"False Data Injection Attack Detection Dataset for Solar Insecticidal Lamp Internet of Things Node"

"Solar insecticidal lamps (SILs) are a type of green pest control device that attracts pests through lure lamps and kills them using high-voltage metal mesh. When combined with Internet of Things technology, the SIL system can collect various data and implement insecticidal counting functionality, facilitating pest monitoring. However, the reliability of data sources is a prerequisite for achieving accurate insecticidal counting. The SIL system may face a false data injection attack (FDIA), where an attacker can simulate the process of killing pests by using a conductive object to touch the metal mesh of the SIL, resulting in counting errors in the system. To tackle this challenge, we construct a specialized dataset for FDIA detection. The dataset consists of two parts: sound data and numerical data, specifically designed for SIL devices equipped with and without microphones."