Very Short Intermient Distributed Denial of Service (VSI-DDoS) attack is a new form of DDoS attacks with potential to bypass many of the security measures used today and still severely damage the quality of service of web applications in cloud systems. The attacks consists of short bursts of legitimate packets which exploits vulnerabilities in the targeted system. With the growing popularity of using containers instead of Virtual Machines in clouds, this project presents an approach for detecting these attacks in a container based cloud system. The approach uses signal processing in the form of Discrete Wavelet Transform (DWT) and recurrent neural networks (RNN) called Long Short Term Memory (LSTM) to detect attacks. Several experiments have been carried out to evaluate the performance of the proposed approach in a controlled testbed environment and it is shown to perform well with competing approaches.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-165181 |
| Date | January 2019 |
| Creators | Landfors, Kristoffer |
| Publisher | Umeå universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UMNAD ; 1220 |
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