الفهرس 
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Abstract
The rapid advancement of the use of information technology in industry, government, and academia raises challenging questions and problems regarding the protection and use of personal information. Threats and risks to databases have increased and therefore, the need for securing databases has also increased to prevent unauthorized data observation and modification ensuring the confidentiality of the data. Hackers have been able to target large databases in recent years to obtain sensitive information like credit card numbers and other personal information. It is important to protect databases against these risks, and this is where database security comes into place. The key technical challenge is to balance data usage with the need to preserve the privacy of individual data. Not all risks come from outsider threats; the privacy preserving model should take care of insider and outsider threats. The dramatic increase in the usage of the internet raises questions regarding privacy if sensitive data is published. The privacy-preserving model should satisfy the concept of privacy-preserving data publishing. The past few years have seen a dramatic increase in the growth of data collected from users/sensors and other embedded systems. That is why a new term called “Big Data” was introduced. A new challenge is created by the adoption of big data in order to guarantee the security and privacy preservation of this data. One of the main characteristics of big data is velocity which means the flow of creation and update of this data is high. The challenge is how to extract the data while preserving security with minimal effect on the performance. In this research, it is aimed to find a solution for privacy preservation in systems that adopt big data. Big data results in creating new techniques and methodologies to handle such an amount of data. This is mainly called NoSQL (Not only SQL databases) which contains different types. This diversity in database types created another challenge to security in big data. The proposed research meets the particular requirements of the workflow systems such as the notion of a task life cycle, dynamic access control management, active permission assignment, and applying access control policies to enhance user privacy. In addition, the proposed solution adapts the notion of the conditional purposes, which allows users to use some data for certain purpose with conditions. Conditional purpose provides more reliable data management because more information can be extracted assuring the same user privacy. The solution also protects against users who have administrative permissions. The research could be considered a general model which can be applied to more than one type of NoSQL database.