2024/09/17 by Kang, Denglin, Youqian Zhang, Zhang, Youqian +4
Biochemistry, Genetics and Molecular Biology · Computer Science · #B.4.2 #B.4.5 #Bacillus and Francisella bacterial research #Computer Vision and Pattern Recognition (cs.CV) #Cryptographic Implementations and Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #I.4.3 #I.4.4 #Wireless Signal Modulation Classification
paper · pdf · doi:10.48550/arxiv.2409.10922
openalex publication_date 2024/09/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Cameras are integral components of many critical intelligent systems. However, a growing threat, known as Electromagnetic Signal Injection Attacks (ESIA), poses a significant risk to these systems, where ESIA enables attackers to remotely manipulate images captured by cameras, potentially leading to malicious actions and catastrophic consequences. Despite the severity of this threat, the underlying reasons for ESIA's effectiveness remain poorly understood, and effective countermeasures are lacking. This paper aims to address these gaps by investigating ESIA from two distinct aspects: pixel loss and color strips. By analyzing these aspects separately on image classification tasks, we gain a deeper understanding of how ESIA can compromise intelligent systems. Additionally, we explore a lightweight solution to mitigate the effects of ESIA while acknowledging its limitations. Our findings provide valuable insights for future research and development in the field of camera security and intelligent systems.