Privacy- Preservation and Network Security Us...

Privacy- Preservation and Network Security Using and Deep CNN Algorithm

Author Name : M. Nagaraju Naik. , Prof.M. Padmavathamma

DOI: https://doi.org/10.56025/IJARESM.2023.11923444

ABSTRACT With the development of emerging technologies such as big data, IoT and cloud computing, innovative solutions for simpler communication are provided. Besides, the advancements serious issues of threats and attacks to data are manipulated each time. Various intrusion detection methods are evolved in aspects of detecting the common network attacks. Attack detection technologies play a potential role in securing the data and other essentials form an intrusion or an attack. These attacks provide consequences such as heavy data breaches and data loss resulting in complete data unavailability. Many such approaches have been carried out in detecting and in classifying the attack over the networks. But these approaches are associated with several complexities such as lower accuracy rates, high computational complexity. Further challenges are laid in cases of less detection rates of feature space, less recognition to encrypted data and detecting only known attacks. Considering these laybacks, the DL approaches are one of the promising solutions in providing remarkable outcomes in both attack detection and classification. These are viable in producing remarkable outcomes in case of accuracy rates, less complexity, and faster detection rates. With correlation to these advantages, the proposed model considers using the Federated learning-based CNN model in classifying the presence or absence of attack over network.