A Spectrum Injection-Based Approach for Malware Prevention in UHF RFID Systems

Abstract

Radio frequency identification (RFID) is a technology that uses electromagnetic waves (EMW) to send, process, and store data by using a built-in integrated circuit and antenna. However, its susceptibility to malware attacks poses a threat to data privacy and system performance. Thus, there is a need to develop techniques to protect RFID systems from malware injection and improve efficiency through spectrum optimization. An approach for improving the efficiency and data privacy of RFID systems operating in the ultra-high frequency (UHF) band is proposed for multiple data rates of 160, 256, 320, and 640 kbps. Firstly, a method is introduced for reconstructing regular data in a malware-free RFID system with optimized spectrum usage, which reaches up to 50% of the total spectrum and improves efficiency. Secondly, a spectrum injection-based approach (SIBA) is proposed by incorporating a bandpass filtering (BPF) technique to inject the missing spectrum of regular data with a portion of the malware-injected data spectrum. This approach results in faster and more precise data reconstruction with higher accuracy and overcomes the malware. A noise reduction technique based on BPF is also proposed to reduce the noise effects and enhance the accuracy of data reconstruction at different signal-to-noise ratio (SNR) levels. This technique is evaluated through extensive analysis with various metrics such as reconstruction accuracy, robustness to noise, bandwidth utilization factor (BUF), and computational complexity, making it suitable for resource-constrained environmental settings. These approaches address the challenges of malware injection and spectrum optimization, resulting in more efficient and secure RFID systems.

Keywords

• Baseband signal reconstruction
• BPF
• BUF
• data privacy
• RFID
• EMW