Privacy-Breaching Patterns in NoSQL Databases

Kanika Goel,Arthur H M Ter Hofstede

doi:10.1109/access.2021.3062034

Kanika Goel, Arthur H M Ter Hofstede

Open Access

https://doi.org/10.1109/access.2021.3062034

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Abstract

NoSQL databases disrupted the database market when first introduced. Their contemporary relevance has increased further in the era of big data due to the demands placed on (real-time) analytics. NoSQL databases are well placed to meet these demands due to their performance, availability, scalability, and storage solutions. Unfortunately, to achieve these features, compromises have been made with respect to security and privacy. Growing community awareness and unease combined with increased legislative requirements around data privacy have made such compromises less palatable, risky, or downright unacceptable. And though there is a growing body of knowledge related to data privacy in NoSQL databases, it is diverse and fragmented, and does not adequately address the challenges arising from the current environment. This paper aims to systematically examine various privacy weaknesses of NoSQL databases in the form of patterns. The patterns are shown to manifest themselves in well-known NoSQL databases and this evaluation can be used for benchmarking purposes. Through a survey it is demonstrated that the patterns have been observed in practice and are perceived as relevant. The pattern collection forms a repository of knowledge that can serve as a starting point for future privacy-related research for NoSQL databases through its identification of key problems, trade-offs, existing solution mechanisms, and its provision of terminology.

Highlights

Technological advancements have resulted in an inconceivable growth in data
Data privacy is of growing concern, which has resulted in an emerging stream of privacy-related research in NoSQL databases
The patterns presented in this paper have been derived after collating issues that have impacted multiple types of NoSQL databases

Summary

INTRODUCTION

Technological advancements have resulted in an inconceivable growth in data. The massive amounts of data generated on an everyday basis today have become the wealth of organisations, harnessed for improved decision making. With the growing awareness of the need for data privacy, an emerging stream of privacy-related research can be observed in the field of NoSQL databases [10]. While this is clearly a trend in the right direction, the research efforts are still quite diverse and fragmented and not yet amounting to a cohesive program of work. The privacy-breaching patterns presented in this paper offer a repository of knowledge about a range of privacy-related issues that NoSQL databases can be exposed to. The pattern collection enables benchmarking, i.e., selection of a suitable database for a particular application and provides a foundation for future work in the area of data privacy and NoSQL databases.

AND RELATED WORK

SYSTEM EVALUATION

EMPIRICAL EVALUATION

Findings

CONCLUSION