Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Android source code vulnerability detection: a systematic literature review
The use of mobile devices is rising daily in this technological era. A continuous and
increasing number of mobile applications are constantly offered on mobile marketplaces to …
increasing number of mobile applications are constantly offered on mobile marketplaces to …
Explainable artificial intelligence in cybersecurity: A survey
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
Android mobile malware detection using machine learning: A systematic review
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …
phones, which account for 72.2% of the total market share. Hackers try to attack …
Deep learning for zero-day malware detection and classification: A survey
Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …
malware software can catch it. This novelty and the lack of existing mitigation strategies …
[HTML][HTML] Machine learning for android malware detection: mission accomplished? a comprehensive review of open challenges and future perspectives
A Guerra-Manzanares - Computers & Security, 2024 - Elsevier
The extensive research in machine learning based Android malware detection showcases
high-performance metrics through a wide range of proposed solutions. Consequently, this …
high-performance metrics through a wide range of proposed solutions. Consequently, this …
AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities
Abstract Many Machine Learning (ML)-based approaches have been proposed to
automatically detect, localize, and repair software vulnerabilities. While ML-based methods …
automatically detect, localize, and repair software vulnerabilities. While ML-based methods …
Explainable ai for android malware detection: Towards understanding why the models perform so well?
Machine learning (ML)-based Android malware detection has been one of the most popular
research topics in the mobile security community. An increasing number of research studies …
research topics in the mobile security community. An increasing number of research studies …
A lightweight deep learning-based android malware detection framework
Android, as the most prevalent mobile operating system (OS) in recent years, has been
widely applied in various cell phones, tablets, and embedded devices, greatly facilitating …
widely applied in various cell phones, tablets, and embedded devices, greatly facilitating …
Pitfalls in language models for code intelligence: A taxonomy and survey
Modern language models (LMs) have been successfully employed in source code
generation and understanding, leading to a significant increase in research focused on …
generation and understanding, leading to a significant increase in research focused on …