System for DDoS attack mitigation by discovering the attack vectors through statistical traffic analysis

2020 ◽  
Vol 13 (3/4) ◽  
pp. 309
Author(s):  
Mircho Jordanov Mirchev ◽  
Seferin Todorov Mirtchev
Author(s):  
Sumit Kumar Yadav ◽  
Kavita Sharma ◽  
Arushi Arora

In this article, the authors propose a DDoS mitigation system through access list-based configurations, which are deployed at the ISP (Internet Service Provider's) edge routers to prohibit DDoS attacks over ISPs' networks traffic. The effectiveness of the proposed system relies heavily on the willingness of ISPs in implementing the system. Once each ISP implements the system, most attacks can easily be stopped close to their point of origin. The main challenge is to implement such a system with the fixed amount of memory and available processing power with routers. A coordinated effort by participating ISPs filters out attacks close to their source, reducing the load on other routers. The suspicious traffic is first filtered out based on their source IP address. The authors also implemented the WRED algorithm for their case and conduct GNS3 experiments in a simulated environment.


2019 ◽  
Vol 9 (21) ◽  
pp. 4633 ◽  
Author(s):  
Jian Zhang ◽  
Qidi Liang ◽  
Rui Jiang ◽  
Xi Li

In recent years, distributed denial of service (DDoS) attacks have increasingly shown the trend of multiattack vector composites, which has significantly improved the concealment and success rate of DDoS attacks. Therefore, improving the ubiquitous detection capability of DDoS attacks and accurately and quickly identifying DDoS attack traffic play an important role in later attack mitigation. This paper proposes a method to efficiently detect and identify multivector DDoS attacks. The detection algorithm is applicable to known and unknown DDoS attacks.


2016 ◽  
Vol 43 (5) ◽  
pp. 596-605
Author(s):  
Hyuk Joon Kim ◽  
Dong Hwan Lee ◽  
Dong Hwa Kim ◽  
Myung Kil Ahn ◽  
Yong Hyun Kim

Sign in / Sign up

Export Citation Format

Share Document