , comprising:
based on monitored pointing device dynamics and gestures of said user, estimating a user-specific behavioral trait corresponding to angle of approach by said user to an on-screen field of said particular computerized financial service;
based on the estimated user-specific behavioral trait of angle of approach of said user, differentiating between said user and another user interacting with said particular computerized financial service.

14. The method of claim 1 , comprising:
based on monitored pointing device dynamics and gestures of said user, estimating a user-specific behavioral trait corresponding to angle of exit by said user from an on-screen field of said particular computerized financial service;
based on the estimated user-specific behavioral trait of angle of exit of said user, differentiating between said user and another user interacting with said particular computerized financial service.

15. The method of claim 1 , comprising:
based on monitored pointing device dynamics and gestures of said user, estimating a user-specific behavioral trait corresponding to speed of approach by said user to an on-screen field of said particular computerized financial service;
based on the estimated user-specific behavioral trait of speed of approach of said user, differentiating between said user and another user interacting with said particular computerized financial service.

16. The method of claim 1 , comprising:
based on monitored pointing device dynamics and gestures of said user, estimating a user-specific behavioral trait corresponding to speed of exit by said user from an on-screen field of said particular computerized financial servi

Assignees

• Biocatch Ltd

Inventors

• Turgeman Avi
• Novick Itai
• Lehmann Yaron
• Kadyshevitch Lev
• Dekel Edo

Classifications

• G06F21/31

  User authentication · CPC title

• H04W12/06 Primary

  Authentication · CPC title

• G06F21/316

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

• G06F21/32 Primary

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

• H04W12/68

  Gesture-dependent or behaviour-dependent · CPC title