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Online social networks are becoming increasingly popular in Saudi society, with their usage rising rapidly and with sites such as Twitter, Facebook, and LinkedIn in particular experiencing a dramatic uptake in new users over the last year. Indeed, Snapchat has indicated that Saudi Arabia is one of its ten strongest markets globally. In this study, we identify and measure various awareness aspects of privacy for online social networks in Saudi Arabia and contrast them with individuals protective actions. The results in this paper are based on a statistical analysis of a survey questionnaire. A reliability test was conducted to assure the internal consistency and the reliability of the measures used in the study. Analysis of the study showed high levels of privacy concerns among Saudi society. A correlation analysis was conducted and showed that although individuals seem to be concerned about privacy and the protection of their personal information, their behavior was not proportionate with their privacy concerns.This observation was further verified among the different genders and age groups with respect to their claimed privacy concerns, where the results revealed no significant difference between the different groups. A closer investigation of the awareness of privacy issues in Snapchat -the social platform chosen as the research subject for this study -revealed that users are highly aware of its privacy issues. The results of this study can be useful to assist developing new privacy techniques, whether technological or awareness-based, that can facilitate the safe use of social networks, with increased privacy protection capabilities.

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Demands for better design and analysis of access controls require system-level evaluation models that can facilitate a quantitative and consistent study of operational capabilities and economics of access control implementations. Previous works on access control models are mainly centered on the access interaction between system subjects and objects with respect to rights, addressing their basic security goals, thus failing to address other dependability attributes. To address this shortcoming, we first propose the abstraction of a computing system into: objects and rights of subjects (called in this paper assets and controls, respectively) to study the unavoidable failure interdependency between these two classes, a perspective that can be a basis for various failure-related assessment methods. We then propose a modeling technique that probabilistically captures the interaction between assets and controls into a graph theoretic paradigm; we specifically show how Bayesian Networks (BNs) can model this dilemma. This paper presents the proposed abstraction, modeling formalism, and associated notation, along with a demonstration example of various useful inferences and further research directions.