Mobile malware
View article
DL-Droid: Deep learning based android malware detection using real devices Open
The Android operating system has been the most popular for smartphones and\ntablets since 2012. This popularity has led to a rapid raise of Android malware\nin recent years. The sophistication of Android malware obfuscation and\ndetection …
View article
MalDozer: Automatic framework for android malware detection using deep learning Open
Android OS experiences a blazing popularity since the last few years. This predominant platform has established itself not only in the mobile world but also in the Internet of Things (IoT) devices. This popularity, however, comes at the ex…
View article
The Evolution of Android Malware and Android Analysis Techniques Open
With the integration of mobile devices into daily life, smartphones are privy to increasing amounts of sensitive information. Sophisticated mobile malware, particularly Android malware, acquire or utilize such data without user consent. It…
View article
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning\n Detection Open
Machine learning based solutions have been successfully employed for\nautomatic detection of malware on Android. However, machine learning models\nlack robustness to adversarial examples, which are crafted by adding carefully\nchosen pertu…
View article
Consortium Blockchain-Based Malware Detection in Mobile Devices Open
To address the problem of detecting malicious codes in malware and extracting the corresponding evidences in mobile devices, we construct a consortium blockchain framework, which is composed of a detecting consortium chain shared by test m…
View article
Detecting Android Malware Leveraging Text Semantics of Network Flows Open
The emergence of malicious apps poses a serious threat to the Android platform. Most types of mobile malware rely on network interface to coordinate operations, steal users' private information, and launch attack activities. In this paper,…
View article
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices Open
Currently, Android malware detection is mostly performed on server side\nagainst the increasing number of malware. Powerful computing resource provides\nmore exhaustive protection for app markets than maintaining detection by a\nsingle use…
View article
A Comprehensive Survey on Machine Learning Techniques for Android Malware Detection Open
Year after year, mobile malware attacks grow in both sophistication and diffusion. As the open source Android platform continues to dominate the market, malware writers consider it as their preferred target. Almost strictly, state-of-the-a…
View article
Android Mobile Malware Detection Using Machine Learning: A Systematic Review Open
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 smartphones with various methods such as credential theft, survei…
View article
MAPAS: a practical deep learning-based android malware detection system Open
A lot of malicious applications appears every day, threatening numerous users. Therefore, a surge of studies have been conducted to protect users from newly emerging malware by using machine learning algorithms. Albeit existing machine or …
View article
A Two-Layer Deep Learning Method for Android Malware Detection Using Network Traffic Open
Because of the characteristic of openness and flexibility, Android has become the most popular mobile platform. However, it has also become the most targeted system by mobile malware. It is necessary for the users to have a fast and reliab…
View article
Machine Learning-Based Malicious Application Detection of Android Open
In this paper, we propose a machine learning based approach to detect malicious mobile malware Android applications. Our work is able to capture instantaneous attacks that cannot be effectively detected in past work. Based on the proposed …
View article
A large-scale empirical study on the effects of code obfuscations on Android apps and anti-malware products Open
The Android platform has been the dominant mobile platform in recent years resulting in millions of apps and security threats against those apps. Anti-malware products aim to protect smartphone users from these threats, especially from mal…
View article
A Survey of Deep Learning Techniques for Cybersecurity in Mobile Networks Open
The widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as their complexity. T…
View article
An Android Malware Detection Approach Based on Static Feature Analysis Using Machine Learning Algorithms Open
In the past decade, mobile devices became necessary for modern civilization and contributed directly to its development stages in defining mobile information access. Nonetheless, along with these rapid developments in modern mobile devices…
View article
A Survey on Mobile Malware Detection Techniques Open
Modern mobile devices are equipped with a variety of tools and services, and handle increasing amounts of sensitive information. In the\nsame trend, the number of vulnerabilities exploiting mobile devices are also augmented on a daily basi…
View article
Artificial Intelligence Algorithms for Malware Detection in Android-Operated Mobile Devices Open
With the rapid expansion of the use of smartphone devices, malicious attacks against Android mobile devices have increased. The Android system adopted a wide range of sensitive applications such as banking applications; therefore, it is be…
View article
A Survey on Smartphones Security: Software Vulnerabilities, Malware, and Attacks Open
The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in mobile applications, particularly targeting the Android pl…
View article
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification Open
Malicious software (malware) poses an increasing threat to the security of\ncommunication systems as the number of interconnected mobile devices increases\nexponentially. While some existing malware detection and classification\napproaches…
View article
Android Malware Detection Based on Factorization Machine Open
As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft that mobile phone users face, the detection of malware on Android devices has bec…
View article
Towards Explainable CNNs for Android Malware Detection Open
A challenge for implementing deep learning research in the real-world is the availability of techniques that explain predictions of a model, particularly in light of potential legal requirements to give an account of algorithmic outcomes f…
View article
A Review of State-of-the-Art Malware Attack Trends and Defense Mechanisms Open
The increasing sophistication of malware threats has led to growing concerns in the anti-malware community, as malware poses a significant danger to online users despite the availability of numerous defense solutions. This study aims to co…
View article
Why an Android App Is Classified as Malware Open
Machine learning–(ML) based approach is considered as one of the most promising techniques for Android malware detection and has achieved high accuracy by leveraging commonly used features. In practice, most of the ML classifications only …
View article
A Bayesian probability model for Android malware detection Open
The unprecedented growth of mobile technology has generated an increase in malware and raised concerns over malware threats. Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To com…
View article
Semi supervised machine learning approach for DDOS detection Open
The appearance of malicious apps is a serious threat to the Android platform. In this paper, we propose an effective and automatic malware detection method using the text semantics of network traffic. In particular, we consider each HTTP f…
View article
Android Malware Detection using Deep Learning on API Method Sequences Open
Android OS experiences a blazing popularity since the last few years. This predominant platform has established itself not only in the mobile world but also in the Internet of Things (IoT) devices. This popularity, however, comes at the ex…
View article
Automated Malware Detection in Mobile App Stores Based on Robust Feature Generation Open
Many Internet of Things (IoT) services are currently tracked and regulated via mobile devices, making them vulnerable to privacy attacks and exploitation by various malicious applications. Current solutions are unable to keep pace with the…
View article
MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models Open
The rise in popularity of the Android platform has resulted in an explosion of malware threats targeting it. As both Android malware and the operating system itself constantly evolve, it is very challenging to design robust malware mitigat…
View article
A Lightweight Android Malware Classifier Using Novel Feature Selection Methods Open
Smartphones and mobile tablets play significant roles in daily life and have led to an increase in the number of users of this technology. The rising number of mobile device end-users has resulted in the generation of malware by hackers. T…
View article
Machine Learning-Based Android Malware Detection Using Manifest Permissions Open
The Android operating system is currently the most prevalent mobile device operating system holding roughly 54 percent of the total global market share. Due to Android’s substantial presence, it has gained the attention of those with malic…