Malicious application detection in android—a systematic literature review
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …
gadgets became an essential necessity of day-to-day life. People are using new …
Machine learning algorithm for malware detection: Taxonomy, current challenges, and future directions
Malware has emerged as a cyber security threat that continuously changes to target
computer systems, smart devices, and extensive networks with the development of …
computer systems, smart devices, and extensive networks with the development of …
[HTML][HTML] Android malware classification using optimum feature selection and ensemble machine learning
The majority of smartphones on the market run on the Android operating system. Security
has been a core concern with this platform since it allows users to install apps from unknown …
has been a core concern with this platform since it allows users to install apps from unknown …
Constructing features for detecting android malicious applications: issues, taxonomy and directions
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
A static analysis approach for Android permission-based malware detection systems
J Mohamad Arif, MF Ab Razak, S Awang, SR Tuan Mat… - PloS one, 2021 - journals.plos.org
The evolution of malware is causing mobile devices to crash with increasing frequency.
Therefore, adequate security evaluations that detect Android malware are crucial. Two …
Therefore, adequate security evaluations that detect Android malware are crucial. Two …
Android malware detection using network traffic based on sequential deep learning models
S Fallah, AJ Bidgoly - Software: Practice and Experience, 2022 - Wiley Online Library
The increasing trend of smartphone capabilities has caught the attention of many users. This
has led to the emergence of malware that threatening the users' privacy and security. Many …
has led to the emergence of malware that threatening the users' privacy and security. Many …
Droid-NNet: Deep learning neural network for android malware detection
M Masum, H Shahriar - … Conference on Big Data (Big Data), 2019 - ieeexplore.ieee.org
Android, the most dominant Operating System (OS), experiences immense popularity for
smart devices for the last few years. Due to its' popularity and open characteristics, Android …
smart devices for the last few years. Due to its' popularity and open characteristics, Android …
Quantum machine learning for software supply chain attacks: How far can we go?
Quantum Computing (QC) has gained immense popularity as a potential solution to deal
with the ever-increasing size of data and associated challenges leveraging the concept of …
with the ever-increasing size of data and associated challenges leveraging the concept of …
Self-attention based convolutional-LSTM for android malware detection using network traffics grayscale image
L Shen, J Feng, Z Chen, Z Sun, D Liang, H Li… - Applied Intelligence, 2023 - Springer
To accurately find malware in a large number of mobile APPs, and determine which family it
belongs to is one of the most important challenges in Android malware detection. Existed …
belongs to is one of the most important challenges in Android malware detection. Existed …
An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Classification has become an important task for automatically categorizing documents
based on their respective group. The purpose of classification is to assign the pre-specified …
based on their respective group. The purpose of classification is to assign the pre-specified …