Published Paper Details:

Advances made in the wearable and biosensor has attracted the applicability and usability of the healthcare applications. The biosensors collect the human physiological data from a remote area using wireless communication medium. Different form of security implications have to be exhibited in Edge Computing Networks. This paper researches on enhancing the network layer and application layer of the Edge Computing Networks in healthcare environment. The objective of the each phase is to enhance the data accuracy of the collected data with minimized delay. In the first phase, we have constructed attack model for Sybil, Sinkhole and Wormhole attacks and detected those attacks under different constraints. Secondly, an efficient packet transmission model which helps to transmit the sensed data based on their emergency using Weighted Product Model (WPM). After devising network layer, a lightweight security scheme, an improved Elliptic Curve Cryptography (ECC) that permits the data access for the authorized users. Experimental analysis is carried out for each phase under pre-defined simulation parameters which explores better results. The framed attack model detects the three eminent attacks in terms of False Positive Rate (FPR) and False Negative Rate (FNR) which helps the Data Controller for message transmission process. Likewise, we have also achieved 97% Packet Delivery Ratio with 0.8ms Packet Dropping Ratio for better packet transmission model than the existing TOPSIS model.