The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches

H Hanif, MHNM Nasir, MF Ab Razak, A Firdaus… - Journal of Network and …, 2021 - Elsevier
The detection of software vulnerability requires critical attention during the development
phase to make it secure and less vulnerable. Vulnerable software always invites hackers to …

Automatic feature learning for predicting vulnerable software components

HK Dam, T Tran, T Pham, SW Ng… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Code flaws or vulnerabilities are prevalent in software systems and can potentially cause a
variety of problems including deadlock, hacking, information loss and system failure. A …

Out of sight, out of mind? How vulnerable dependencies affect open-source projects

GAA Prana, A Sharma, LK Shar, D Foo… - Empirical Software …, 2021 - Springer
Context Software developers often use open-source libraries in their project to improve
development speed. However, such libraries may contain security vulnerabilities, and this …

The importance of accounting for real-world labelling when predicting software vulnerabilities

M Jimenez, R Rwemalika, M Papadakis… - Proceedings of the …, 2019 - dl.acm.org
Previous work on vulnerability prediction assume that predictive models are trained with
respect to perfect labelling information (includes labels from future, as yet undiscovered …

A large-scale empirical study on vulnerability distribution within projects and the lessons learned

B Liu, G Meng, W Zou, Q Gong, F Li, M Lin… - Proceedings of the …, 2020 - dl.acm.org
The number of vulnerabilities increases rapidly in recent years, due to advances in
vulnerability discovery solutions. It enables a thorough analysis on the vulnerability …

Risk prediction of IoT devices based on vulnerability analysis

P Oser, RW van der Heijden, S Lüders… - ACM Transactions on …, 2022 - dl.acm.org
Internet of Things (IoT) devices are becoming more widespread not only in areas such as
smart homes and smart cities but also in research and office environments. The sheer …

[HTML][HTML] Efficient feature selection for static analysis vulnerability prediction

K Filus, P Boryszko, J Domańska, M Siavvas… - Sensors, 2021 - mdpi.com
Common software vulnerabilities can result in severe security breaches, financial losses,
and reputation deterioration and require research effort to improve software security. The …

A hierarchical model for quantifying software security based on static analysis alerts and software metrics

M Siavvas, D Kehagias, D Tzovaras, E Gelenbe - Software Quality Journal, 2021 - Springer
Despite the acknowledged importance of quantitative security assessment in secure
software development, current literature still lacks an efficient model for measuring internal …

A catalog of metrics at source code level for vulnerability prediction: A systematic map** study

Z Codabux, K Zakia Sultana… - Journal of Software …, 2024 - Wiley Online Library
Industry practitioners assess software from a security perspective to reduce the risks of
deploying vulnerable software. Besides following security best practice guidelines during …

A deep learning‐based approach for software vulnerability detection using code metrics

F Subhan, X Wu, L Bo, X Sun, M Rahman - IET software, 2022 - Wiley Online Library
Vulnerabilities can have devastating effects on information security, affecting the economy,
social stability, and national security. The idea of automatic vulnerability detection has …