Abnormal Traffic Monitoring Methods Based on a Cloud Computing Platform









Abstract

Every packet on the internet represents a traffic, and in addition to normal traffic, there are many abnormal traffic, and the abnormal traffic may bring huge security risks to the security and the normal use of the network. Therefore, timely detection and processing of the abnormal network traffic is of great significance for ensuring the network security. At present, all kinds of research foundations for the abnormal network traffic are based on “Flow” which is the main basis for the network data traffic monitoring and the security judgment. The “Flow” is defined as an access request packet from the source access device to the target access device. This one-way propagated data packets can be uniquely identified and determined by the address and the port number of the source device and the target device. Because Hadoop allows the users to perform efficient, reliable, and scalable distributed program development without any foundation, therefore, this paper proposes to monitor the abnormal traffic of the cloud computing platform based on Hadoop, which can also solve many network data storage and anomaly monitoring problems.


Modules


Algorithms


Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL