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N-opcode Analysis for Android Malware Classification and Categorization

N-opcode Analysis for Android Malware Classification and Categorization

27 July 2016
Boojoong Kang
S. Yerima
K. Mclaughlin
S. Sezer
ArXiv (abs)PDFHTML

Papers citing "N-opcode Analysis for Android Malware Classification and Categorization"

12 / 12 papers shown
Detecting Android Malware by Visualizing App Behaviors from Multiple
  Complementary Views
Detecting Android Malware by Visualizing App Behaviors from Multiple Complementary ViewsIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2024
Zhaoyi Meng
Jiale Zhang
Jiaqi Guo
Wansen Wang
Wenchao Huang
Jie Cui
Hong Zhong
Yan Xiong
AAML
172
5
0
08 Oct 2024
ActDroid: An active learning framework for Android malware detection
ActDroid: An active learning framework for Android malware detection
Ali Muzaffar
H. R. Hassen
Hind Zantout
M. Lones
273
4
0
30 Jan 2024
Light up that Droid! On the Effectiveness of Static Analysis Features
  against App Obfuscation for Android Malware Detection
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection
Borja Molina-Coronado
Antonio Ruggia
U. Mori
Alessio Merlo
A. Mendiburu
J. Miguel-Alonso
AAML
204
6
0
24 Oct 2023
Reassessing feature-based Android malware detection in a contemporary context
Reassessing feature-based Android malware detection in a contemporary context
Ali Muzaffar
H. R. Hassen
Hind Zantout
M. Lones
234
5
0
30 Jan 2023
Fast and Efficient Malware Detection with Joint Static and Dynamic
  Features Through Transfer Learning
Fast and Efficient Malware Detection with Joint Static and Dynamic Features Through Transfer LearningInternational Conference on Applied Cryptography and Network Security (ACNS), 2022
Mao V. Ngo
Tram Truong-Huu
Dima Rabadi
Jia Yi Loo
Sin Gee Teo
115
10
0
25 Nov 2022
Adversarial Patterns: Building Robust Android Malware Classifiers
Adversarial Patterns: Building Robust Android Malware ClassifiersACM Computing Surveys (ACM CSUR), 2022
Dipkamal Bhusal
Nidhi Rastogi
AAML
370
9
0
04 Mar 2022
MG-DVD: A Real-time Framework for Malware Variant Detection Based on
  Dynamic Heterogeneous Graph Learning
MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning
Chen Liu
Yue Liu
Jun Zhao
Ming-shan Su
Xudong Liu
111
17
0
23 Jun 2021
Op2Vec: An Opcode Embedding Technique and Dataset Design for End-to-End
  Detection of Android Malware
Op2Vec: An Opcode Embedding Technique and Dataset Design for End-to-End Detection of Android MalwareSecurity and Communication Networks (SCN), 2021
Kaleem Nawaz Khan
Najeeb Ullah
Sikandar Ali
Muhammad Salman Khan
M. Nauman
Muhammad Yaseen Khan
143
10
0
10 Apr 2021
DL-Droid: Deep learning based android malware detection using real
  devices
DL-Droid: Deep learning based android malware detection using real devicesComputers & security (Comput. Secur.), 2019
Mohammed K. Alzaylaee
S. Yerima
S. Sezer
AAML
174
359
0
22 Nov 2019
New Era of Deeplearning-Based Malware Intrusion Detection: The Malware Detection and Prediction Based On Deep Learning
Shuqiang Lu
Lingyun Ying
Wenjie Lin
Yu Wang
Meining Nie
Kaiwen Shen
Lu Liu
Haixin Duan
314
11
0
19 Jul 2019
A Survey on the Detection of Android Malicious Apps
A Survey on the Detection of Android Malicious AppsAdvances in Intelligent Systems and Computing (AISC), 2019
S. K. Sahay
Ashu Sharma
102
8
0
30 May 2019
An investigation of the classifiers to detect android malicious apps
An investigation of the classifiers to detect android malicious apps
Ashu Sharma
S. K. Sahay
82
12
0
23 Feb 2018
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