providing a useful system to detect the intrusion detection system with the ability to attack in order to increase accuracy and improve security in cloud computing

Intrusion detection system (ids) is an important component to maintain network security. therefore, all applications that use networks to serve their customers can use intrusion detection systems. also, since the cloud platform is rapidly developing and becoming an integral part of daily life, building an ids in the cloud is very effective. with the launch of the intrusion detection system, if a user s behavior is not the same as his previous impression, a warning about the possibility of an intrusion will be announced by the system administrator (one of the ids departments). it is also possible to prevent the erasure of the records stored by the intrusion detection system and the change of information by the intruder. intrusion detection systems, which are reactive tools, are widely used as a complementary defense layer alongside these methods. an intrusion detection system is a hardware or software system that examines incoming traffic to a network or host in order to detect attacks and unusual behaviors. the purpose of this paper is to provide a method based on intrusion detection systems and its different types of architecture with the aim of increasing the accuracy of intrusion detection in cloud computing. this paper will use a nkdd99 dataset for classification training and testing. it then shows that the resulting results can perform better than other tasks that have been made with available features so far.