False Data Injection Attack

False data injection attacks (FDIAs) are sophisticated cyberattacks that manipulate sensor readings in various cyber-physical systems, aiming to disrupt operations without detection. Current research focuses on developing robust detection methods using machine learning models like LSTM, GNNs, and deep reinforcement learning, often incorporating spatiotemporal analysis to capture the dynamics of the attacked systems. This research is crucial for securing critical infrastructure like power grids and robotic systems, as FDIAs can compromise stability, safety, and reliability, necessitating the development of effective detection and mitigation strategies. The overarching goal is to create resilient systems capable of identifying and neutralizing these attacks.

Papers

November 15, 2024

Continual Adversarial Reinforcement Learning (CARL) of False Data Injection detection: forgetting and explainability
Pooja Aslami, Kejun Chen, Timothy M. Hansen, Malik Hassanaly
High Explainability Anti Forgetting Adversarial Reinforcement Learning False Data Injection Attack Injection Attack

November 2, 2024

False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
Md Raihan Uddin, Ratun Rahman, Dinh C. Nguyen
Network Programming Smart Meter False Data Injection Attack Power System Measurement Data Injection Attack

September 19, 2024

Perfectly Undetectable False Data Injection Attacks on Encrypted Bilateral Teleoperation System based on Dynamic Symmetry and Malleability
Hyukbin Kwon, Hiroaki Kawase, Heriberto Andres Nieves-Vazquez, Kiminaro Kogiso, Jun Ueda
Robot Teleoperation Teleoperation Mode Bilateral Teleoperation False Data Injection Attack

September 6, 2024

Detection of False Data Injection Attacks (FDIA) on Power Dynamical Systems With a State Prediction Method
Abhijeet Sahu, Truc Nguyen, Kejun Chen, Xiangyu Zhang, Malik Hassanaly
Data Detection Dynamical System Dynamic Prediction State Prediction False Data Injection Attack Data Injection Attack

August 30, 2024

Discovery of False Data Injection Schemes on Frequency Controllers with Reinforcement Learning
Romesh Prasad, Malik Hassanaly, Xiangyu Zhang, Abhijeet Sahu
Reinforcement Learning Adversarial Attack Scientific Discovery Power Grid False Data Injection Attack Frequency Control

August 19, 2024

Perfectly Undetectable Reflection and Scaling False Data Injection Attacks via Affine Transformation on Mobile Robot Trajectory Tracking Control
Jun Ueda, Hyukbin Kwon
Cyber Physical System Malicious Agent Affine Transformation Specular Reflection Trajectory Tracking Control False Data Injection Attack Resilient Control

July 12, 2024

MIXED-SENSE: A Mixed Reality Sensor Emulation Framework for Test and Evaluation of UAVs Against False Data Injection Attacks
Kartik A. Pant, Li-Yu Lin, Jaehyeok Kim, Worawis Sribunma, James M. Goppert, Inseok Hwang
Unmanned Aerial Vehicle Level Test Mixed Speech False Data Injection Attack

December 7, 2023

Improved Efficient Two-Stage Denoising Diffusion Power System Measurement Recovery Against False Data Injection Attacks and Data Losses
Jianhua Pei, Jingyu Wang, Dongyuan Shi, Ping Wang
Diffusion Model Power System False Data Injection Attack Power System Measurement Signal Imputation Data Loss

December 4, 2023

Mitigating Data Injection Attacks on Federated Learning
Or Shalom, Amir Leshem, Waheed U. Bajwa
Federated Learning Safe Agent False Data Injection Attack Injection Attack

September 21, 2023

Extracting Physical Causality from Measurements to Detect and Localize False Data Injection Attacks
Shengyang Wu, Jingyu Wang, Dongyuan Shi
Cyber Physical Internal Measurement Actual Causality False Data Injection Attack Data Injection Attack

June 17, 2023

Federated Learning Based Distributed Localization of False Data Injection Attacks on Smart Grids
Cihat Keçeci, Katherine R. Davis, Erchin Serpedin
Cyber Physical System Smart Grid Global Localization False Data Injection Attack Data Injection Attack

January 28, 2023

Analyzing Robustness of the Deep Reinforcement Learning Algorithm in Ramp Metering Applications Considering False Data Injection Attack and Defense
Diyi Liu, Lanmin Liu, Lee D Han
Deep Reinforcement Learning Native Robustness Deep Q Learning False Data Injection Attack Ramp Metering

October 13, 2022

A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems
Ehsan Hallaji, Roozbeh Razavi-Far, Meng Wang, Mehrdad Saif, Bruce Fardanesh
Data Driven Real Time State Estimation Cyber Physical Stream Learning False Data Injection Attack Attack Classification

July 15, 2022

PowerFDNet: Deep Learning-Based Stealthy False Data Injection Attack Detection for AC-model Transmission Systems
Xuefei Yin, Yanming Zhu, Yi Xie, Jiankun Hu
Smart Grid False Data Injection Attack Power Transmission

November 28, 2021

False Data Injection Threats in Active Distribution Systems: A Comprehensive Survey
Muhammad Akbar Husnoo, Adnan Anwar, Nasser Hosseinzadeh, Shama Naz Islam, Abdun Naser Mahmood, Robin Doss
Comprehensive Survey Smart Grid Cyber Physical False Data Injection Attack Active Distribution Data Injection Attack

False Data Injection Attack

Papers

Continual Adversarial Reinforcement Learning (CARL) of False Data Injection detection: forgetting and explainability

False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning

Perfectly Undetectable False Data Injection Attacks on Encrypted Bilateral Teleoperation System based on Dynamic Symmetry and Malleability

Detection of False Data Injection Attacks (FDIA) on Power Dynamical Systems With a State Prediction Method

Discovery of False Data Injection Schemes on Frequency Controllers with Reinforcement Learning

Perfectly Undetectable Reflection and Scaling False Data Injection Attacks via Affine Transformation on Mobile Robot Trajectory Tracking Control

MIXED-SENSE: A Mixed Reality Sensor Emulation Framework for Test and Evaluation of UAVs Against False Data Injection Attacks

Improved Efficient Two-Stage Denoising Diffusion Power System Measurement Recovery Against False Data Injection Attacks and Data Losses

Mitigating Data Injection Attacks on Federated Learning

Extracting Physical Causality from Measurements to Detect and Localize False Data Injection Attacks

Federated Learning Based Distributed Localization of False Data Injection Attacks on Smart Grids

Analyzing Robustness of the Deep Reinforcement Learning Algorithm in Ramp Metering Applications Considering False Data Injection Attack and Defense

A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems

PowerFDNet: Deep Learning-Based Stealthy False Data Injection Attack Detection for AC-model Transmission Systems

False Data Injection Threats in Active Distribution Systems: A Comprehensive Survey