Kerberos is a well-known network authentication protocol that allows nodes to communicate over a non-secure network connection. After Kerberos is used to prove the identity of objects in client-server model, it will encrypt all of their communications in following steps to assure privacy and data integrity. In this paper, we modify the initial authentication exchange in Kerberos 5 by using biometric data and asymmetric cryptography. This proposed method creates a new preauthentication protocol in order to make Kerberos 5 more secure. Due to the proposed method, the limitation of passwordbased authentication in Kerberos 5 is solved. It is too difficult for a user to repudiate having accessed to the application. Moreover, the mechanism of user authentication is more convenient. This method is a strong authentication scheme that is against several attacks.
Non-orthogonal multiple access (NOMA) has drawn enormous attention from the research community as a promising technology for future wireless communications with increasing demands of capacity and throughput. Especially, in the light of fifth-generation (5G) communication where multiple internet-of-things (IoT) devices are connected, the application of NOMA to indoor wireless networks has become more interesting to study. In view of this, we investigate the NOMA technique in energy harvesting (EH) half-duplex (HD) decode-and-forward (DF) power-splitting relaying (PSR) networks over indoor scenarios which are characterized by log-normal fading channels. The system performance of such networks is evaluated in terms of outage probability (OP) and total throughput for delay-limited transmission mode whose expressions are derived herein. In general, we can see in details how different system parameters affect such networks thanks to the results from Monte Carlo simulations. For illustrating the accuracy of our analytical results, we plot them along with the theoretical ones for comparison.
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