Image processing (IP) technology has emerged on the basis of AI, digital imaging technology, and multimedia technology, and people began to use computers to process images to improve image quality and improve human vi...
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With the increased specifications of healthcare services, diagnosis become very common in most of the healthcare sector to provide better treatment for patients. Here, the person's medical information can be track...
详细信息
With the increased specifications of healthcare services, diagnosis become very common in most of the healthcare sector to provide better treatment for patients. Here, the person's medical information can be tracked with the help of an Electronic Health Record (EHR). The EHR system maintains the digital medical records of medical organizations. Enterprise-wide data systems, along with other networking activities, are used to exchange medical documents in the current environment where the patient seeks rapid access to their medical records. Moreover, the EHR system faces many problems regarding integrity, management and security. Still, there are some concerns regarding the security and privacy of patient medical records. However, it suffers from managing the large volume of electronically generated healthcare data. Thus, this work adapts blockchain technology, which effectively stores healthcare data. Therefore, decentralized technology was just recently introduced in order to offer an innovative viewpoint on data security and system effectiveness. In this work, a blockchain-related system is developed to secure patients' health data with high verifiability. A total of two mechanisms are carried out in the developed model to encrypt the privacy of the health data that is Data Sanitization and Polynomial Interpolation-based Cryptography (DSPIC). In the data sanitization mechanism, the optimal key is generated through the Modernized Position-based Coot and Penguins search optimization algorithm (MP-CPeSOA). The polynomial interpolation method is carried out through the estimation of values between two data points to handle the heterogeneity. The objective function is considered for securing the patient's health data with Euclidian distance, hiding ratio, preservation ratio and correlation among the original data and the restored data. In this developed model, the generated key is digitally signed to provide high security for the patient's health data. At last, the eff
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