The evolution of android malware and android analysis techniques

K Tam, A Feizollah, NB Anuar, R Salleh… - ACM Computing …, 2017 - dl.acm.org
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …

Internet of drones security: Taxonomies, open issues, and future directions

A Derhab, O Cheikhrouhou, A Allouch, A Koubaa… - Vehicular …, 2023 - Elsevier
Drones have recently become one of the most important technological breakthroughs. They
have opened the horizon for a vast array of applications and paved the way for a diversity of …

MAPAS: a practical deep learning-based android malware detection system

J Kim, Y Ban, E Ko, H Cho, JH Yi - International Journal of Information …, 2022 - Springer
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 …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

50 ways to leak your data: An exploration of apps' circumvention of the android permissions system

J Reardon, Á Feal, P Wijesekera, AEB On… - 28th USENIX security …, 2019 - usenix.org
Modern smartphone platforms implement permission-based models to protect access to
sensitive data and system resources. However, apps can circumvent the permission model …

Yes, machine learning can be more secure! a case study on android malware detection

A Demontis, M Melis, B Biggio… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
To cope with the increasing variability and sophistication of modern attacks, machine
learning has been widely adopted as a statistically-sound tool for malware detection …

Droidsieve: Fast and accurate classification of obfuscated android malware

G Suarez-Tangil, SK Dash, M Ahmadi… - Proceedings of the …, 2017 - dl.acm.org
With more than two million applications, Android marketplaces require automatic and
scalable methods to efficiently vet apps for the absence of malicious threats. Recent …

Detection approaches for android malware: Taxonomy and review analysis

HHR Manzil, SM Naik - Expert Systems with Applications, 2024 - Elsevier
The main objective of this review is to present an in-depth study of Android malware
detection approaches. This article provides a comprehensive survey of 150 studies on …

Understanding android obfuscation techniques: A large-scale investigation in the wild

S Dong, M Li, W Diao, X Liu, J Liu, Z Li, F Xu… - Security and privacy in …, 2018 - Springer
Program code is a valuable asset to its owner. Due to the easy-to-reverse nature of Java,
code protection for Android apps is of particular importance. To this end, code obfuscation is …

Android malware detection based on a hybrid deep learning model

T Lu, Y Du, L Ouyang, Q Chen… - Security and …, 2020 - Wiley Online Library
In recent years, the number of malware on the Android platform has been increasing, and
with the widespread use of code obfuscation technology, the accuracy of antivirus software …