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You searched for all technologies in the category Computer Software.
Your search returned 15 results.

Displaying results 1–5 of 15.
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Robust Keystroke Authentication and Input-Traffic Correlation Analysis for Accurate Bot Detection

VTIP:10-103

Our security technology aims to detect a compromised personal computer by monitoring and analyzing the characteristic human behavior patterns of the PC owner. We develop a Personalized Bot Detection (PBD) system that can be installed on a computer. PBD has the following main features:

(1) collects and analyzes the ...

GePSeA: General-Purpose Software Acceleration Framework for Lightweight Task Offloading

VTIP:10-024

Hardware-acceleration techniques continue to be used to speed-up the execution of scienti?c codes. To do so, software developers identify portions of these codes that are amenable for of?oading and map them to hardware accelerators. However, of?oading such tasks to specialized hardware accelerators is non-trivial. Furthemore, these accelerators can ...

Funding Opportunities Management System

VTIP:10-006

The software provides a means of managing funding opportunities such that a central administration group can choose relevant opportunities for an institution and present them to their researchers in a filtered, searchable fashion with added keywords and filtering. Searches can be done by keyword, title, abstract, custom tagging, sponsoring agency, ...

A Methodology for Phishing Site Detection Using Online Resources

VTIP:09-137

Phishing is an attempt to fradulently acquire users? sensitive information, such as passwords or financial inforamtion, by masquerading as a trustworthy entity in online transactions. This methodology significantly improves the accuracy of phishing site detection when used in combination with other phishing detection techniques by utilizing online resources such as ...

Methodology and Software for Financial Fraud Detection Using Textual Analysis/Text Mining

VTIP:09-130

The software uses publicly available data about any publicly traded firms such as annual reports and letters to shareholders to automatically perform financial statement fraud risk assessments. The fraud profiles are automatically built using historical fraud data. The accuracy rate of fraud prediction is very high.

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