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User Behaviour-Based Access Control for Social Media with Qualitative Research and Bayesian Modelling

机译:定性研究和贝叶斯建模的基于用户行为的社交媒体访问控制

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Access control systems protect against unauthorised access to resources, where security policies define what is allowed, and what is not. Traditional models focus on protecting access to files, directories, and processes; however, the rise of social media has brought about a need for a new type of model – one focused on sharing rather than protecting, and based on user behaviour rather than a technical specification. A methodology is proposed to perform what we call user behaviour-based access control, building access control policies through analysis of user behaviour. The process involves a combination of qualitative research practices and probabilistic reasoning to address the problems of uncertainty and diversity associated with the study of human behaviour. Data collection and analysis is achieved through semi-structured interviewing and grounded theory techniques. The results of the analysis are used to build a probabilistic model, in the form of a Bayesian network, which implements access control. Requests containing observations of the attribute values are pushed through the network to produce a probabilistic access control decision. The method has been evaluated on real social media users, and has been shown to be effective in capturing and mechanising user sharing preferences.
机译:访问控制系统可防止未经授权的资源访问,其中安全策略定义了允许的内容和不允许的内容。传统模型侧重于保护对文件,目录和进程的访问。但是,社交媒体的兴起带来了对一种新型模型的需求-一种侧重于共享而不是保护,并且基于用户行为而不是技术规范的模型。提出了一种方法来执行我们所谓的基于用户行为的访问控制,并通过分析用户行为来构建访问控制策略。该过程涉及定性研究实践和概率推理的结合,以解决与人类行为研究相关的不确定性和多样性问题。数据收集和分析是通过半结构化访谈和扎实的理论技术来实现的。分析结果用于建立贝叶斯网络形式的概率模型,该模型实现访问控制。包含对属性值的观察的请求将通过网络推送,以产生概率访问控制决策。该方法已在真实的社交媒体用户上进行了评估,并已证明在捕获和机械化用户共享首选项方面有效。

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