The Internet of Things (IoT) introduces innovative real-time applications that use sensors to collect data that exchange between things to things and things to humans through the network. In this aspect, security and privacy is the primary concern for researchers to protect these systems. This paper proposes a real-time authentication algorithm based on the one-time pad (OTP) principle. The keys are dynamically exchanged, and the data is encrypted via dynamic encryption, depending on random sensors’ data. The key is generated and exchanged dynamically using the dynamic encryption technique, thus enhancing the users’ data privacy and security. Moreover, a lightweight key generation, exchange, and authentication protocol are proposed for data collecting from smart home sensors. The proposed protocol guarantees security and privacy demand, which are the user’s primary concern. The proposed protocol is developed for smart home applications with interfacing requirements, which makes the system real and applicable. The operation principle of the proposed protocol is illustrated sufficiently if there is any desynchronization or emergency.
A heterogeneous cellular network can define as a network that is composed of different cell sizes (macrocell (MeNB), small cell (SeNB), femtocell). Such heterogeneity of network is the backbone of the 5G networks where new applications on mobile devices need extensive computing power consumption and ultra-low latency constraints. Using a heterogeneous network will provide multiple paths in which the users’ data can flow through the network depending on the users’ available resources, remaining energy, etc. we study the heterogeneous network model, which contains MeNB, SeNB and femtocells. Also, we propose a matching subcarrier resource allocation and offloading decision (MSRAOD) algorithm, that depends on recourse allocation optimization. The main optimization goal has been set to minimize the total energy consumption of mobile users’ devices with acceptable latency requirements of the applications. Our proposed algorithm results show that the proposed algorithm enhances the average energy consumption of mobile users in the heterogeneous network.
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