An Innovative Approach to Solve Healthcare Issues Using Big Data Image Analytics

Abstract

The increasing adoption of transmission of medical images through internet in healthcare has led to several security threats to patient medical information. Permitting quiet data to be in peril may prompt hopeless harm, ethically and truly to the patient. Accordingly, it is important to take measures to forestall illicit access and altering of clinical pictures. This requests reception of security components to guarantee three fundamental security administrations – classification, content-based legitimacy, and trustworthiness of clinical pictures traded in telemedicine applications. Right now, inside created symmetric key cryptographic capacities are utilized. Pictorial model-based perceptual image hash is used to provide content-based authentication for malicious tampering detection and localization. The presentation of the projected algorithm has been evaluated using performance metrics such as PSNR, normalized correlation, entropy, and histogram analysis, and the simulation results show that the security services have been achieved effectively.

An Analysis of Data Processing for Big Data Analytics

“…The issues posed by large datasets, complex, dynamic and scattered data properties are addressed by large data sets algorithms, which focus on algorithm design [2]. The phases of the challenges are as follows: Data fusion methods are used to pre-process HC, fragmented, inconsistent, limited, and multi-source data.…”