This dataset used in the research paper "JamShield: A Machine Learning Detection System for Over-the-Air Jamming Attacks." The research was conducted by Ioannis Panitsas, Yagmur Yigit, Leandros Tassiulas, Leandros Maglaras, and Berk Canberk from Yale University and Edinburgh Napier University.
The "RF Jamming Dataset for Vehicular Wireless Networks" presents a comprehensive collection of data used in the research paper titled "RF Jamming Classification Using Relative Speed Estimation in Vehicular Wireless Networks." This dataset comprises diverse scenarios of RF jamming attacks and interference in Vehicular Ad-hoc Networks (VANETs), along with corresponding ground truth labels. The dataset is designed to support the evaluation and development of detection algorithms for RF jamming attacks in VANETs.