The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches
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 …
phase to make it secure and less vulnerable. Vulnerable software always invites hackers to …
A survey on data-driven software vulnerability assessment and prioritization
Software Vulnerabilities (SVs) are increasing in complexity and scale, posing great security
risks to many software systems. Given the limited resources in practice, SV assessment and …
risks to many software systems. Given the limited resources in practice, SV assessment and …
Automatic classification method for software vulnerability based on deep neural network
G Huang, Y Li, Q Wang, J Ren, Y Cheng, X Zhao - IEEE Access, 2019 - ieeexplore.ieee.org
Software vulnerabilities are the root causes of various security risks. Once a vulnerability is
exploited by malicious attacks, it will greatly compromise the safety of the system, and may …
exploited by malicious attacks, it will greatly compromise the safety of the system, and may …
Common vulnerability scoring system prediction based on open source intelligence information sources
The number of newly published vulnerabilities is constantly increasing. Until now, the
information available when a new vulnerability is published is manually assessed by experts …
information available when a new vulnerability is published is manually assessed by experts …
Automated event extraction of CVE descriptions
Context: The dramatically increasing number of vulnerabilities makes manual vulnerability
analysis increasingly more difficult. Automatic extraction of vulnerability information can help …
analysis increasingly more difficult. Automatic extraction of vulnerability information can help …
On the use of fine-grained vulnerable code statements for software vulnerability assessment models
Many studies have developed Machine Learning (ML) approaches to detect Software
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
An automatic algorithm for software vulnerability classification based on CNN and GRU
Q Wang, Y Li, Y Wang, J Ren - Multimedia Tools and Applications, 2022 - Springer
In order to improve the management efficiency of software vulnerability classification, reduce
the risk of system being attacked and destroyed, and save the cost for vulnerability repair …
the risk of system being attacked and destroyed, and save the cost for vulnerability repair …
A survey on automated software vulnerability detection using machine learning and deep learning
Software vulnerability detection is critical in software security because it identifies potential
bugs in software systems, enabling immediate remediation and mitigation measures to be …
bugs in software systems, enabling immediate remediation and mitigation measures to be …
An approach to discover and assess vulnerability severity automatically in cyber-physical systems
Current vulnerability scoring mechanisms in complex cyber-physical systems (CPSs) face
challenges induced by the proliferation of both component versions and recurring scoring …
challenges induced by the proliferation of both component versions and recurring scoring …
Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniques
C Sauerwein, A Pfohl - arXiv preprint arXiv:2207.08478, 2022 - arxiv.org
The increasingly sophisticated and growing number of threat actors along with the sheer
speed at which cyber attacks unfold, make timely identification of attacks imperative to an …
speed at which cyber attacks unfold, make timely identification of attacks imperative to an …