PBAMA: PARALLEL BEST ATTACK MITIGATION ALGORITHM BASED DDOS ATTACKS DETECTION IN INTERNET OF THINGS

Abstract

Distributed Denial of Service (DDoS) attacks is usually explicit efforts to exhaust the legitimate user bandwidth or disrupt the services. Conventional architecture of IoT is susceptible to DDoS attacks and it offers a prospect to an attacker to gain access to a huge number of compromised IoT systems by using their vulnerabilities. The present work provides the novel Parallel Best Attack Mitigation Algorithm (PBAMA) based DDoS attacks in Internet of Things. The proposed framework detects the different DDoS attacks like flooding of User Datagram Protocol, spoofed SYN packets, ICMPF echoes. The IP address of the detected DDoS attacks was analyzed through the malicious request table (MRT). The MRT will be updated when an attacker approaches the system with new IP address. Additionally, the original IP address of the attacker was traced effectively to secure the IoT system from recurring attacks from the same attacker. The performance of the proposed algorithm was evaluated on the false positive and false negative rates over the CPU, radio transmit, radio listen and LPM. The network hop was also evaluated over different number of nodes. The obtained result showed that the FPR and the FNR was limited to 30% and 5.50 % respectively. The Hop value attained was either 1 or 2 over the different number of nodes.