Saved in:
| Main Authors: | Zhang, Guangyu, Wang, Xixuan, Sun, Shiyu, Xiao, Peiyan, Sun, Kun, Xiong, Yanhai |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.08865 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Detecting Android Malware by Visualizing App Behaviors from Multiple Complementary Views
by: Meng, Zhaoyi, et al.
Published: (2024)
by: Meng, Zhaoyi, et al.
Published: (2024)
MARD: A Multi-Agent Framework for Robust Android Malware Detection
by: Zeng, Xueying, et al.
Published: (2026)
by: Zeng, Xueying, et al.
Published: (2026)
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
by: Song, Shiwen, et al.
Published: (2025)
by: Song, Shiwen, et al.
Published: (2025)
MalFlows: Context-aware Fusion of Heterogeneous Flow Semantics for Android Malware Detection
by: Meng, Zhaoyi, et al.
Published: (2025)
by: Meng, Zhaoyi, et al.
Published: (2025)
DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware
by: Sun, Tiezhu, et al.
Published: (2024)
by: Sun, Tiezhu, et al.
Published: (2024)
Enhancing Android Malware Detection: The Influence of ChatGPT on Decision-centric Task
by: Li, Yao, et al.
Published: (2024)
by: Li, Yao, et al.
Published: (2024)
MASKDROID: Robust Android Malware Detection with Masked Graph Representations
by: Zheng, Jingnan, et al.
Published: (2024)
by: Zheng, Jingnan, et al.
Published: (2024)
XTrace: A Non-Invasive Dynamic Tracing Framework for Android Applications in Production
by: Hu, Qi, et al.
Published: (2025)
by: Hu, Qi, et al.
Published: (2025)
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems
by: He, Ping, et al.
Published: (2025)
by: He, Ping, et al.
Published: (2025)
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
by: Bostani, Hamid, et al.
Published: (2024)
by: Bostani, Hamid, et al.
Published: (2024)
Enhancing LLM-Based Bug Reproduction for Android Apps via Pre-Assessment of Visual Effects
by: Xiao, Xiangyang, et al.
Published: (2026)
by: Xiao, Xiangyang, et al.
Published: (2026)
Assessing the Capability of Android Dynamic Analysis Tools to Combat Anti-Runtime Analysis Techniques
by: Suo, Dewen, et al.
Published: (2025)
by: Suo, Dewen, et al.
Published: (2025)
GDPR-Bench-Android: A Benchmark for Evaluating Automated GDPR Compliance Detection in Android
by: Ran, Huaijin, et al.
Published: (2025)
by: Ran, Huaijin, et al.
Published: (2025)
Same App, Different Behaviors: Uncovering Device-specific Behaviors in Android Apps
by: Dong, Zikan, et al.
Published: (2024)
by: Dong, Zikan, et al.
Published: (2024)
Bamboo: LLM-Driven Discovery of API-Permission Mappings in the Android Framework
by: Hu, Han, et al.
Published: (2025)
by: Hu, Han, et al.
Published: (2025)
SemOpt: LLM-Driven Code Optimization via Rule-Based Analysis
by: Zhao, Yuwei, et al.
Published: (2025)
by: Zhao, Yuwei, et al.
Published: (2025)
AgentDroid: A Multi-Agent Framework for Detecting Fraudulent Android Applications
by: Pan, Ruwei, et al.
Published: (2025)
by: Pan, Ruwei, et al.
Published: (2025)
DynamicsLLM: a Dynamic Analysis-based Tool for Generating Intelligent Execution Traces Using LLMs to Detect Android Behavioural Code Smells
by: Cherief, Houcine Abdelkader, et al.
Published: (2026)
by: Cherief, Houcine Abdelkader, et al.
Published: (2026)
Integrating APK Image and Text Data for Enhanced Threat Detection: A Multimodal Deep Learning Approach to Android Malware
by: Arifin, Md Mashrur, et al.
Published: (2026)
by: Arifin, Md Mashrur, et al.
Published: (2026)
LDMDroid: Leveraging LLMs for Detecting Data Manipulation Errors in Android Apps
by: Xiao, Xiangyang, et al.
Published: (2026)
by: Xiao, Xiangyang, et al.
Published: (2026)
Explainable Fault Localization for Programming Assignments via LLM-Guided Annotation
by: Liu, Fang, et al.
Published: (2025)
by: Liu, Fang, et al.
Published: (2025)
Rethinking and Exploring String-Based Malware Family Classification in the Era of LLMs and RAG
by: Chen, Yufan, et al.
Published: (2025)
by: Chen, Yufan, et al.
Published: (2025)
ARAP: Demystifying Anti Runtime Analysis Code in Android Apps
by: Suo, Dewen, et al.
Published: (2024)
by: Suo, Dewen, et al.
Published: (2024)
TreeMind: Automatically Reproducing Android Bug Reports via LLM-empowered Monte Carlo Tree Search
by: Chen, Zhengyu, et al.
Published: (2025)
by: Chen, Zhengyu, et al.
Published: (2025)
Which Code Statements Implement Privacy Behaviors in Android Applications?
by: Su, Chia-Yi, et al.
Published: (2025)
by: Su, Chia-Yi, et al.
Published: (2025)
Synergistic Directed Execution and LLM-Driven Analysis for Zero-Day AI-Generated Malware Detection
by: Edwards, George, et al.
Published: (2026)
by: Edwards, George, et al.
Published: (2026)
A Pilot Study on LLM-Based Agentic Translation from Android to iOS: Pitfalls and Insights
by: Zeng, Zhili, et al.
Published: (2025)
by: Zeng, Zhili, et al.
Published: (2025)
Feedback-Driven Automated Whole Bug Report Reproduction for Android Apps
by: Wang, Dingbang, et al.
Published: (2024)
by: Wang, Dingbang, et al.
Published: (2024)
TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code
by: Huang, Jiangping, et al.
Published: (2026)
by: Huang, Jiangping, et al.
Published: (2026)
Call Graph Soundness in Android Static Analysis
by: Samhi, Jordan, et al.
Published: (2024)
by: Samhi, Jordan, et al.
Published: (2024)
A Large-scale Investigation of Semantically Incompatible APIs behind Compatibility Issues in Android Apps
by: Pan, Shidong, et al.
Published: (2024)
by: Pan, Shidong, et al.
Published: (2024)
Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis
by: Yang, Xixuan, et al.
Published: (2025)
by: Yang, Xixuan, et al.
Published: (2025)
Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
by: Du, Xueying, et al.
Published: (2024)
by: Du, Xueying, et al.
Published: (2024)
FusionLog: Cross-System Log-based Anomaly Detection via Fusion of General and Proprietary Knowledge
by: Zhao, Xinlong, et al.
Published: (2025)
by: Zhao, Xinlong, et al.
Published: (2025)
Towards Explainable Vulnerability Detection with Large Language Models
by: Mao, Qiheng, et al.
Published: (2024)
by: Mao, Qiheng, et al.
Published: (2024)
Identifying Adversary Tactics and Techniques in Malware Binaries with an LLM Agent
by: Xuan, Zhou, et al.
Published: (2026)
by: Xuan, Zhou, et al.
Published: (2026)
AndroLog: Android Instrumentation and Code Coverage Analysis
by: Samhi, Jordan, et al.
Published: (2024)
by: Samhi, Jordan, et al.
Published: (2024)
A Comparative Study of Android Performance Issues in Real-world Applications and Literature
by: Liao, Dianshu, et al.
Published: (2024)
by: Liao, Dianshu, et al.
Published: (2024)
AutoDroid: LLM-powered Task Automation in Android
by: Wen, Hao, et al.
Published: (2023)
by: Wen, Hao, et al.
Published: (2023)
Can Large Language Models Detect Real-World Android Software Compliance Violations?
by: Zhang, Haoyi, et al.
Published: (2025)
by: Zhang, Haoyi, et al.
Published: (2025)
Similar Items
-
Detecting Android Malware by Visualizing App Behaviors from Multiple Complementary Views
by: Meng, Zhaoyi, et al.
Published: (2024) -
MARD: A Multi-Agent Framework for Robust Android Malware Detection
by: Zeng, Xueying, et al.
Published: (2026) -
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
by: Song, Shiwen, et al.
Published: (2025) -
MalFlows: Context-aware Fusion of Heterogeneous Flow Semantics for Android Malware Detection
by: Meng, Zhaoyi, et al.
Published: (2025) -
DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware
by: Sun, Tiezhu, et al.
Published: (2024)