Advancing Database Security to Secure Big Data
Big data solutions have grown in popularity owing to the accumulation of digital information and data worldwide. The entry of IoT into the daily household converting appliance into data collectors to track behavior for data scientists has made the big data storage indispensible.
Coming to the rescue, NoSQL database offers the advantages of size, speed, selection, and authenticity, to handle large data storage, avoiding the surplus computing power and increased costs. Big data is an option that is available and accessible to all, due to the large number of reliable solution providers. From the security standpoint, relational databases have been present since the beginning. Large volumes of data are a victim of breaches, insider threats, and security compromises. While it may seem like a humungous task to secure large data, it is a workable and practical aspect.
Big data maximizes the existing computing power and facilitates data backup by spreading to distributed environments, but in the process, leaving the organization devoid of the information of big data clusters and their locations. A discovery process helps to point out the servers where big data resides and also figure out anonymous databases residing in the enterprise network.
Data that is mapped during the discovery process is sorted and sensitive data that requires protection is identified. The sensitive data may be trade secrets, as well as medical, financial and identity data. Knowing the clusters where this sensitive information helps organizations secure them better and more effectively.
With the knowledge of the residing sensitive information and its security status, there is a clear understanding of the utilization of existing protection tools. An assessment process test can be carried out to detect vulnerabilities in the database and misconfigurations. The vulnerability tests such as CIS and DISA are benchmarks. It is important to monitor the data in order to have an audit trail of all actions performed with a data set. Besides, alerts can be generated when an account attempts to access secure data, and also logged for future reporting.