Deep Ground Truth Analysis of Current Android Malware

By Fengguo Wei, Yuping Li, Sankardas Roy, Xinming Ou, Wu Zhou. International Conference on Detection of intrusions and malware, and vulnerability assessment, 2017

418 citations recorded by the source corpus.

Subfields: Information Systems, Software, Signal Processing

View Paper: https://www.semanticscholar.org/paper/c58e3b32bc88ed3d8e7bcdf0523eb27057bd7d0f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Surya Nepal
2. Ali Akbar Ghorbani
3. Arash Habibi Lashkari
4. Jun Zhang
5. Yang Liu
6. Yang Xiang

In Software

1. Surya Nepal
2. Annamalai Narayanan
3. Jun Zhang
4. Yang Liu
5. Lihui Chen
6. Yang Xiang

In Signal Processing

1. Wei Luo
2. Surya Nepal
3. Ali Akbar Ghorbani
4. Arash Habibi Lashkari
5. Annamalai Narayanan
6. Lei Pan
7. Junyang Qiu
8. Jun Zhang

Citations in the corpus

• Toward Developing a Systematic Approach to Generate Benchmark Android Malware Datasets and Classification (2018, methodology): “Besides this dataset, the AMD dataset[16] is another pub-”
• A Survey of Android Malware Detection with Deep Neural Models (2020, methodology): “The first method is the dominant keyword algorithm [45].”
• graph2vec: Learning Distributed Representations of Graphs (2017, methodology): “To this end, we consider the AMD dataset [13] which comprises of more than 24,000 Android malware apps belonging to 71 families.”