A Novel Framework for DDoS Detectionin Huge Scale Networks, Thanksto QoS Features
Hamed Rezaei, Nima Ghazanfari motlagha, Yaghoub Farjamib, Mohammad, Hossein Yektae

TL;DR
This paper proposes a new hybrid framework leveraging QoS features for effective DDoS detection in large-scale cloud networks, addressing limitations of traditional methods.
Contribution
It introduces a novel hybrid detection protocol tailored for cloud-scale networks, improving sensitivity and efficiency over existing approaches.
Findings
Enhanced detection accuracy in large-scale environments
Reduced false positives compared to traditional methods
Effective identification of DDoS attacks in cloud infrastructures
Abstract
It is not been a long time since the advent of cloud-based technology. However, in this short period of timeseveral advantages and disadvantages have been emerged. This is a problem solving technology with some threats as well. These threats and potential damages are not only limited to the cloud-based technologies, but they have always been against computer network infrastructures. One of these examples is Distributed Denial-of-Service (DDoS) intrusion which is of course one of the most complex and the most dangerous types of attacks. The impact of this type of attack, due to its powerful nature, is much higher on cloud systems since in case of occurrence, the service providers lose their services completely as well as their reputationand loyal customers. This, apparently,can even lead to the collapse of the stock and other destructive consequences. On the other hand, due to the…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Advanced Malware Detection Techniques · Internet Traffic Analysis and Secure E-voting
