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DCW-RNN: Improving Class Level Metrics for Software Vulnerability Detection Using Artificial Immune System with Clock-Work Recurrent Neural Network
(IEEE (Institute of Electrical and Electronics Engineers), 2021)
As the defenses evolve, so do the solutions to a software vulnerability. The primary reason for security incidents, e.g., cyber-attacks, originates from software vulnerabilities. It is challenging to enhance the performance ...
Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes
(Springer, 2021)
With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart ...
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 ...
The Role of Vulnerable Software Metrics on Software Maintainability Prediction
(Dergipark, 2021)
Software maintainability is among the basic quality features of software engineering. Vulnerability prediction is crucial to protect software maintainability from attacks for cybersecurity. Hence, managing vulnerability ...