DDoS Attack Detection and Prevention with Local Monitoring Attack Detection (Lm-Ad) Scheme Under SDN Context in Cloud Computing

Network monitoring and detecting attacks are complex in random networks. The varied packet sizes used make reliable and secure communication more challenging. We propose a methodology called Local MonitoringBased Attack Detection (LM-AD) to address this. LM-AD implements two monitor serves, such as source side and destination side local monitors, for collecting and storing the network performance. These monitor servers are built with high bandwidth and storage capabilities. The proposed approach efficiently improves the ability of SDN and cloud storage to achieve prominent data communications. The primary goal of the proposed LM-AD is to attain maximum attack detection rate, packet delivery ratio (PDR), system efficiency and minimum packet loss ratio. The proposed LM-AD utilizes network behaviors and analyzes routing tables to recognize misbehaved nodes and attacks. The experimental work shows that the LM-AD is successful in detecting the attacks. The proposed mechanism focuses on monitoring network performance, ensuring reliable network communication and detecting attacks in dynamic environments. In the future, LM-AD research can be further improved to include huge and practical applications in real-world networks.