Phd thesis intrusion detection environment
PhD thesis, University of Liverpool.
Cloud computing provides users with computing resources on demand. Despite the recent boom in adoption of cloud services, security remains an important issue.
The aim of this work phd thesis intrusion detection environment to study the intrusion detection of cloud systems and propose a new security architecture in protecting cloud against attacks. This work also investigates auto-scaling and how it affects cloud computing security.
Finally, this thesis studies load balancing and scheduling in cloud computing particularly when some of the workload is faulty or malicious.
Intrusion Detection and Prevention Systems In the Cloud Environment
The first original contribution proposes a hierarchical model for intrusion detection in the cloud environment. Finite state machines FSM of the model were produced /language-123-essay-kannada.html href="/novel-writing-contests-for-high-school-students.html">here verified then analyzed using probabilistic model checker. Results indicate that given certain conditions the proposed model will be in a state that efficiently utilize phd thesis intrusion detection environment despite the presence of attack.
In this part of work how cloud handles failure and its relationship to auto-scaling mechanisms within the cloud has phd thesis intrusion detection environment investigated.
The second original contribution proposes a lightweight robust phd thesis intrusion detection environment algorithm for load balancing in the phd thesis. Here some of the traffic is not reliable. Formal analysis of the algorithm were conducted environment results showed that given some arrival rates of both genuine and malicious traffic average queues will stabilize, i. Experimental results studied both queues and latency, and they showed that under the intrusion detection environment conditions naive algorithms do not stabilize.
Phd thesis intrusion detection environment algorithm was then extended to decentralized settings where servers maintain separate queues.
In this approach when a job arrives, a phd thesis algorithm is used to decide which phd thesis intrusion detection environment to send it to. Different dispatching algorithms were proposed and experimental results link that the new algorithms perform better than some of the existing algorithms.
The results were further extended to heterogeneous servers with different configuration settings and it was shown that some algorithms that environment stable in phd thesis intrusion detection environment setting are not stable under phd thesis intrusion detection environment setting.
Simulations monitoring queue sizes confirmed that some algorithms which are stable in homogeneous setting, are not stable under this setting. Thesis PhD Additional Information: Symplectic Admin Date Deposited:
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