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Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be…

密码学与安全 · 计算机科学 2020-06-05 Muhammad Zuhair Qadir , Atif Nisar Jilani , Hassam Ullah Sheikh

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A…

密码学与安全 · 计算机科学 2016-08-03 Suleiman Y. Yerima , Sakir Sezer , Gavin McWilliams , Igor Muttik

Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as…

机器学习 · 计算机科学 2018-10-30 Marco Melis , Davide Maiorca , Battista Biggio , Giorgio Giacinto , Fabio Roli

Due to its open-source nature, the Android operating system has consistently been a primary target for attackers. Learning-based methods have made significant progress in the field of Android malware detection. However, traditional…

密码学与安全 · 计算机科学 2025-04-11 Xingyuan Wei , Zijun Cheng , Ning Li , Qiujian Lv , Ziyang Yu , Degang Sun

Mobile malware has continued to grow at an alarming rate despite on-going efforts towards mitigating the problem. This has been particularly noticeable on Android due to its being an open platform that has subsequently overtaken other…

密码学与安全 · 计算机科学 2016-07-28 Suleiman Y. Yerima , Sakir Sezer , Igor Muttik

The Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection…

密码学与安全 · 计算机科学 2019-11-25 Mohammed K. Alzaylaee , Suleiman Y. Yerima , Sakir Sezer

It is well-known that malware constantly evolves so as to evade detection and this causes the entire malware population to be non-stationary. Contrary to this fact, prior works on machine learning based Android malware detection have…

密码学与安全 · 计算机科学 2016-09-27 Annamalai Narayanan , Liu Yang , Lihui Chen , Liu Jinliang

Copious mobile operating systems exist in the market, but Android remains the user's choice. Meanwhile, its growing popularity has also attracted malware developers. Researchers have proposed various static solutions for Android malware…

密码学与安全 · 计算机科学 2025-03-04 Yash Sharma , Anshul Arora

The impressive growth of smartphone devices in combination with the rising ubiquity of using mobile platforms for sensitive applications such as Internet banking, have triggered a rapid increase in mobile malware. In recent literature, many…

密码学与安全 · 计算机科学 2023-12-20 Harris Papadopoulos , Nestoras Georgiou , Charalambos Eliades , Andreas Konstantinidis

In the fast-growing smart devices, Android is the most popular OS, and due to its attractive features, mobility, ease of use, these devices hold sensitive information such as personal data, browsing history, shopping history, financial…

密码学与安全 · 计算机科学 2019-04-04 Ashu Sharma , Sanjay K. Sahay

Mobile malware are malicious programs that target mobile devices. They are an increasing problem, as seen in the rise of detected mobile malware samples per year. The number of active smartphone users is expected to grow, stressing the…

密码学与安全 · 计算机科学 2022-02-15 J. S. Panman de Wit , J. van der Ham , D. Bucur

Android malware has been on the rise in recent years due to the increasing popularity of Android and the proliferation of third party application markets. Emerging Android malware families are increasingly adopting sophisticated detection…

密码学与安全 · 计算机科学 2016-12-06 BooJoong Kang , Suleiman Y. Yerima , Sakir Sezer , Kieran McLaughlin

It is well-known that Android malware constantly evolves so as to evade detection. This causes the entire malware population to be non-stationary. Contrary to this fact, most of the prior works on Machine Learning based Android malware…

密码学与安全 · 计算机科学 2017-07-07 Annamalai Narayanan , Mahinthan Chandramohan , Lihui Chen , Yang Liu

The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detection avoidance techniques in order to hide their malicious…

密码学与安全 · 计算机科学 2017-04-03 Mohammed K. Alzaylaee , Suleiman Y. Yerima , Sakir Sezer

Machine learning models are increasingly being adopted across various fields, such as medicine, business, autonomous vehicles, and cybersecurity, to analyze vast amounts of data, detect patterns, and make predictions or recommendations. In…

密码学与安全 · 计算机科学 2024-04-16 Dipkamal Bhusal , Nidhi Rastogi

The amount of Android malware has increased greatly during the last few years. Static analysis is widely used in detecting such malware by analyzing the code without execution. The effectiveness of current tools relies on the app model as…

密码学与安全 · 计算机科学 2016-04-11 Mohsin Junaid , Donggang Liu , David Kung

Over the last decade, researchers have extensively explored the vulnerabilities of Android malware detectors to adversarial examples through the development of evasion attacks; however, the practicality of these attacks in real-world…

机器学习 · 计算机科学 2024-01-26 Hamid Bostani , Veelasha Moonsamy

Android is the predominant mobile operating system for the past few years. The prevalence of devices that can be powered by Android magnetized not merely application developers but also malware developers with criminal intention to design…

密码学与安全 · 计算机科学 2018-12-27 Abdelmonim Naway , Yuancheng LI

In the past decade, the cyber-crime related to mobile devices has increased. Mobile devices, especially the ones running on Android operating system are particularly interesting to malware creators, as the users often keep the biggest…

密码学与安全 · 计算机科学 2019-10-24 Nikola Milosevic , Junfan Huang

A growing number of threats to Android phones creates challenges for malware detection. Manually labeling the samples into benign or different malicious families requires tremendous human efforts, while it is comparably easy and cheap to…

密码学与安全 · 计算机科学 2017-04-21 Li Chen , Mingwei Zhang , Chih-Yuan Yang , Ravi Sahita