Affine Transformation-based Perfectly Undetectable False Data Injection Attacks on Remote Manipulator Kinematic Control with Attack Detector
<|reference_start|>Affine Transformation-based Perfectly Undetectable False Data Injection Attacks on Remote Manipulator Kinematic Control with Attack Detector: This paper demonstrates the viability of perfectly undetectable affine transformation attacks against robotic manipulators where intelligent attackers can inject multiplicative and additive false data while remaining completely hidden from system users. The attacker can implement these communication line attacks by satisfying three Conditions presented in this work. These claims are experimentally validated on a FANUC 6 degree of freedom manipulator by comparing a nominal (non-attacked) trial and a detectable attack case against three perfectly undetectable trajectory attack Scenarios: scaling, reflection, and shearing. The results show similar observed end effector error for the attack Scenarios and the nominal case, indicating that the perfectly undetectable affine transformation attack method keeps the attacker perfectly hidden while enabling them to attack manipulator trajectories.<|reference_end|>
@article{ueda2024affine,
    title={Affine Transformation-based Perfectly Undetectable False Data Injection
  Attacks on Remote Manipulator Kinematic Control with Attack Detector},
    author={Jun Ueda and Jacob Blevins},
    journal={arXiv preprint arXiv:2405.11047},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.11047},
    primaryClass={eess.SY cs.SY}
}