Spectrum-based Malware Detection for RFID Memory Banks in LF, HF, and UHF Bands

Abstract

The use of Radio-Frequency Identification (RFID) technology has become increasingly prevalent in various industries due to its ability to track and manage inventory efficiently. However, there is always a chance of cybersecurity risks like malware attacks, just like with any other technology. To detect malware in low-frequency (LF), high-frequency (HF), and ultra-high-frequency (UHF) RFID tags, a method using spectrum monitoring of both regular and malware data in user memory banks has been proposed. The method involves the use of SQL interjection virus code simulated using MATLAB. The binary equivalent of the signal from the RFID tags is passed through a double-sideband amplitude shift keying (DSB-ASK) modulation system and then analyzed through spectrum analysis as frequency hopping takes place. By monitoring the power of each signal, the difference between the malware and normal signal data can be identified, with the malware causing a decrease in the original signal’s power by approximately 1 dB.