In this paper, cloud computing security is enhanced by the use of the intrusion detection framework and the neural network. In order to handle access to traffic in a large network and control data and applications in cloud computing, an impressive framework called the Layer Intrusion Detection Framework that can be used on different layers and classes of cloud computing can be used. You can identify the presence of normal traffic among cloud traffic. The artificial neural network data mining framework has also been used to increase accuracy and speed. Layer Intrusion Detection Framework can reduce the amount of traffic that has been analyzed and increase performance to better performance. So far, much research has been done to increase the accuracy of finding malicious traffic, which, given the limitations available, still has trouble finding these malicious traffic. In this research, we first tried to use real-time network traffic monitoring to use the network monitoring module to monitor traffic and then use the seventy extraction features of various traffic and neural networks to solve the problem and the classification was made. In this framework, in addition to the real-time monitoring of existing traffic using network monitoring software, seventeen features have been used, two of which have been used for the first time, which increase the security of cloud computing and prevent the intrusion of distractors.