Enhanced ML Framework based on Artificial Neural Network for countermeasures of Data Protection and Network Vulnerabilities Detection in Industrial Internet of Things

Abstract

The Internet of Things (IoT) is rapidly becoming an integral component of the industrial market in areas such as automation and analytics, giving rise to what is termed the Industrial IoTs (IIoTs). The IIoT promises innovative business models in various industrial domains by providing ubiquitous connectivity, efficient data analytics tools. The way an IIoT is designed can become very complex due to its features. The fact that security and privacy are turning out to be very urgent issues. Many models have been released to look into the security challenges of IoT. The studies described, in general, the security issues involved in the IIoTs using ANN based Proposed Model. Included are threats or a determined analysis that highlights specific forms of technology. Even so, studies from recent years fail to compare the security that is demanded by these technologies with the security that is in reality applied. It is unclear if the security issues of IIoT can be properly tackled. The proposed framework covers IIoT security in detail and offers an overview of the defenses used in the industry currently using ANN-based Convolutional Neural Network CNN. The Proposed model outperforms the other renowned RNN, DT and LSTM models and gives significant improvement in results using (CIC APT IIoT) Dataset 2024 with an accuracy of 98.67%, a Recall of 86.1% achieved an F1-score. that measures a model's accuracy by balancing precision and recall with an improvement of 2.3% as compared to RNN, DT and LSTM models. In this article, the Industrial Internet of Things technologies are split into four layers by developing the architecture for defense systems that fulfill the CIA security standards. Identify the weaknesses in today’s countermeasures and point out the main issues that are still unresolved challenges. The proposed framework is the solution that covers all issues within the IIoT ecosystem, Security in IIoT systems should be handled using a bottom-up approach it is necessary to reach a higher level of abstraction.

Keywords: Industrial Internet of Things (IIoT); IoT architecture and networks; security, Machine Learning, Deep Neural Network, CNN, Prediction models