Secure Cloud-Based Storage Framework for EEG Files in Blockchain E-health Systems Using Compression, Digital Signatures, and Chaotic Encryption
International journal of intelligent engineering and systems · 2025
The increasing adoption of blockchain technology in healthcare presents challenges in storing massive amounts of medical data, including electroencephalogram (EEG) files, because of the inherent storage limits of blockchain technology.This study presents a method for securely storing EEG medical data on the cloud, such as offchain storage, that combines encryption and compression approaches.This study proposes two compression approaches.The first method uses a packet biorthogonal tap 9/7 wavelet transform, uniform quantization, mapping to positive values, and an adaptive bit encoder.The second approach uses uniform quantization, delta modulation, mapping to positive values, and the Huffman encoder.Both strategies effectively reduce file size while maintaining data integrity; however, the second method is more efficient for large EEG datasets.This study uses a chaotic system with three types of random encryption generators.The proposed chaotic system uses Logistic, Tent, and Sine chaotic systems to generate encryption keys to encrypt data.This approach achieves high unpredictability and robustness against cryptographic attacks by achieving high randomness.To ensure the integrity of the EEG file, the SHA-256 hash algorithm is employed, providing robust data verification methods.The proposed framework provides a secure, efficient, and scalable approach to storing and managing sensitive medical data in cloud environments as off-chain storage.It employs blockchain technology to ensure integrity verification and access control.The proposed framework is evaluated using the publicly available EEG dataset from the CHB-MIT database.The Huffman-based method preserved data quality and produced an excellent compression ratio (CR) of 12.41, mean square error (MSE) of 0.0008, and a percentage root mean square distortion (PRD) of 0.031.Adaptive shift-based compression functioned well, even with lower compression ratios (7.92-9.26).Entropy revealed that 8-bit-per-byte encryption retained data unpredictability.All NIST statistical tests passed, proving encryption keys sturdy.