Privacy has become a significant factor of e-Health system in the area of data mining termed as Privacy preserving data mining (PPDM) as it can uncover underlying rules and hide sensitive data for data sanitization. Various algorithms and heuristics have been studied to hide sensitive data using transaction removal. However, they are facing challenges to attain the reasonable side effects. Thus, rain optimization algorithm (ROA) based sensitive data hiding techniques is proposed in this paper. Using this algorithm, suitable transactions to be removed are selected. Besides, in this work, ROA based two frameworks are designed for data sanitization that are simple ROA to remove transaction (sROA2RT) and pre-large ROA to remove transaction (pROA2RT). In this algorithm, fitness is evaluated based on four side effects such as hiding failure, artificial cost, missing cost and dissimilarity of database. The proposed frameworks are evaluated using three e-Health datasets. Compared to previous frameworks, the proposed frameworks attain reasonable side effects.

Medical data sharing can help to enhance diagnostic accuracy where security and privacy protection are critical to the e-Health system. Nowadays, blockchain (BC) has been proposed as a promising solution to achieve the sharing of personal health information (PHI) because of its merit of immutability. However, privacy preserving of the patients and security of PHI sharing are further to be improved. Thus, a secure and reliable medical data sharing (SRMDS) system is presented in this paper. This system includes hybrid cryptography, private BC and Consortium BC (CBC). To enhance the privacy preserving of each patient, their PHI is encrypted using advanced encryption standard (AES) and the AES key is encrypted using adaptive elliptic curve cryptography (AECC). The ciphertexts of PHI and AES key are stored as block to the private BC of the hospital. Besides, keyword of PHI is forwarded to the CBC. The doctor can access the private BC to recover the PHI of a patient by checking the keyword of corresponding PHI. Simulation results illustrate that the proposed SRMDS based e-Health system improves the security and privacy preserving of patient by decreasing encryption time, decryption time and storage overhead.