Aomdroid: detecting obfuscation variants of android malware using transfer learning

Y Jiang, R Li, J Tang, A Davanian, H Yin - … , DC, USA, October 21-23, 2020 …, 2020 - Springer
Android with its large market attracts malware developers. Malware developers employ
obfuscation techniques to bypass malware detection mechanisms. Existing systems cannot …

Obfusifier: Obfuscation-resistant android malware detection system

Z Li, J Sun, Q Yan, W Srisa-An, Y Tsutano - … , FL, USA, October 23-25, 2019 …, 2019 - Springer
The structure-changing obfuscation has become an effective means for malware authors to
create malicious apps that can evade the machine learning-based detection systems …

Android malware obfuscation variants detection method based on multi-granularity opcode features

J Tang, R Li, Y Jiang, X Gu, Y Li - Future Generation Computer Systems, 2022 - Elsevier
Android malware poses a serious security threat to ordinary mobile users. However, the
obfuscation technology can generate malware variants, which can bypass existing detection …

An Overview of Techniques for Obfuscated Android Malware Detection

S Siddiqui, TA Khan - SN Computer Science, 2024 - Springer
Obfuscation is a method to hide coding strategies for security and privacy. Despite its
positive use, malware experts have also used this technique to develop malware …

Utilizing obfuscation information in deep learning-based Android malware detection

J Wu, A Kanai - 2021 IEEE 45th Annual Computers, Software …, 2021 - ieeexplore.ieee.org
With the large number of Android applications being released, reliable Android malware
classifier is required. In recent years, machine learning as well as deep learning have …

Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism

S Aurangzeb, M Aleem - Scientific Reports, 2023 - nature.com
With the rise in popularity and usage of Android operating systems, malicious applications
are targeted by applying innovative ways and techniques. Today, malware becomes …

A large-scale investigation to identify the pattern of app component in obfuscated Android malwares

MOFK Russel, SSMM Rahman, T Islam - … 2020, Silchar, India, July 30-31 …, 2020 - Springer
Abstract Number of smartphone users of android based devices is growing rapidly. Because
of the popularity of the android market malware attackers are focusing in this area for their …

[PDF][PDF] De-LADY: Deep learning based Android malware detection using Dynamic features.

V Sihag, M Vardhan, P Singh, G Choudhary… - J. Internet Serv. Inf …, 2021 - jisis.org
Popularity and market share of Android operating system has given significant rise to
malicious apps targeting it. Traditional malware detection methods are obsolete as current …

AndroOBFS: time-tagged obfuscated Android malware dataset with family information

S Kumar, D Mishra, B Panda, SK Shukla - Proceedings of the 19th …, 2022 - dl.acm.org
With the large-scale adaptation of Android OS and ever-increasing contributions in the
Android application space, Android has become the number one target of malware writers …

[PDF][PDF] Impact of Code Obfuscation on Android Malware Detection based on Static and Dynamic Analysis.

A Bacci, A Bartoli, F Martinelli, E Medvet, F Mercaldo… - ICISSP, 2018 - scitepress.org
The huge diffusion of malware in mobile platform is plaguing users. New malware
proliferates at a very fast pace: as a matter of fact, to evade the signature-based mechanism …