Big Data Security Issues from the Perspective of IoT and Cloud Computing: A Review

Abstract

Background: The data is one of the prime assets in today’s world. The continuous data generation ultimately creates huge volume of data that cannot be processed or stored by a normal relational database management system. This problem is addressed by a new concept: Big Data. Apart from the size of data, security and privacy of data are the more challenging issues in Big data technology. Objective: The primary objective of the research is to identify the potential security threats of different big data computing technologies and provide a defense mechanism to mitigate the issues. Methods: To identify the security issues, different existing big data systems are thoroughly analysed and observed. Security systems are completely dependent on the system architecture. This can be a single architecture (dependent on one computing technology) or multi architecture type (dependent on multiple computing technologies). The internal mechanism of different technologies is observed and how the attacks change the behavioural pattern of the systems is the main backbone of the research. Based on the behaviour of dissimilar attacks, a comprehensive defense mechanism is identified. Security and privacy challenges of mobile healthcare are also considered as a case study. Results: The complete lists of big data computing security threats in different layers of the systems are identified. Through this research the remedial measures of the different attacks are found. The security challenges of mobile healthcare technology and its predictive measurements are sorted out. The changes of big data security systems behaviour based on its architecture are of the major findings of this research. Conclusion: The integration of mobile healthcare along with Internet of Things (IoT) and blockchain computing can enhance the system level and hence security threats can be minimized.