An efficient medical data encryption scheme using selective shuffling and inter-intra pixel diffusion IoT-enabled secure E-healthcare framework.

Security in e-healthcare applications such as Telemedicine is crucial in safeguarding patients' sensitive data during transmission. The proposed system measures the patient's health parameters, such as body temperature and pulse rate, using LM35 and pulse sensors, respectively. The sensor data and the patient's medical image are encrypted in the Raspberry Pi 3 B + processor using Python's proposed text and medical image encryption scheme. The encrypted data is transmitted via the Thing Speak cloud and received by another Raspberry Pi at the receiver to decrypt the cipher data. The flask webserver can view the decrypted data by the doctor at the other end. This IoT implementation of secure Electronic Health Record (EHR) transmission employs text and medical image encryption schemes using a Combined Chaotic System (CCS). The CCS generates the chaotic key sequences to shuffle the medical image row-wise and column-wise. Then, selective shuffling between the cut-off points breaks the statistical relationship between the neighbouring pixels. Finally, the intra and inter-pixel diffusion is carried out using bit permutation and bit-wise XOR operation to create a highly random cipher image. The initial seed for inter-pixel diffusion is obtained from the hash of intra-pixel diffused images to resist chosen plain text and cipher text attacks. The efficiency of the developed medical image encryption algorithm is tested against various attack analyses. The results and the security analyses validate the effectiveness of the proposed scheme.