Competitive Advantages:
Future vulnerabilites can be anticipated easily, Improved software security, Helps developers allocate resources efficiently and implement counter measures.
Aspects of software vulnerability prediction are described. In some examples vulnerability data is obtained from a vulnerability database for the software. The total cumulative vulnerability of the software is estimated using the vulnerability data. The total cumulative vulnerability is based at least in part on a time based nonlinear differential equation model. The time based nonlinear differential equation model generates a complete vulnerability life cycle. A graph is generated to display a cyclic increasing behavior of the complete vulnerability life cycle of the software.Researchers at USF have created a novel technology that efficiently helps developers of the OS examine the software readiness by predicting its future vulnerability trend. The analytical model strongly captures the complicated linear and nonlinear behavior of the historically available data points and predicts the future vulnerabilities. Each version of the software is considered individually to tackle all the loopholes and make it more secure.
Brochure
