SAFELOC: Overcoming Data Poisoning Attacks in Heterogeneous Federated Machine Learning for Indoor Localization
Fuente:
arXiv
Saved in:
| Main Authors: | Singampalli, Akhil, Gufran, Danish, Pasricha, Sudeep |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ARMOR: Adaptive Resilience Against Model Poisoning Attacks in Continual Federated Learning for Mobile Indoor Localization
by: Gufran, Danish, et al.
Published: (2026)
by: Gufran, Danish, et al.
Published: (2026)
DAILOC: Domain-Incremental Learning for Indoor Localization using Smartphones
by: Singampalli, Akhil, et al.
Published: (2025)
by: Singampalli, Akhil, et al.
Published: (2025)
SENTINEL: Securing Indoor Localization against Adversarial Attacks with Capsule Neural Networks
by: Gufran, Danish, et al.
Published: (2024)
by: Gufran, Danish, et al.
Published: (2024)
Unified Class and Domain Incremental Learning with Mixture of Experts for Indoor Localization
by: Singampalli, Akhil, et al.
Published: (2025)
by: Singampalli, Akhil, et al.
Published: (2025)
Towards Explainable Indoor Localization: Interpreting Neural Network Learning on Wi-Fi Fingerprints Using Logic Gates
by: Gufran, Danish, et al.
Published: (2025)
by: Gufran, Danish, et al.
Published: (2025)
GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices
by: Gufran, Danish, et al.
Published: (2025)
by: Gufran, Danish, et al.
Published: (2025)
SANGRIA: Stacked Autoencoder Neural Networks with Gradient Boosting for Indoor Localization
by: Gufran, Danish, et al.
Published: (2024)
by: Gufran, Danish, et al.
Published: (2024)
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
by: Zuo, Shiyuan, et al.
Published: (2024)
by: Zuo, Shiyuan, et al.
Published: (2024)
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
by: Zhang, Heyi, et al.
Published: (2025)
by: Zhang, Heyi, et al.
Published: (2025)
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)
by: Xu, Zhangchen, et al.
Published: (2024)
GFCL: A GRU-based Federated Continual Learning Framework against Data Poisoning Attacks in IoV
by: Talpur, Anum, et al.
Published: (2022)
by: Talpur, Anum, et al.
Published: (2022)
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning
by: Meerza, Syed Irfan Ali, et al.
Published: (2024)
by: Meerza, Syed Irfan Ali, et al.
Published: (2024)
AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems
by: Pasricha, Sudeep
Published: (2024)
by: Pasricha, Sudeep
Published: (2024)
Machine Unlearning Fails to Remove Data Poisoning Attacks
by: Pawelczyk, Martin, et al.
Published: (2024)
by: Pawelczyk, Martin, et al.
Published: (2024)
Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning
by: Zhang, Yujie, et al.
Published: (2024)
by: Zhang, Yujie, et al.
Published: (2024)
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
by: Di, Jimmy Z., et al.
Published: (2022)
by: Di, Jimmy Z., et al.
Published: (2022)
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
by: Lobo, Elita, et al.
Published: (2024)
by: Lobo, Elita, et al.
Published: (2024)
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
by: Gabrielli, Edoardo, et al.
Published: (2023)
by: Gabrielli, Edoardo, et al.
Published: (2023)
Local Model Reconstruction Attacks in Federated Learning and their Uses
by: Driouich, Ilias, et al.
Published: (2022)
by: Driouich, Ilias, et al.
Published: (2022)
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models
by: Xu, Yuancheng, et al.
Published: (2024)
by: Xu, Yuancheng, et al.
Published: (2024)
Data Overvaluation Attack and Truthful Data Valuation in Federated Learning
by: Zheng, Shuyuan, et al.
Published: (2025)
by: Zheng, Shuyuan, et al.
Published: (2025)
UIFV: Data Reconstruction Attack in Vertical Federated Learning
by: Yang, Jirui, et al.
Published: (2024)
by: Yang, Jirui, et al.
Published: (2024)
Poisoning Attacks on Federated Learning for Autonomous Driving
by: Garg, Sonakshi, et al.
Published: (2024)
by: Garg, Sonakshi, et al.
Published: (2024)
Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learning
by: Xu, Yinglun, et al.
Published: (2024)
by: Xu, Yinglun, et al.
Published: (2024)
Privacy-Preserving Heterogeneous Federated Learning for Sensitive Healthcare Data
by: Xu, Yukai, et al.
Published: (2024)
by: Xu, Yukai, et al.
Published: (2024)
Stealthy Poisoning Attacks Bypass Defenses in Regression Settings
by: Carnerero-Cano, Javier, et al.
Published: (2026)
by: Carnerero-Cano, Javier, et al.
Published: (2026)
Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks
by: Halloran, John T., et al.
Published: (2026)
by: Halloran, John T., et al.
Published: (2026)
Defending Against Poisoning Attacks in Federated Learning with Blockchain
by: Dong, Nanqing, et al.
Published: (2023)
by: Dong, Nanqing, et al.
Published: (2023)
FedReview: A Review Mechanism for Rejecting Poisoned Updates in Federated Learning
by: Zheng, Tianhang, et al.
Published: (2024)
by: Zheng, Tianhang, et al.
Published: (2024)
Have You Poisoned My Data? Defending Neural Networks against Data Poisoning
by: De Gaspari, Fabio, et al.
Published: (2024)
by: De Gaspari, Fabio, et al.
Published: (2024)
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
by: Liu, Yi, et al.
Published: (2024)
by: Liu, Yi, et al.
Published: (2024)
Local Environment Poisoning Attacks on Federated Reinforcement Learning
by: Ma, Evelyn, et al.
Published: (2023)
by: Ma, Evelyn, et al.
Published: (2023)
Semantic Chameleon: Corpus-Dependent Poisoning Attacks and Defenses in RAG Systems
by: Thornton, Scott
Published: (2026)
by: Thornton, Scott
Published: (2026)
Scaling Trends for Data Poisoning in LLMs
by: Bowen, Dillon, et al.
Published: (2024)
by: Bowen, Dillon, et al.
Published: (2024)
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning
by: Diana, Francesco, et al.
Published: (2025)
by: Diana, Francesco, et al.
Published: (2025)
Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks
by: Nowroozi, Ehsan, et al.
Published: (2024)
by: Nowroozi, Ehsan, et al.
Published: (2024)
Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data
by: Baumgärtner, Tim, et al.
Published: (2024)
by: Baumgärtner, Tim, et al.
Published: (2024)
Reasoning Introduces New Poisoning Attacks Yet Makes Them More Complicated
by: Foerster, Hanna, et al.
Published: (2025)
by: Foerster, Hanna, et al.
Published: (2025)
False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
by: Uddin, Md Raihan, et al.
Published: (2024)
by: Uddin, Md Raihan, et al.
Published: (2024)
Heterogeneous Graph Backdoor Attack
by: Chen, Jiawei, et al.
Published: (2025)
by: Chen, Jiawei, et al.
Published: (2025)
Similar Items
-
ARMOR: Adaptive Resilience Against Model Poisoning Attacks in Continual Federated Learning for Mobile Indoor Localization
by: Gufran, Danish, et al.
Published: (2026) -
DAILOC: Domain-Incremental Learning for Indoor Localization using Smartphones
by: Singampalli, Akhil, et al.
Published: (2025) -
SENTINEL: Securing Indoor Localization against Adversarial Attacks with Capsule Neural Networks
by: Gufran, Danish, et al.
Published: (2024) -
Unified Class and Domain Incremental Learning with Mixture of Experts for Indoor Localization
by: Singampalli, Akhil, et al.
Published: (2025) -
Towards Explainable Indoor Localization: Interpreting Neural Network Learning on Wi-Fi Fingerprints Using Logic Gates
by: Gufran, Danish, et al.
Published: (2025)