The increasing number of Internet of Things (IoT) devices creates a greater need for authentication solutions that protect user privacy and operate on devices with limited resources. The research study presents an IoT authentication system which uses Radio Frequency Identification (RFID) technology together with SHA-256 hashing and a Discrete Wavelet Transform-Discrete Cosine Transform (DWT-DCT) digital watermarking method that runs on a Raspberry Pi edge device which connects to a Django authentication system. The system uses Quantization Index Modulation (QIM) with step Δ = 24.0 to embed the SHA-256 hash of a user's RFID unique identifier as a 256-bit binary payload which targets the LL approximation subband of the image luminance channel, with sevenfold repetition coding and majority-voting error correction as additional elements. The testing process which used 20 USC-SIPI benchmark images achieved a PSNR value of 49.68 dB together with an SSIM value of 0.9974 which indicated exceptional visual imperceptibility. The system maintains operation with NCC values exceeding 0.95 during testing that used six different signal processing attacks, while JPEG compression only causes minor data loss (NCC = 0.99943, BER = 1.93 %). The complete authentication system achieved perfect accuracy in 75 testing sessions, while the total processing time took about 3.0 seconds, which proved that the system can operate in real time on devices with limited processing power. The proposed method outperforms current state-of-the-art methods in protecting visual content while delivering full authentication through RFID technology.
Keywords
IoT AuthenticationDigital WatermarkingDWT-DCTRFIDRaspberry PiEdge ComputingSHA-256Quantization Index Modulation
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