Artificial Intelligence based Network Security System to Predict the Possible Threats in Healthcare Data

The world is filled with exciting technologies and ideas; scientists build machines to avoid human intervention in completing work. It is highly challenging to complete the task without the Artificial Intelligence (AI) Technology intervention. With the technological development, certain processes or consultations are performed with the aid of doctors available around the world. In this scenario, it could be noticed that health care is one of the world's expected domains that require the most incredible attention in data security while performing data transfer. Nodes in the network are considered based on the weakest link to overcome the cyber attacker's issues. Besides building the software for data storage, a better mechanism has to be incorporated to provide security to the stored data. This process is a delicate task for every network engineer. This paper will explain such concepts related to health prediction and health care by building the most robust network security systems. Finally, the discussion would cross over human-looping systems, which act as one of the common problems that are affected mentally for a person. The proposed optimized neural network model is compared with the existing data summarization method. From the results it is observed that the proposed model achieves an accuracy of 98.89% which is 4.76% higher than the existing model.