Results 101 to 110 of about 20,533 (244)

Android Malware Detection by Correlated Real Permission Couples Using FP Growth Algorithm and Neural Networks [PDF]

, 2023
Abhinandan Banik, Jyoti Prakash Singh
openalex   +1 more source

An Effective Temporal Convolutional Networks-Based Method for Detecting Android Malware Using Dynamic Extracted Features

IEEE Access
With an increase in the number and complexity of malware, traditional malware detection methods such as heuristic-based and signature-based ones have become less adequate, leaving user applications vulnerable.
Abdurraheem Joomye, Mee Hong Ling, Muhammed Basheer Jasser, Athirah Mohd Ramly, Kok-Lim Alvin Yau   +4 more
doaj   +1 more source

A3CM: Automatic Capability Annotation for Android Malware

IEEE Access, 2019
Android malware poses serious security and privacy threats to the mobile users. Traditional malware detection and family classification technologies are becoming less effective due to the rapid evolution of the malware landscape, with the emerging of so ...
Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, Yu Wang, Yang Xiang   +6 more
doaj   +1 more source

Android Malware Detection Based on Feature Selection and Weight Measurement [PDF]

, 2022
Huizhong Sun, Guosheng Xu, Zhimin Wu, Ruijie Quan   +3 more
openalex   +1 more source

Using Dalvik opcodes for malware detection on android [PDF]

, 2017
José Gaviria de la Puerta, Borja Sanz
openalex   +1 more source

Explaining the Use of Cryptographic API in Android Malware [PDF]

, 2023
Adam Janovsky, Davide Maiorca, Dominik Macko, Vashek Matyáš, Giorgio Giacinto   +4 more
openalex   +1 more source

MADRAS-NET: A deep learning approach for detecting and classifying android malware using Linknet

Measurement: Sensors
Malware is an intentionally created malicious software that still poses a serious threat in cyberspace. Android malware has become one of the most significant online threats in recent years due to its increase in prevalence. Even though a lot of work has
Yi Wang, Shanshan Jia
doaj   +1 more source

AndroDFA: Android Malware Classification Based on Resource Consumption [PDF]

, 2020
Luca Massarelli, Leonardo Aniello, Claudio Ciccotelli, Leonardo Querzoni, Daniele Ucci, Roberto Baldoni   +5 more
openalex   +1 more source

Android malware dataset construction methodology to minimize bias–variance tradeoff

, 2021
Shinho Lee, Wookhyun Jung, Wonrak Lee, Hyung Geun Oh, Eui Tak Kim   +4 more
openalex   +1 more source

MalQwen: Fine Tuned LLM for Static Android Malware Analysis Report

IEEE Access
The Android operating system continues to face escalating security challenges, primarily due to its open-source nature and the rapid proliferation of applications from untrusted sources.
Tegar Ganang Satrio Priambodo, Angela Oryza Prabowo, Annisa Dwi Puspitarini, Raihan Adam Handoyo Winarso, Nur Aisyah, Mohammad Yoga Pratama, Diana Purwitasari, Baskoro Adi Pratomo   +7 more
doaj   +1 more source