India’s use of the Internet is expanding quickly. Every coin has two sides. Cybercrime, or criminal online activity, is one of the drawbacks of the Internet. Illegal imports or malicious software are crimes that include utilizing a computer and the internet to steal someone’s identity. Cybercrime is criminal action committed online and via computers. “Cybersecurity” refers to the systems and practices designed to protect computers, networks, and data from unauthorized access and online attacks by cybercriminals. Cybersecurity, however, is necessary for network, data, and application security. This research recommends a precise protected framework for detecting and preventing data integrity threats in wireless sensor networks. A clever cyberattack detection strategy based on predictive learning methods to offer the best forecast is required for this. It also applies the combinatorial concept of prediction intervals to overcome the instability issues caused by neural networks. The proposed model is presented to differentiate malicious attacks of varying degrees of intensity during a secured operation, with improve accuracy rate leading to high performance comparing to existing works in this domain. The machine learning model is the foundation for the suggested cyberattack detection technique.