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Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features
(2021)
The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. ...
Sequential Feature Maps with LSTM Recurrent Neural Networks for Robust Tumor Classification
(2021)
In the field of biomedicine, applications for the identification of biomarkers require a robust gene selection
mechanism. To identify the characteristic marker of an observed event, the selection of attributes becomes ...
A novel deep learning-based feature selection model for improving the static analysis of vulnerability detection
(Springer, 2021)
The automatic detection of software vulnerabilities is considered a complex and common research problem. It is possible to detect several security vulnerabilities using static analysis (SA) tools, but comparatively high ...