Extensive Analysis Of Internet Of Things Based Health Care Surveillance System Using Rfid Assisted Lightweight Cryptographic Methodology
Main Article Content
Internet of Things (IoT) plays a vital role in Smart Applications such as Smart City Maintenance and Control, Health Care, Transportation, Defense Operations and so on. Compare to all of these mentioned applications Health care is the most significant and necessary application to take care with as well as the concern regarding patients and their belongings need to be monitor the patient health related summary from the remote end without any hurdle. This is possible with the help of Internet of Things, in which it enables the bridge between client end and the server end to track the health records clearly without any delay as well as providing the proper security mechanisms to the health records preserved into the server. In this paper, a new Radio Frequency Identification (RFID) enabled Lightweight Cryptographic Method (RFIDLCM) is introduced to provide proper security mechanisms to the health records preserved into the server end. In addition, it must be kept secure against abuse as well as authentication when storing the patient's record as other devices can easily be monitored. It is quite difficult to encrypt voluminous data encryption protocols because of restricted IoT devices. For this reason, Homomorphic encryption models are recommended and in this paper, a new block cipher technique has been proposed for the safe transmission of health information from such Internet of Things devices. The proposed approach is activated with the help of Smart Helath Monitoring Device interconnected with several health related sensors such as RFID Reader, ECG Sensor, Pressure Level Estimation Sensor and Temperature Sensor. All these sensors are integrated together to provide a proper solution to the health care surveillance scheme in an intelligent manner. The resulting emulations of this paper proves the efficiency of the proposed approach in clear manner with graphical representations. The proposed approach of RFIDLCM proves its efficiency with respect to the improvements in prediction accuracy levels, security levels, time concerns and the data transportation efficiency.