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 developing 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 …
Contractward: Automated vulnerability detection models for ethereum smart contracts
Smart contracts are decentralized applications running on Blockchain. A very large number
of smart contracts has been deployed on Ethereum. Meanwhile, security flaws of contracts …
of smart contracts has been deployed on Ethereum. Meanwhile, security flaws of contracts …
BotMark: Automated botnet detection with hybrid analysis of flow-based and graph-based traffic behaviors
The Botnets have become one of the most serious threats to cyber infrastructure. Most
existing work on detecting botnets is based on flow-based traffic analysis by mining their …
existing work on detecting botnets is based on flow-based traffic analysis by mining their …
Famd: A fast multifeature android malware detection framework, design, and implementation
H Bai, N Xie, X Di, Q Ye - IEEE Access, 2020 - ieeexplore.ieee.org
With Android's dominant position within the current smartphone OS, increasing number of
malware applications pose a great threat to user privacy and security. Classification …
malware applications pose a great threat to user privacy and security. Classification …
Privacy issues of android application permissions: A literature review
Android is an application platform for mobile devices. It comprises of the operating system,
software framework, and core programs. This platform uses permissions to hide precious …
software framework, and core programs. This platform uses permissions to hide precious …
IPDroid: Android malware detection using intents and permissions
With the increasing popularity of Android smart-phones over the years, the number of
malware attacks on Android has also increased. Around 26 million malware samples were …
malware attacks on Android has also increased. Around 26 million malware samples were …
Android malware detection using fine‐grained features
X Jiang, B Mao, J Guan, X Huang - Scientific Programming, 2020 - Wiley Online Library
Nowadays, Android applications declare as many permissions as possible to provide more
function for the users, which also poses severe security threat to them. Although many …
function for the users, which also poses severe security threat to them. Although many …
Deep and broad URL feature mining for android malware detection
In recent years, the scale and diversity of malicious software on mobile networks have grown
significantly, thereby causing considerable danger to users' property and personal privacy …
significantly, thereby causing considerable danger to users' property and personal privacy …
Detecting anomalies in intelligent vehicle charging and station power supply systems with multi-head attention models
Y Li, L Zhang, Z Lv, W Wang - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Safe and reliable intelligent charging stations are imperative in an intelligent transportation
infrastructure. Over the past few years, a big number of smart charging stations have been …
infrastructure. Over the past few years, a big number of smart charging stations have been …
A detection method for android application security based on TF-IDF and machine learning
H Yuan, Y Tang, W Sun, L Liu - Plos one, 2020 - journals.plos.org
Android is the most widely used mobile operating system (OS). A large number of third-party
Android application (app) markets have emerged. The absence of third-party market …
Android application (app) markets have emerged. The absence of third-party market …