A Predictive Model for Risk and Trust Assessment in Cloud Computing: Taxonomy and Analysis for Attack Pattern Detection

Abstract

Cloud computing environments consist of many entities that have different roles, such as provider and customer, and multiple interactions amongst them. Trust is an essential element to develop confidence-based relationships amongst the various components in such a diverse environment. The current chapter presents the taxonomy of trust models and classification of information sources for trust assess- ment. Furthermore, it presents the taxonomy of risk factors in cloud computing environment. It analyses further the existing approaches and portrays the potential of enhancing trust development by merging trust assessment and risk assessment methodologies. The aim of the proposed solution is to combine information sources collected from various trust and risk assessment systems deployed in cloud services, with data related to attack patterns. Specifically, the approach suggests a new qualitative solution that could analyze each symptom, indicator, and vulnerability in order to detect the impact and likelihood of attacks directed at cloud computing environ- ments. Therefore, possible implementation of the proposed framework might help to minimise false positive alarms, as well as to improve performance and security, in the cloud computing environment.