Biblio

The Internet of Things (IoT) is a novel paradigm that enables the development of a slew of Services for the future of technology advancements. When it comes to IoT applications, the cyber and physical worlds can be seamlessly integrated, but they are essentially limitless. However, despite the great efforts of standardization bodies, coalitions, companies, researchers, and others, there are still a slew of issues to overcome in order to fully realize the IoT's promise. These concerns should be examined from a variety of perspectives, including enabling technology, applications, business models, and social and environmental consequences. The focus of this paper is on open concerns and challenges from a technological standpoint. We will study the differences in technical such Sigfox, NB-IoT, LoRa, and 6LowPAN, and discuss their advantages and disadvantage for each technology compared with other technologies. Demonstrate that each technology has a position in the internet of things market. Each technology has different advantages and disadvantages it depends on the quality of services, latency, and battery life as a mention. The first will be analysis IoT technologies. SigFox technology offers a long-range, low-power, low-throughput communications network that is remarkably resistant to environmental interference, enabling information to be used efficiently in a wide variety of applications. We analyze how NB-IoT technology will benefit higher-value-added services markets for IoT devices that are willing to pay for exceptionally low latency and high service quality. The LoRa technology will be used as a low-cost device, as it has a very long-range (high coverage).

Smart city is gaining a significant attention all around the world. Narrowband technologies would have strong impact on achieving the smart city promises to its citizens with its powerful and efficient spectrum. The expected diversity of applications, different data structures and high volume of connecting devices for smart cities increase the persistent need to apply narrowband technologies. However, narrowband technologies have recognized limitations regarding security which make them an attractive target to cyber-attacks. In this paper, a novel platform architecture to secure smart city against cyber attackers is presented. The framework is providing a threat deep learning-based model to detect attackers based on users data behavior. The proposed architecture could be considered as an attempt toward developing a universal model to identify and block Denial of Service (DoS) attackers in a real time for smart city applications.