APPROACH OF DETECTION AND TRACING TECHNIQUE OF DDOS ATTACKS FROM FLASH EVENT USING FCC
Dipali Pawar · Journal of Emerging Technologies and Innovative Research · 2019
Internet is a wide network used to combine different sectors, education, business, banks, government, entertainment, optical network technologies. It carries number of information services and resources which exchange large amount of traffic over the Internet every day. The growing needs of such applications to make it more prone towards malicious users who are trying to invade. Protection against different software attacks is one of the key challenges to maintain data integrity and privacy. Among them, Distributed Denial of Service (DDoS) and Flash Crowd attacks are the two major events. Web services require security and stability and from these two concerns there are some methods that can differentiate DDoS attack from flash crowd and trace the sources of the attack in large amount of traffic in network. But it is difficult to detect the exact sources of DDoS attacks in traffic of network when flash crowd event is also present. Due to the alikeness of these two irregularities, attacker can easily mimic the harmful flow into legitimate network traffic patterns and The existing defense mechanism fail to detect real sources of attack on time. After analyzing the characteristics of DDoS attacks and the existing Algorithms to detect DDoS attacks, this paper proposes a novel detecting and tracing algorithm for DDoS attacks based on flow correlation coefficient. In this paper, flow correlation coefficient, a theoretic parameter, is used to differentiate DDoS attack from flash Crowd and trace the sources of the DDoS attack. The proposed approach focuses majorly on the efficiency and scalablity features with minimum overhead in terms of resources and time, removal of traffic pattern dependency, increase in detection rate between DDoS and flash crowd and also trace the sources of DDoS attack.