RFID-ExSim: A multi-scenario experimental dataset for collision timing, tag cloning, replay injection, and flooding...

RFID-ExSim is an experimental dataset designed for studying passive RFID systems under normal operating conditions and in adversarial attack scenarios. The dataset was collected in a controlled laboratory environment using two synchronized ESP32-based MFRC522 RFID readers interacting with twelve passive RFID tags. In total, >400,000 raw RFID read events were recorded and stored in a structured JSONL format with millisecond-level timestamp resolution. The dataset is structured around five well-defined acquisition scenarios: (i) basic single-reader operation, (ii) dual-reader collision interference, (iii) tag cloning at the UID level, (iv) replay and software injection attacks, and (v) high-throughput stress sessions simulating denial-of-service conditions. Each recorded event includes the reader ID, local tag ID, hashed UID, raw payload, scenario label, and physical acquisition parameters, including tag-to-reader distance and angular orientation. RFID-ExSim offers a reproducible and fully documented benchmark for analyzing RFID reliability, collision dynamics, identity cloning, replay behavior, and system robustness under high load conditions. The dataset is designed to support research in the areas of RFID security, physical layer analysis, anomaly detection, intrusion detection systems, and machine learning-based RFID authentication.