Classic intrusion detection mechanisms are not flexible enough to cope with cloud specific characteristics such as frequent infrastructure changes. This makes them unable to address new cloud specific security issues. In this paper we introduce the cloud incident detection system Security Audit as a Service (SAaaS). It is built upon intelligent autonomous agents, which are aware of underlying business driven intercommunication of cloud services. This enables the presented SAaaS architecture to be flexible and to supported cross customer event monitoring within a cloud infrastructure. A contribution of this paper it to provide a high-level design of the SAaaS architecture, an introduction into the proposed Security Business Flow Language (SBFL), a first prototype of an autonomous agent and an evaluation about, which cloud specific security problems are addressed by the presented architecture. It is shown that autonomous agents and behaviour analysis are fertile approaches to detect cloud specific security problems and can create a cloud audit system.
The paper considers the requirement for information security within the domain of online distance learning. A generic module structure is presented which represents a high level abstraction of the different stages of the educational process. This leads into a discussion of the main security issues that must be considered at each stage. These various requirements are being addressed in practice by the security framework being developed by the SDLearn research project, a collaborative initiative between higher academic establishments in the UK and Germany.
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