Securing IoT Networks: A Post-Quantum Blockchain and Deep Learning Approach for Enhanced Cyber Defense

The high rate of growth in the number of IoT devices has resulted in more than a billion interconnected things exchanging data, creating new security threats.Traditional security, when facing advanced cyber-attacks, especially in the era of quantum computing, is getting weaker.This paper explains novel way methods, a combination of post-quantum blockchain technology and deep learning to improve security on IoT networks.With the correct preparations in place, such as implementing post-quantum cryptography, which is secure against quantum attacks, your data remains confidential, and integrity-related issues are protected.It is a distributed framework that blockchain technology has been using to secure IoT communications since tamper resistance and transparency in the environment are key.At the same time, deep learning algorithms capable of processing large amounts of data allow for more sophisticated ways to detect and respond to threats quicker than before.In this article, we will explain how a mixture of these technologies can be applied in the framework that allows building such robust cyber defense systems for IoT networks.Post-quantum blockchain is integrated for secure communication channels and immutable transaction records, ongoing traffic monitoring using deep learning models that are able to dynamically update threat detection signatures instantly.We perform an in-depth system architecture analysis, illustrating blockchain's decentralized security and deep learning predictive analytics.The possibility of a practical integration received 95 percent success.The paper evaluates PQCrypto, Blockchain, and Deep Learning technically to get quantized accuracy, efficiency, and the possibility of a practical integration.It received 95% percent success.