Explainable artificial intelligence applications in cyber security: State-of-the-art in research
This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …
A Comprehensive Analysis of Explainable AI for Malware Hunting
In the past decade, the number of malware variants has increased rapidly. Many
researchers have proposed to detect malware using intelligent techniques, such as Machine …
researchers have proposed to detect malware using intelligent techniques, such as Machine …
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 …
Sok: Explainable machine learning for computer security applications
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
An automated vision-based deep learning model for efficient detection of android malware attacks
Recently, cybersecurity experts and researchers have given special attention to develo**
cost-effective deep learning (DL)-based algorithms for Android malware detection (AMD) …
cost-effective deep learning (DL)-based algorithms for Android malware detection (AMD) …
XRan: Explainable deep learning-based ransomware detection using dynamic analysis
Recently, the frequency and complexity of ransomware attacks have been increasing
steadily, posing significant threats to individuals and organizations alike. While traditional …
steadily, posing significant threats to individuals and organizations alike. While traditional …
[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 …
Explainable ResNet50 learning model based on copula entropy for cotton plant disease prediction
This paper presents a novel Deep Learning (DL) framework for cotton plant disease
prediction based on Explainable Artificial Intelligence (XAI) and Copula entropy based-Grey …
prediction based on Explainable Artificial Intelligence (XAI) and Copula entropy based-Grey …
[HTML][HTML] A survey of malware detection using deep learning
The problem of malicious software (malware) detection and classification is a complex task,
and there is no perfect approach. There is still a lot of work to be done. Unlike most other …
and there is no perfect approach. There is still a lot of work to be done. Unlike most other …
Concept drift and cross-device behavior: Challenges and implications for effective android malware detection
The large body of Android malware research has demonstrated that machine learning
methods can provide high performance for detecting Android malware. However, the vast …
methods can provide high performance for detecting Android malware. However, the vast …