Models and Languages for Big Data Protection

In this era of digitalizing the world, the protection of huge datasets often referred to as “big data” has emerged to be one of the pressing concerns not only for people but also for organizations. Big data refers to enormous, heterogenous, and constantly moving datasets too big or complex to analyze with traditional data management tools. This paper discusses various models and languages developed for security and privacy of big data. We clearly state specific problems brought about by big data related to privacy, access control, and integrity and discuss various technological approaches such as encryption, anonymization, access control policies, and blockchain. We also review different programming languages and frameworks optimized for the protection of data. Finally, we appeal to organizations to embrace strong big data protection practices and be prepared to the evolving threats.