# Main Issues in Big Data Security
## 1 Introduction  
Over the last few years, data has become one of the most important assets for companies in almost every field. Not only are they important for companies related to the computer science industry, but also for organisations, such as countries' governments, healthcare, education, or the engineering sector. Data are essential with respect to carrying out their daily activities, and also helping the businesses' management to achieve their goals and make the best decisions on the basis of the information extracted from them [1]. It is estimated that of all the data in recorded human history, 90 percent has been created in the last few years. In 2003, five exabytes of data were created by humans, and this amount of information is, at present, created within two days [2].  
This tendency towards increasing the volume and detail of the data that is collected by companies will not change in the near future, as the rise of social networks, multimedia, and the Internet of Things (IoT) is producing an overwhelming flow of data [3]. We are living in the era of Big Data. Furthermore, this data is mostly unstructured, signifying that traditional systems are not capable of analysing it. Organisations are willing to extract more beneficial information from this high volume and variety of data [4]. A new analysis paradigm with which to analyse and better understand this data, therefore, emerged in order to obtain not only private, but also public, benefits, and this was Big Data [5].  
Each new disruptive technology brings new issues with it. In the case of Big Data, these issues are related not only to the volume or the variety of data, but also to data quality, data privacy, and data security. This paper will focus on the subjects of Big Data privacy and security. Big Data not only increases the scale of the challenges related to privacy and security as they are addressed in traditional security management, but also create new ones that need to be approached in a new way [6]. As more data is stored and analysed by organisations or governments, more regulationsare needed to address these concerns. Achieving security in Big Data has, therefore, become one of the most important barriers that could slow down the spread of technology; without adequate security guarantees, Big Data will not achieve the required level of trust [7]. Big Data brings big responsibility [8].  
According to the Big Data Working Group at the Cloud Security Alliance organisation there are, principally, four different aspects of Big Data security: infrastructure security, data privacy, data management, and integrity and reactive security [9]. This division of Big Data security into four principal topics has also been used by the International Organisation for Standardisation in order to create a security standard for security in Big Data. Figure 1 contains a scheme showing the main topics related to security in Big Data.  
The purposes of this paper are to highlight the main security challenges that may affect Big Data, along with the solutions that researchers have proposed in order to deal with them. This big picture of the security problem may help other researchers to better understand the security changes produced by the inherent characteristics of the Big Data framework and, consequently, find new research lines so as to carry out more in-depth investigations. This goal has been accomplished by carrying out an empirical investigation by means of the systematic mapping study method with the aim of obtaining a complete background to the security problem as regards Big Data and the proposed solutions.  
This paper is consequently structured as follows: first we provide a brief introduction to the subject of Big Data, after which we describe the systematic mapping study process. We then go on to analyse the results obtained, and additionally discuss them. Finally, we present a section concerning our conclusions.