A Hybrid Cryptography and LogiXGBoost Model for Intelligent and Privacy Protection in Wireless Body Sensor Networks (WBSNS)

Abstract

An increasing number of healthcare applications are making use of wireless body sensor networks (WBSNs). WBSN technology provides a framework that allows for remote physiological monitoring of patients without the use of wired connections in the house. Furthermore, these systems provide real-time data transfer for medical personnel, allowing them to make timely decisions regarding patient care. Despite this, worries remain about patient data being compromised. This research presents a strategy for protecting patient-provider communications by making use of WBSNs. To solve the problem of how to securely store sensitive information on blockchains, a hybrid cryptographic architecture is proposed. The strengths of both public key and symmetric key cryptography are leveraged in my approach. In order to achieve this goal, I have developed a new algorithm by fusing the AES, RSA, and Blowfish algorithms. My experiments have shown that the proposed solution can keep private data safe without affecting its scalability. Using Logi-XGB as a prediction model for attacks, the proposed approach can successfully thwart 99.7 percent of them.