Deep learning for vulnerability and attack detection on web applications: A systematic literature review
RL Alaoui, EH Nfaoui - Future Internet, 2022 - mdpi.com
Web applications are the best Internet-based solution to provide online web services, but
they also bring serious security challenges. Thus, enhancing web applications security …
they also bring serious security challenges. Thus, enhancing web applications security …
A survey of recent advances in deep learning models for detecting malware in desktop and mobile platforms
Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …
millions of devices and can perform several malicious activities including compromising …
A bidirectional LSTM language model for code evaluation and repair
MM Rahman, Y Watanobe, K Nakamura - Symmetry, 2021 - mdpi.com
Programming is a vital skill in computer science and engineering-related disciplines.
However, developing source code is an error-prone task. Logical errors in code are …
However, developing source code is an error-prone task. Logical errors in code are …
Ensemble-based classification using neural networks and machine learning models for windows pe malware detection
The security of information is among the greatest challenges facing organizations and
institutions. Cybercrime has risen in frequency and magnitude in recent years, with new …
institutions. Cybercrime has risen in frequency and magnitude in recent years, with new …
Detection of obfuscated malicious JavaScript code
Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code
because of its strong impact and dramatic effect. Numerous recent cyberattacks use …
because of its strong impact and dramatic effect. Numerous recent cyberattacks use …
[HTML][HTML] ConvXSS: A deep learning-based smart ICT framework against code injection attacks for HTML5 web applications in sustainable smart city infrastructure
In this paper we propose ConvXSS, a novel deep learning approach for the detection of XSS
and code injection attacks, followed by context-based sanitization of the malicious code if …
and code injection attacks, followed by context-based sanitization of the malicious code if …
[HTML][HTML] Detection of malicious javascript on an imbalanced dataset
NM Phung, M Mimura - Internet of Things, 2021 - Elsevier
In order to be able to detect new malicious JavaScript with low cost, methods with machine
learning techniques have been proposed and gave positive results. These methods focus …
learning techniques have been proposed and gave positive results. These methods focus …
[HTML][HTML] Machine and deep learning-based xss detection approaches: a systematic literature review
Web applications are paramount tools for facilitating services providing in the modern world.
Unfortunately, the tremendous growth in the web application usage has resulted in a rise in …
Unfortunately, the tremendous growth in the web application usage has resulted in a rise in …
Transast: A machine translation-based approach for obfuscated malicious javascript detection
Y Qin, W Wang, Z Chen, H Song… - 2023 53rd Annual IEEE …, 2023 - ieeexplore.ieee.org
As an essential part of the website, JavaScript greatly enriches its functions. At the same
time, JavaScript has become the most common attack payload on malicious websites …
time, JavaScript has become the most common attack payload on malicious websites …
An exploratory study of cognitive sciences applied to cybersecurity
Cognitive security is the interception between cognitive science and artificial intelligence
techniques used to protect institutions against cyberattacks. However, this field has not been …
techniques used to protect institutions against cyberattacks. However, this field has not been …