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Eight Years of Rider Measurement in the Android Malware Ecosystem:
  Evolution and Lessons Learned

Eight Years of Rider Measurement in the Android Malware Ecosystem: Evolution and Lessons Learned

24 January 2018
Guillermo Suarez-Tangil
Gianluca Stringhini
ArXivPDFHTML

Papers citing "Eight Years of Rider Measurement in the Android Malware Ecosystem: Evolution and Lessons Learned"

5 / 5 papers shown
Title
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
Shiwen Song
Xiaofei Xie
Ruitao Feng
Qi Guo
Sen Chen
AAML
45
0
0
28 Apr 2025
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion
  Detection
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection
Giovanni Apruzzese
Pavel Laskov
J. Schneider
53
25
0
30 Apr 2023
DeepCatra: Learning Flow- and Graph-based Behaviors for Android Malware
  Detection
DeepCatra: Learning Flow- and Graph-based Behaviors for Android Malware Detection
Yafei Wu
Jian Shi
Peicheng Wang
Dongrui Zeng
Cong Sun
14
30
0
30 Jan 2022
How Did That Get In My Phone? Unwanted App Distribution on Android
  Devices
How Did That Get In My Phone? Unwanted App Distribution on Android Devices
Platon Kotzias
Juan Caballero
Leyla Bilge
MedIm
48
36
0
20 Oct 2020
MadDroid: Characterising and Detecting Devious Ad Content for Android
  Apps
MadDroid: Characterising and Detecting Devious Ad Content for Android Apps
Tianming Liu
Haoyu Wang
Li Li
Xiapu Luo
Feng Dong
Yao Guo
Liu Wang
Tegawende F. Bissyande
Jacques Klein
16
34
0
05 Feb 2020
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