logo

Detect Android malware by using deep learning: Experiment and Evaluation

RESEARCH CREW
12:59 05/01/2021

With the emergence of deep learning, recent years have witnessed a booming of artificial intelligence (AI) applications and services in many fields of modern society, ranging from face recognition to video surveillance to many recommendation systems. In addition, there is a tremendous increase in cyberattacks or data leakage which draws much attention from both the professional and the public due to the popularity of mobile devices like Android. Driving by this trend, many security approaches push AI or deep learning to Android malware detection to enhance the accuracy and capability of scanning or detecting systems. However, research on this field is still in the early stage since there is the diversity of deep learning models and a shortage of standardized Android datasets for evaluating the efficiency of each approach. To this end, we conduct a comparative study of famous deep learning models on one dataset to give an overview of their powers in providing the method of dissecting Android malware.

TIN LIÊN QUAN
PoFQ: A Blockchain Consensus Protocol for Decentralized Federated Learning-Based Threat Hunting Approach in a Trustless Computing Landscape
An empirical review of the effectiveness of different language processing approaches in Software Code Vulnerability Detection
The advancement of software vulnerability detection tools has accelerated in recent years, yet the prevalence and severity of vulnerabilities continue to escalate, posing significant threats to computer security and information safety. To address this, numerous detection methodologies have been proposed, with machine learning-based approaches demonstrating notable promise. In this paper,...
RAX-ClaMal: Dynamic Android malware classification based on RAX register values
Detecting malware on Android remains a major challenge because malicious apps use sophisticated evasion techniques. This study presents RAX-ClaMal, a novel approach leveraging dynamic analysis of RAX (Register a Extended) register values for Android malware detection. By extracting and examining the RAX register in the data sections from Dalvik Executable...