Simulating and Modeling a Secure Content Caching System in IoT Networks Using Deep Learning Tools

Ahmed Adnan Hadi

Authors

Ahmed Adnan Hadi Open Educational College, Al-Qadisiyah Center, Iraq

Keywords:

Secure content caching system, IoT networks, Deep learning tools, Simulating, Modeling, Content caching, Security in IoT

Abstract

By keeping frequently accessed content closer to the end users, content caching is essential to maximizing the performance of Internet of Things (IoT) networks. Nonetheless, because the data being transferred is sensitive, security in IoT situations is critical. The goal of this project is to use deep learning methods, namely decision trees and neural networks, to simulate and build a secure content caching system in Internet of Things networks.The suggested method makes use of decision trees to identify the best material to cache according to a number of variables, including network conditions, security needs, and content popularity. Because decision trees recursively divide data according to qualities, they are useful for managing complex scenarios and allow for precise caching decisions.Moreover, neural networks are used to improve the caching system's security feature. The system is able to make security-aware decisions on content caching by using a neural network model that has been trained on a large dataset that includes different network settings and content attributes. By identifying patterns and connections between various input parameters, the neural network model is able to recognize possible security threats and modify the caching approach accordingly.The caching hit ratio, latency reduction, and security enhancement can be used to assess the efficacy and performance of the secure content caching system through modeling and simulation. The study's findings will shed important light on the possible advantages of utilizing deep learning techniques to secure content caching systems for Internet of Things networks.The overarching goal of this research is to improve the user experience and protect sensitive IoT data by aiding in the development of dependable and secure content caching technologies that increase the effectiveness and security of IoT networks.

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