期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2013
卷号：4
期号：1
页码：14-16
出版社：TechScience Publications
摘要：Throughout companies, government departments, and doctors’ offices, database systems are used. This particular system stores and retrieves sensitive information such as social security numbers, financial statements, and highly classified data. Organizations with sensitive data in their hands need to be secured using different security techniques and policies. In order to secure the data on a computer, they need to implement techniques like access control, auditing, authentication, encryption, etc; however, malicious users are still breaking into companies’ data. Needless to say, companies are not implementing poor security techniques but hackers are just getting smarter and smarter. This is where IT employees need to find new techniques or enhance previous ones. Thus, we develop an inference violation detection system to protect sensitive data content. Based on data dependency, database schema and semantic knowledge, we constructed a semantic inference model (SIM) that represents the possible inference channels from any attribute to the pre-assigned sensitive attributes. This model can work for single user as well as for multi user environment. For a single user case, when a user poses a query, the detection system will examine his/her past query log and calculate the probability of inferring sensitive information. The query request will be denied if the inference probability exceeds the pre-specified threshold. For multi-user cases, the users may share their query answers to increase the inference probability. Therefore, we develop a model to evaluate collaborative inference based on the query sequences of collaborators and their task-sensitive collaboration levels.
关键词：Database; Security; and Detection Inferences.;Semantic Inference Model(SIM).
