Results 281 to 290 of about 222,584 (313)

AndroidLab: Training and Systematic Benchmarking of Android Autonomous Agents

arXiv.org
Autonomous agents have become increasingly important for interacting with the real world. Android agents, in particular, have been recently a frequently-mentioned interaction method.
Yifan Xu, Xiao Liu, Xueqiao Sun, Siyi Cheng, Yun-Hao Liu, Hanyu Lai, Shudan Zhang, Dan Zhang, Jie Tang, Yuxiao Dong   +9 more
semanticscholar   +1 more source

Reinforcement learning based curiosity-driven testing of Android applications

International Symposium on Software Testing and Analysis, 2020
Mobile applications play an important role in our daily life, while it still remains a challenge to guarantee their correctness. Model-based and systematic approaches have been applied to Android GUI testing.
Minxue Pan, An Huang, Guoxin Wang, Tian Zhang, Xuandong Li   +4 more
semanticscholar   +1 more source

EntropLyzer: Android Malware Classification and Characterization Using Entropy Analysis of Dynamic Characteristics

2021 Reconciling Data Analytics, Automation, Privacy, and Security: A Big Data Challenge (RDAAPS), 2021
The unmatched threat of Android malware has tremendously increased the need for analyzing prominent malware samples. There are remarkable efforts in static and dynamic malware analysis using static features and API calls respectively.
David S. Keyes, Beiqi Li, Gurdip Kaur, Arash Habibi Lashkari, F. Gagnon, Frédéric Massicotte   +5 more
semanticscholar   +1 more source

DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling

IEEE Transactions on Information Forensics and Security, 2019
Most existing Android malware detection and categorization techniques are static approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program behaviors, dynamic approaches are potentially more resilient against these attacks ...
Haipeng Cai, Na Meng, B. Ryder, Daphne Yao   +3 more
semanticscholar   +1 more source

PermPair: Android Malware Detection Using Permission Pairs

IEEE Transactions on Information Forensics and Security, 2020
The Android smartphones are highly prone to spreading the malware due to intrinsic feebleness that permits an application to access the internal resources when the user grants the permissions knowingly or unknowingly.
Anshul Arora, S. K. Peddoju, M. Conti
semanticscholar   +1 more source

AI Benchmark: Running Deep Neural Networks on Android Smartphones

ECCV Workshops, 2018
Over the last years, the computational power of mobile devices such as smartphones and tablets has grown dramatically, reaching the level of desktop computers available not long ago.
Andrey D. Ignatov, R. Timofte, William Chou, Ke Wang, Max Wu, Tim Hartley, L. Gool   +6 more
semanticscholar   +1 more source

Toward Developing a Systematic Approach to Generate Benchmark Android Malware Datasets and Classification

International Carnahan Conference on Security Technology, 2018
Malware detection is one of the most important factors in the security of smartphones. Academic researchers have extensively studied Android malware detection problems.
Arash Habibi Lashkari, A. A. Kadir, Laya Taheri, A. Ghorbani   +3 more
semanticscholar   +1 more source

Effective and Efficient Hybrid Android Malware Classification Using Pseudo-Label Stacked Auto-Encoder

Journal of Network and Systems Management, 2021
Samaneh Mahdavifar, Dima Alhadidi, A. Ghorbani   +2 more
semanticscholar   +1 more source

FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps

ACM-SIGPLAN Symposium on Programming Language Design and Implementation, 2014
Steven Arzt, Siegfried Rasthofer, Christian G Fritz, E. Bodden, Alexandre Bartel, Jacques Klein, Y. L. Traon, Damien Octeau, P. Mcdaniel   +8 more
semanticscholar   +1 more source

HamDroid: permission-based harmful android anti-malware detection using neural networks

Neural computing & applications (Print), 2022
Saeed Seraj, Siavash Khodambashi, Michalis Pavlidis, Nikolaos Polatidis   +3 more
semanticscholar   +1 more source