Software vulnerability analysis and discovery using machine-learning and data-mining techniques: A survey

SM Ghaffarian, HR Shahriari - ACM computing surveys (CSUR), 2017 - dl.acm.org
Software security vulnerabilities are one of the critical issues in the realm of computer
security. Due to their potential high severity impacts, many different approaches have been …

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 …

Software vulnerability detection using deep neural networks: a survey

G Lin, S Wen, QL Han, J Zhang… - Proceedings of the …, 2020 - ieeexplore.ieee.org
The constantly increasing number of disclosed security vulnerabilities have become an
important concern in the software industry and in the field of cybersecurity, suggesting that …

Sysevr: A framework for using deep learning to detect software vulnerabilities

Z Li, D Zou, S Xu, H Jin, Y Zhu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The detection of software vulnerabilities (or vulnerabilities for short) is an important problem
that has yet to be tackled, as manifested by the many vulnerabilities reported on a daily …

Vulcnn: An image-inspired scalable vulnerability detection system

Y Wu, D Zou, S Dou, W Yang, D Xu, H Jin - Proceedings of the 44th …, 2022 - dl.acm.org
Since deep learning (DL) can automatically learn features from source code, it has been
widely used to detect source code vulnerability. To achieve scalable vulnerability scanning …

A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - arXiv preprint arXiv …, 2021 - arxiv.org
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

IoT vulnerability assessment for sustainable computing: threats, current solutions, and open challenges

P Anand, Y Singh, A Selwal, M Alazab, S Tanwar… - IEEE …, 2020 - ieeexplore.ieee.org
Over the last few decades, sustainable computing has been widely used in areas like social
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …

[HTML][HTML] Attacks and defences on intelligent connected vehicles: A survey

M Dibaei, X Zheng, K Jiang, R Abbas, S Liu… - Digital Communications …, 2020 - Elsevier
Intelligent vehicles are advancing at a fast speed with the improvement of automation and
connectivity, which opens up new possibilities for different cyber-attacks, including in-vehicle …

Big data for cybersecurity: Vulnerability disclosure trends and dependencies

MJ Tang, M Alazab, Y Luo - IEEE Transactions on Big Data, 2017 - ieeexplore.ieee.org
Complex Big Data systems in modern organisations are progressively becoming attack
targets by existing and emerging threat agents. Elaborate and specialised attacks will …

Static analysis of information systems for IoT cyber security: a survey of machine learning approaches

I Kotenko, K Izrailov, M Buinevich - Sensors, 2022 - mdpi.com
Ensuring security for modern IoT systems requires the use of complex methods to analyze
their software. One of the most in-demand methods that has repeatedly been proven to be …