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Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated…

密码学与安全 · 计算机科学 2016-07-28 BooJoong Kang , Suleiman Y. Yerima , Kieran McLaughlin , Sakir Sezer

The emergence of mobile platforms with increased storage and computing capabilities and the pervasive use of these platforms for sensitive applications such as online banking, e-commerce and the storage of sensitive information on these…

密码学与安全 · 计算机科学 2015-12-15 Joshua Abah , Waziri O. , Abdullahi M. B , Arthur U. M , Adewale O. S

Thousands of malicious applications targeting mobile devices, including the popular Android platform, are created every day. A large number of those applications are created by a small number of professional under-ground actors, however…

密码学与安全 · 计算机科学 2019-03-06 Hyunjae Kang , Jae-wook Jang , Aziz Mohaisen , Huy Kang Kim

The Android operating system is the most spread mobile platform in the world. Therefor attackers are producing an incredible number of malware applications for Android. Our aim is to detect Android's malware in order to protect the user. To…

密码学与安全 · 计算机科学 2021-04-09 Alain Menelet , Charles-Edmond Bichot

Android Malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and…

密码学与安全 · 计算机科学 2017-12-13 Ignacio Martín , José Alberto Hernández , Alfonso Muñoz , Antonio Guzmán

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

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

The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper…

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

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

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

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

This study examines machine learning techniques like Decision Trees, Support Vector Machines, Logistic Regression, Neural Networks, and ensemble methods to detect Android malware. The study evaluates these models on a dataset of Android…

密码学与安全 · 计算机科学 2025-11-04 Hasan Abdulla

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 digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication.…

密码学与安全 · 计算机科学 2023-07-18 Alexander Hefter , Christoph Sendner , Alexandra Dmitrienko

Malware for Android is becoming increasingly dangerous to the safety of mobile devices and the data they hold. Although machine learning(ML) techniques have been shown to be effective at detecting malware for Android, a comprehensive…

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

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

Android malware is one of the most dangerous threats on the internet, and it's been on the rise for several years. Despite significant efforts in detecting and classifying android malware from innocuous android applications, there is still…

密码学与安全 · 计算机科学 2021-07-06 Ahmed Hashem El Fiky , Ayman El Shenawy , Mohamed Ashraf Madkour

We investigate the use of Android permissions as the vehicle to allow for quick and effective differentiation between benign and malware apps. To this end, we extract all Android permissions, eliminating those that have zero impact, and…

密码学与安全 · 计算机科学 2022-01-24 Muhammad Suleman Saleem , Jelena Mišić , Vojislav B. Mišić

Since Google unveiled Android OS for smartphones, malware are thriving with 3Vs, i.e. volume, velocity, and variety. A recent report indicates that one out of every five business/industry mobile application leaks sensitive personal data.…

密码学与安全 · 计算机科学 2021-03-02 Hemant Rathore , Sanjay K. Sahay , Ritvik Rajvanshi , Mohit Sewak
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