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 …

An automatic classification algorithm for software vulnerability based on weighted word vector and fusion neural network

Q Wang, Y Gao, J Ren, B Zhang - Computers & Security, 2023‏ - Elsevier
To address the problem that the traditional vectored representation of software vulnerability
data has high-dimensional sparsity and leads to unsatisfactory automatic classification, this …

An automatic software vulnerability classification framework using term frequency-inverse gravity moment and feature selection

J Chen, PK Kudjo, S Mensah, SA Brown… - Journal of Systems and …, 2020‏ - Elsevier
Vulnerability classification is an important activity in software development and software
quality maintenance. A typical vulnerability classification model usually involves a stage of …

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 …

Context-aware software vulnerability classification using machine learning

G Siewruk, W Mazurczyk - IEEE Access, 2021‏ - ieeexplore.ieee.org
Managing the vulnerabilities reported by a number of security scanning software is a tedious
and time-consuming task, especially in large-scale, modern communication networks …

Detecting unknown vulnerabilities in smart contracts using opcode sequences

P Li, G Wang, X **ng, X Li, J Zhu - Connection Science, 2024‏ - Taylor & Francis
Unknown vulnerabilities, also known as zero-day vulnerabilities, are vulnerabilities in
software, systems, or networks that have not yet been publicly disclosed or fixed. If these …

Machine learning techniques for python source code vulnerability detection

T Farasat, J Posegga - Proceedings of the Fourteenth ACM Conference …, 2024‏ - dl.acm.org
Software vulnerabilities are a fundamental reason for the prevalence of cyber attacks and
their identification is a crucial yet challenging problem in cyber security. In this paper, we …

Large-scale empirical study of important features indicative of discovered vulnerabilities to assess application security

M Zhang, XDC De Carnavalet, L Wang… - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Existing research on vulnerability discovery models shows that the existence of
vulnerabilities inside an application may be linked to certain features, eg, size or complexity …

A novel approach to continuous CVE analysis on enterprise operating systems for system vulnerability assessment

Y Kocaman, S Gönen, MA Barişkan… - International Journal of …, 2022‏ - Springer
Advances in information and technology have provided great opportunities and
conveniences for human life. However, with this process, attackers have switched to …

An automatic vulnerability classification framework based on BiGRU-TextCNN

M Pan, P Wu, Y Zou, C Ruan, T Zhang - Procedia Computer Science, 2023‏ - Elsevier
Abstract Common Vulnerabilities and Exposures (CVE) records known vulnerabilities and
provides standardized descriptions. By utilizing Common Weakness Enumeration (CWE) to …