Pre-Grant Publication Number: 20090049544
Please help the USPTO examine the application by evaluating the relevance of the publicly submitted prior art to the patent application.
Peer To Patent forwards the Top 10 most relevant prior art submissions and their annotations to the USPTO.
Review this prior art and click on the thumbs up (or down) to indicate whether this submission should be forwarded to the USPTO.
If you login then you can add an annotation by typing in the box at the bottom of the screen to comment on the relevance of the prior art to the claims of the patent application.
Review this prior art and click on the thumbs up (or down) to indicate whether this submission should be forwarded to the USPTO.
If you login then you can add an annotation by typing in the box at the bottom of the screen to comment on the relevance of the prior art to the claims of the patent application.
Prior Art Detail
Summary / Description
| Summary / Description | Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided. |
Basic Information
| Type of Prior Art | Issued Patents - US |
| Country | United States of America |
| Patent/Application # | US 2006/0224898 A1 |
| Kind Code | United States (US) - Patent Appl. Publ. within the ... - A1 |
| Patentee Name | Ahmed El-Sayed Ahmed |
| Relevant Pages, Columns, or Lines | abstract |
| URL | http://www.google.com/patents?i... |
| Filing Date | May 3, 2004 |
| Additional Information | |
Notes / To Do
| Notes | |
Excerpt
Excerpt Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided. |
Relevance
Claims
1
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
3
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
4
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
5
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
6
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
11
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
16
Relevance
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Computer user profiling is based on behavioral biometrics. Distinctive profiles for users are established based on how they use a motion-based input device such as a mouse and/or a keyboard, during a training period. User identification is established by training neural networks. Experimental data is provided.
Claim Chart
All
0 days left
