Wireless networks (WNs) are those that link devices wirelessly, without the need for any form of wire. They do this by employing radio waves. The WN is a significant motivator, drawing in over a million new users every day. Seventy per cent of the organisations are considering migrating to WN due to its several enticing features and pay-as-you-go approach. Almost everyone has at least one internet-connected device in today’s connected society. As the quantity of these devices increases, it is important to put in place a security plan to reduce the likelihood of exploitation. Malicious organisations may utilise internet-connected gadgets to gather personal data, steal identities, jeopardise financial information, and secretly observe or listen to users. This kind of activity can be avoided by configuring and using your devices with a few precautions. Hackers frequently utilise network layer attacks to access remote computers at home or on business networks. After gaining access, they might continue navigating the levels to get further data or infect your machine with malicious software. A multi-level detection approach that fit in the Simple Network Management Protocol (SNMP) with Recurrent Neural Network incoming request analysis techniques is developed in order to fulfil the goals of early detection and cost-efficiency. Based on the attack prediction, the system performance is examined, and performance metrics including throughput, packet delivery ratio, end-to-end delay, energy usage, and packet loss are calculated.