Vol. 4 Issue 2
Year: 2016
Issue:Jun-Aug
Title:Detection of Anomaly Based Application Layer DDoS Attacks Using Machine Learning Approaches
Author Name:M.S.P.S. Vani Nidhi and K. Munivara Prasad
Synopsis:
DDoS (Distributed Denial of Service) attacks are a major threat to security. These attacks are mainly originated from the network layer or application layer of the compromised systems that are connected to the network. The main intention of these DDoS attacks is to deny or disrupt the services or network bandwidth of the victim or target system. Now-a-days, application layer DDoS attacks are posing a serious threat to the Internet. Differentiating between the legitimate/normal and malicious traffic is a very difficult task. A lot of research work has been done in detecting the attacks using machine learning approaches. In this paper, the authors have proposed the machine learning metrics for detecting the application layer DDoS attacks.
Year: 2016
Issue:Jun-Aug
Title:Detection of Anomaly Based Application Layer DDoS Attacks Using Machine Learning Approaches
Author Name:M.S.P.S. Vani Nidhi and K. Munivara Prasad
Synopsis:
DDoS (Distributed Denial of Service) attacks are a major threat to security. These attacks are mainly originated from the network layer or application layer of the compromised systems that are connected to the network. The main intention of these DDoS attacks is to deny or disrupt the services or network bandwidth of the victim or target system. Now-a-days, application layer DDoS attacks are posing a serious threat to the Internet. Differentiating between the legitimate/normal and malicious traffic is a very difficult task. A lot of research work has been done in detecting the attacks using machine learning approaches. In this paper, the authors have proposed the machine learning metrics for detecting the application layer DDoS attacks.
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