Among the existing methods for analysing internet traffic, one focuses on unsolicited and often harmful packets, referred to as Internet Background Radiation (IBR). IBR data can be captured by using cloud-based comput...
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Among the existing methods for analysing internet traffic, one focuses on unsolicited and often harmful packets, referred to as Internet Background Radiation (IBR). IBR data can be captured by using cloud-based comput...
Among the existing methods for analysing internet traffic, one focuses on unsolicited and often harmful packets, referred to as Internet Background Radiation (IBR). IBR data can be captured by using cloud-based computing instances to listen for incoming packets and recording the received headers and contents in files using the PCAP format. No services are run on these hosts so all traffic can be regarded as non-legitimate. This work presents the research plan for capturing a year-long sample of the IBR arriving to up to 1500 geographically distributed sensors across a major service cloud provider. In combination with collection, a data analysis pipeline will be constructed to enable the querying of most relevant quantitative and qualitative aspects of the resulting dataset. The ultimate goal is to answer “how is the IBR characterised when captured within the context of cloud computing?”. Results will include packet distribution according to the properties of the network, transport, and application layers, together with an evaluation of traffic linking to botnet activity such as Mirai and Moobot.
Deployment and configuration of grid computing applications are exhaustive and error-prone tasks, and represent a weak link of the lifecycle of grid applications. To address the problem, this paper proposes AGRADC, an...
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Deployment and configuration of grid computing applications are exhaustive and error-prone tasks, and represent a weak link of the lifecycle of grid applications. To address the problem, this paper proposes AGRADC, an...
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Deployment and configuration of grid computing applications are exhaustive and error-prone tasks, and represent a weak link of the lifecycle of grid applications. To address the problem, this paper proposes AGRADC, an architecture to instantiate grid applications on demand, which incorporates features from the autonomic computing paradigm. This architecture improves the grid application development process, providing tools to define a deployment flow, configuration parameters, and actions to be executed when adverse situations like faults arise.
This paper presents the Urban Environment Model (UEM), a novel approach through which a large number of virtual humans can populate a urban space by considering normal life situations. Using this model, the semantic i...
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