Risk access control model for Hadoop - Jia-shuai LI; Chang-gen PENG; Yi-jie ZHU; Hai-feng MA (网络与信息安全学报)
Traditional access control models are hard to restrain the malicious behavior of authorized users. Accord-ingly, Hadoop platform with this access control model is difficult to prevent the risk of privacy disclosure. A model of access control based on risk was proposed. A risk function of information entropy was designed from users’ his-torical behavior based on setting the tags of subject and object. Furthermore, the tracking chain of risk was built, which could adjust the users’ access authority dynamically according to the risk value and its volatility. Combining with access token and risk supervision, the risk access control mechanism for big data privacy protection was real-ized, which could be applied to enhance the security of Hadoop Kerberos protocol. Finally, the experiment result shows that the model can constrain the authorized users’ access behavior effectively.