Investigation of combined intrusion ate detection systems with network security approach Case study of RPL protocols

Investigating, recognizing, and preventing malicious functions to intrusion systems and designing intrusion detection systems for network security is one of the most important and practical issues in the field of computer and network sciences. In this study, which is organized as a reviewed and library study, the mentioned systems were studied in several areas, including the use of neural networks, genetic algorithms, and specifically the case study of RPL protocols. The results of this study showed that the neural network is very efficient in investigating and detecting intrusion. If this technique is combined with other machine learning methods, the system efficiency will reach over ۹۰%. Moreover, in this survey of RPL protocols and their role in network security and intrusion detection, it is identified that this group of protocols with proper planning and regulation at the project level with high-security capabilities will have many applications in intrusion detection and awareness.

Keywords:

Network Security , intrusion Detection , Neural Network , RPL Protocol , Cyber Security