Jamming Attack

Jamming attacks disrupt wireless communication systems by interfering with signals, compromising the reliability of applications reliant on accurate positioning and data transmission. Current research focuses on developing robust detection and mitigation strategies using machine learning, particularly convolutional neural networks and other classifiers, often incorporating techniques like federated learning to address data privacy concerns in training models. These efforts are crucial for securing various wireless technologies, including 5G networks, UAV communications, and GNSS systems, and improving the resilience of these systems against malicious interference.

Papers

October 3, 2024

Achieving Generalization in Orchestrating GNSS Interference Monitoring Stations Through Pseudo-Labeling
Lucas Heublein, Tobias Feigl, Alexander Rügamer, Felix Ott
Machine Learning Strong Generalization Global Navigation Satellite System Robust Classification Optimal Service Station Design Jamming Attack

September 23, 2024

Evaluating ML Robustness in GNSS Interference Classification, Characterization \& Localization
Lucas Heublein, Tobias Feigl, Thorsten Nowak, Alexander Rügamer, Christopher Mutschler, Felix Ott
Localization Focus New Characterization Global Navigation Satellite System Catastrophic Interference Single Snapshot Jamming Attack Machine Learning Robustness Multipath Propagation

May 7, 2024

May 6, 2024

Enhancing O-RAN Security: Evasion Attacks and Robust Defenses for Graph Reinforcement Learning-based Connection Management
Ravikumar Balakrishnan, Marius Arvinte, Nageen Himayat, Hosein Nikopour, Hassnaa Moustafa
Adversarial Attack Adversarial Learning Robust Defense Evasion Attack Open Radio Access Network RAN Architecture Jamming Attack

April 6, 2024

Securing the Skies: An IRS-Assisted AoI-Aware Secure Multi-UAV System with Efficient Task Offloading
Poorvi Joshi, Alakesh Kalita, Mohan Gurusamy
Unmanned Aerial Vehicle UAV Network Computation Offloading Night Sky Jamming Attack

March 5, 2024

DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs
Ghazal Asemian, Mohammadreza Amini, Burak Kantarci, Melike Erol-Kantarci
Synchronization Parameter Update Barrier Physical Layer Novel RF Editing Pipeline Jamming Attack Connected and Automated Vehicle Jamming Detection

June 5, 2023

Jammer classification with Federated Learning
Peng Wu, Helena Calatrava, Tales Imbiriba, Pau Closas
Signal Classification Jamming Attack Jamming Detection

January 26, 2023

Cluster Forming of Multiagent Systems in Rolling Horizon Games with Non-uniform Horizons
Yurid Nugraha, Ahmet Cetinkaya, Tomohisa Hayakawa, Hideaki Ishii, Quanyan Zhu
Consensus Group Decision Cluster Structure Multiagent System Optimal Strategy Prediction Horizon Jamming Attack

January 12, 2023

Jamming Attacks on Decentralized Federated Learning in General Multi-Hop Wireless Networks
Yi Shi, Yalin E. Sagduyu, Tugba Erpek
Decentralized Federated Learning Multi Hop Decentralized FL Attack Strategy Jamming Attack Fabric Jamming

July 5, 2022

Linear Jamming Bandits: Sample-Efficient Learning for Non-Coherent Digital Jamming
Charles E. Thornton, R. Michael Buehrer
Multi Armed Bandit Linear Bandit Sample Efficient Physical Layer Anti Jamming Jamming Attack

March 21, 2022

Two methods for Jamming Identification in UAVs Networks using New Synthetic Dataset
Joseanne Viana, Hamed Farkhari, Luis Miguel Campos, Pedro Sebastiao, Francisco Cercas, Luis Bernardo, Rui Dinis
Unmanned Aerial Vehicle NCD Method Synthetic Dataset Various Fast Moving Drone UAV Network Anti Jamming Jamming Attack Jamming Detection

January 13, 2022

Jamming Attacks on Federated Learning in Wireless Networks
Yi Shi, Yalin E. Sagduyu
Wireless Network Uplink Control Jamming Attack Downlink Communication

January 12, 2022

When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges
Qun Wang, Haijian Sun, Rose Qingyang Hu, Arupjyoti Bhuyan
Machine Learning Technical Challenge NCD Method Spectrum Sharing Cognitive Radio Spectrum Sensing Jamming Attack Eavesdropping Attack

Jamming Attack

Papers

Achieving Generalization in Orchestrating GNSS Interference Monitoring Stations Through Pseudo-Labeling

Evaluating ML Robustness in GNSS Interference Classification, Characterization \& Localization

One-Class Classification as GLRT for Jamming Detection in Private 5G Networks

Detecting 5G Narrowband Jammers with CNN, k-nearest Neighbors, and Support Vector Machines

Enhancing O-RAN Security: Evasion Attacks and Robust Defenses for Graph Reinforcement Learning-based Connection Management

Securing the Skies: An IRS-Assisted AoI-Aware Secure Multi-UAV System with Efficient Task Offloading

DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs

Jammer classification with Federated Learning

Cluster Forming of Multiagent Systems in Rolling Horizon Games with Non-uniform Horizons

Jamming Attacks on Decentralized Federated Learning in General Multi-Hop Wireless Networks

Linear Jamming Bandits: Sample-Efficient Learning for Non-Coherent Digital Jamming

Two methods for Jamming Identification in UAVs Networks using New Synthetic Dataset

Jamming Attacks on Federated Learning in Wireless Networks

When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges