Economic Denial Of Sustainability (EDOS) Attack Mitigation Mechanism In Cloud Computing Environments

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Date
2017-03
Authors
Bawa, Parminder Singh
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Publisher
Universiti Sains Malaysia
Abstract
Cloud computing (CC) is the next revolution in the Information and Communication Technology arena. CC is often provided as a service comparable to utility services such as electricity, water and telecommunications. Cloud service providers (CSP) offers tailored CC services like Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS), which are delivered as subscription-based services, in which customers pay based on usage. Many organizations and service providers have started shifting from traditional server-cluster infrastructure to cloud-based infrastructure. Nevertheless, security is one of the main factors that inhibit the proliferation of cloud computing. The threat of Distributed Denial of Service (DDoS) attack continues to wreak havoc in these cloud infrastructures. In addition to DDoS attacks, a new form of attack known as Economic Denial of Sustainability (EDoS) attack has emerged in recent years. EDoS which is unique to public cloud infrastructure may not be easily detected as with DDoS. DDoS attack in conventional computing setup usually disrupts the service, which affects the client reputation, and results in financial loss. In CC environment, service disruption is very rare due to the auto-scalability (Elasticity) capability and availability of service level agreements (SLA). However, auto scalability utilize more computing resources in event of a DDoS attack, exceeding the economic bounds for service delivery, thereby triggering EDoS for the organization targeted. Although EDoS attacks are small at the moment, it is expected to grow in the near future in tandem with the growth in cloud usage. There are few EDoS detection and mitigation techniques are available but they have weaknesses and not efficient in mitigating EDoS. Therefore, thesis proposes the EDoS mitigation mechanism (EMM). The primary focus of this mechanism is to provide a real-time and effective mitigation of EDoS attack. EMM relies on an active real-time monitoring of network using sFlow technology which parses the network traffic using flow samples. Several experiments were carried out using a production ready OpenStack- SDN test-bed that was designed and developed as part of the thesis contribution. A number of attack scenarios were created to test the effectiveness of EMM in a cloud environment and results were validated by comparing it with other mitigation techniques namely EDoS-Shield. The obtained results indicated that EMM provides a more effective and efficient mitigation performance to EDoS attacks in comparison to EDoS-Shield. In particular, the proposed EMM is able to detect attacks that are executed using previously whitelisted IP addresses. EDoS-Shield is not able to detect nor mitigate attacks in such a scenario.
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Cloud computing is the next revolution , in the Information and Communication Technology arena.
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