In addition, this paper introduces a new security mechanism for privacy preserving data handling with MongoDB to ensure the privacy of the data before being processed. Finally, in the third phase we discussed in detail root causes and some prevention techniques of vulnerabilities found in the system. Next, in the second phase we proposed a vulnerability analysis testbed to find vulnerabilities associated with the system.
This paper presents the fourth phase of our continuous research where in the first phase we proposed a data analytic framework with MongoDB and Linux Containers (LXCs) with basic security requirements. Therefore, this paper proposes and implements some security mechanisms and techniques, such as secure authentication, secure authorization, and encryption, to assure the overall security of a big data analytic framework with MongoDB free community edition. The protection of confidential data, such as social security numbers, financial information, etc., of the customers and/or employees is among the key responsibilities of any organization, and damage to such sensitive data can easily pose a threat to the future of a business and the security of the customers.
The frequency and scale of unauthorized access cases and misuses of data access privileges are a growing concern of many organizations.
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