International Journal of Science, Engineering and TechnologyAuthors: Research Scholar Sunil Chandolu, Professor Dr.Pankaj Khairnar
Abstract: The fast growth of distributed networks like cloud computing and IoT has further increased cyber threat complexity itself. Traditional intrusion detection systems basically use centralized data processing, which creates the same problems with data privacy, scalability, and efficiency. This paper actually shows how to build a smart security system that works across many computers without sharing data. The system definitely uses connected deep learning models to catch network attacks. We are seeing that the suggested system helps many network points to work together for training models without sharing original data only, so privacy is kept safe. We are seeing that deep learning methods help to make detection more accurate by finding complex patterns in network traffic only. The system actually combines shared learning with privacy protection and definitely uses smart communication methods. Our tests actually show that the new model works very well and definitely beats the old central methods while keeping data
