A survey on heterogeneous graph embedding: methods, techniques, applications and sources
Heterogeneous graphs (HGs) also known as heterogeneous information networks have
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
A survey of android malware detection with deep neural models
Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …
security research. Deep learning models have many advantages over traditional Machine …
A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
A comprehensive survey on machine learning approaches for malware detection in IoT-based enterprise information system
A Gaurav, BB Gupta, PK Panigrahi - Enterprise Information …, 2023 - Taylor & Francis
ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …
academics' and business information systems' attention in recent years. The Internet of …
Heterogeneous network representation learning: A unified framework with survey and benchmark
Since real-world objects and their interactions are often multi-modal and multi-typed,
heterogeneous networks have been widely used as a more powerful, realistic, and generic …
heterogeneous networks have been widely used as a more powerful, realistic, and generic …
GDroid: Android malware detection and classification with graph convolutional network
The dramatic increase in the number of malware poses a serious challenge to the Android
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
MLDroid—framework for Android malware detection using machine learning techniques
This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …
malware from Android devices. Due to increase in the popularity of Android devices …
Mamadroid: Detecting android malware by building markov chains of behavioral models (extended version)
As Android has become increasingly popular, so has malware targeting it, thus motivating
the research community to propose different detection techniques. However, the constant …
the research community to propose different detection techniques. However, the constant …
Iot-based android malware detection using graph neural network with adversarial defense
Since the Internet of Things (IoT) is widely adopted using Android applications, detecting
malicious Android apps is essential. In recent years, Android graph-based deep learning …
malicious Android apps is essential. In recent years, Android graph-based deep learning …
[HTML][HTML] An in-depth review of machine learning based Android malware detection
It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …