Through the Looking Glass: LLM-Based Analysis of AR/VR Android Applications Privacy Policies
Fuente:
arXiv
Saved in:
| Main Authors: | Alghamdi, Abdulaziz, Mohaisen, David |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Comprehensive Analysis of Evolving Permission Usage in Android Apps: Trends, Threats, and Ecosystem Insights
by: Alkinoon, Ali, et al.
Published: (2025)
by: Alkinoon, Ali, et al.
Published: (2025)
Fishing for Phishers: Learning-Based Phishing Detection in Ethereum Transactions
by: Alghuried, Ahod, et al.
Published: (2025)
by: Alghuried, Ahod, et al.
Published: (2025)
Understanding Concept Drift with Deprecated Permissions in Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)
by: Sabbah, Ahmed, et al.
Published: (2025)
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)
by: Sabbah, Ahmed, et al.
Published: (2025)
Simple Perturbations Subvert Ethereum Phishing Transactions Detection: An Empirical Analysis
by: Alghureid, Ahod, et al.
Published: (2024)
by: Alghureid, Ahod, et al.
Published: (2024)
Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations
by: Alghuried, Ahod, et al.
Published: (2025)
by: Alghuried, Ahod, et al.
Published: (2025)
Evaluating Large Language Models in Vulnerability Detection Under Variable Context Windows
by: Lin, Jie, et al.
Published: (2025)
by: Lin, Jie, et al.
Published: (2025)
Adversarial Vulnerability Under Temporal Concept Drift: A Longitudinal Study of Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)
by: Sabbah, Ahmed, et al.
Published: (2026)
A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development
by: Kharma, Mohammed, et al.
Published: (2026)
by: Kharma, Mohammed, et al.
Published: (2026)
Concept Drift Adaptation Using Self-Supervised and Reinforcement Learning In Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)
by: Sabbah, Ahmed, et al.
Published: (2026)
Enhancing Reliability in LLM-Based Secure Code Generation
by: Kharma, Mohammed F., et al.
Published: (2026)
by: Kharma, Mohammed F., et al.
Published: (2026)
Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
by: Kharma, Mohammed, et al.
Published: (2025)
by: Kharma, Mohammed, et al.
Published: (2025)
Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques
by: Jaffal, Niveen O., et al.
Published: (2025)
by: Jaffal, Niveen O., et al.
Published: (2025)
Taking off the Rose-Tinted Glasses: A Critical Look at Adversarial ML Through the Lens of Evasion Attacks
by: Eykholt, Kevin, et al.
Published: (2024)
by: Eykholt, Kevin, et al.
Published: (2024)
LLM-Generated Samples for Android Malware Detection
by: Rollinson, Nik, et al.
Published: (2025)
by: Rollinson, Nik, et al.
Published: (2025)
An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods
by: Kharma, Mohammed, et al.
Published: (2026)
by: Kharma, Mohammed, et al.
Published: (2026)
Enhancing Vulnerability Reports with Automated and Augmented Description Summarization
by: Althebeiti, Hattan, et al.
Published: (2025)
by: Althebeiti, Hattan, et al.
Published: (2025)
On Benchmarking Code LLMs for Android Malware Analysis
by: He, Yiling, et al.
Published: (2025)
by: He, Yiling, et al.
Published: (2025)
LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift Analysis
by: Haque, Md Ahsanul, et al.
Published: (2025)
by: Haque, Md Ahsanul, et al.
Published: (2025)
Memories Retrieved from Many Paths: A Multi-Prefix Framework for Robust Detection of Training Data Leakage in Large Language Models
by: Dang, Trung Cuong, et al.
Published: (2025)
by: Dang, Trung Cuong, et al.
Published: (2025)
XAI and Android Malware Models
by: Kulkarni, Maithili, et al.
Published: (2024)
by: Kulkarni, Maithili, et al.
Published: (2024)
Android Malware Detection Based on RGB Images and Multi-feature Fusion
by: Wang, Zhiqiang, et al.
Published: (2024)
by: Wang, Zhiqiang, et al.
Published: (2024)
Free Record-Level Privacy Risk Evaluation Through Artifact-Based Methods
by: Pollock, Joseph, et al.
Published: (2024)
by: Pollock, Joseph, et al.
Published: (2024)
PrivacySIM: Evaluating LLM Simulation of User Privacy Behavior
by: Flemings, James, et al.
Published: (2026)
by: Flemings, James, et al.
Published: (2026)
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
by: Cundy, Chris, et al.
Published: (2020)
by: Cundy, Chris, et al.
Published: (2020)
mPSAuth: Privacy-Preserving and Scalable Authentication for Mobile Web Applications
by: Monschein, David, et al.
Published: (2022)
by: Monschein, David, et al.
Published: (2022)
Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication
by: Li, Mingjun, et al.
Published: (2024)
by: Li, Mingjun, et al.
Published: (2024)
Building a Robust Risk-Based Access Control System to Combat Ransomware's Capability to Encrypt
by: Begovic, Kenan, et al.
Published: (2026)
by: Begovic, Kenan, et al.
Published: (2026)
R+R: Revisiting Static Feature-Based Android Malware Detection using Machine Learning
by: Alam, Md Tanvirul, et al.
Published: (2024)
by: Alam, Md Tanvirul, et al.
Published: (2024)
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
by: Nadimi, Fardis, et al.
Published: (2025)
by: Nadimi, Fardis, et al.
Published: (2025)
Regression-aware Continual Learning for Android Malware Detection
by: Ghiani, Daniele, et al.
Published: (2025)
by: Ghiani, Daniele, et al.
Published: (2025)
Adversarial Patterns: Building Robust Android Malware Classifiers
by: Bhusal, Dipkamal, et al.
Published: (2022)
by: Bhusal, Dipkamal, et al.
Published: (2022)
Quantifying the Generalization Gap: A New Benchmark for Out-of-Distribution Graph-Based Android Malware Classification
by: Tran, Ngoc N., et al.
Published: (2025)
by: Tran, Ngoc N., et al.
Published: (2025)
Preventing Prompt Injection with Type-Directed Privilege Separation
by: Jacob, Dennis, et al.
Published: (2025)
by: Jacob, Dennis, et al.
Published: (2025)
Optimizing Privacy and Utility Tradeoffs for Group Interests Through Harmonization
by: Mandal, Bishwas, et al.
Published: (2024)
by: Mandal, Bishwas, et al.
Published: (2024)
Unraveling the Key of Machine Learning-based Android Malware Detection
by: Liu, Jiahao, et al.
Published: (2024)
by: Liu, Jiahao, et al.
Published: (2024)
SoK: Privacy-aware LLM in Healthcare: Threat Model, Privacy Techniques, Challenges and Recommendations
by: Tahera, Mohoshin Ara, et al.
Published: (2026)
by: Tahera, Mohoshin Ara, et al.
Published: (2026)
Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications
by: Jandali, Yaman, et al.
Published: (2025)
by: Jandali, Yaman, et al.
Published: (2025)
Privacy Amplification Through Synthetic Data: Insights from Linear Regression
by: Pierquin, Clément, et al.
Published: (2025)
by: Pierquin, Clément, et al.
Published: (2025)
Reassessing feature-based Android malware detection in a contemporary context
by: Muzaffar, Ali, et al.
Published: (2023)
by: Muzaffar, Ali, et al.
Published: (2023)
Similar Items
-
A Comprehensive Analysis of Evolving Permission Usage in Android Apps: Trends, Threats, and Ecosystem Insights
by: Alkinoon, Ali, et al.
Published: (2025) -
Fishing for Phishers: Learning-Based Phishing Detection in Ethereum Transactions
by: Alghuried, Ahod, et al.
Published: (2025) -
Understanding Concept Drift with Deprecated Permissions in Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025) -
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025) -
Simple Perturbations Subvert Ethereum Phishing Transactions Detection: An Empirical Analysis
by: Alghureid, Ahod, et al.
Published: (2024)