Data Security and Privacy Functions in Fog Data Analytics

Abstract

The increasing pervasiveness of the Internet of Things (IoT) has led to more connected remote devices, which entails exponentially more data and computation. This creates the need for the phenomenon of cloud computing. Cloud computing uses third-party hardware in geographically remote locations, which communicate via the internet. And extension to cloud computing is fog computing, which brings the cloud closer to the user, thus decreasing the computation and storage time. However, the geographically distributed fog network nodes are vulnerable to different types of security attacks. This chapter studies the reason for the susceptibility of fog nodes. The security systems and concerns in cloud and fog computing are compared in the chapter. The chapter also examines the various types of attacks to which the fog network is vulnerable. These types include man in the middle attacks, authentication threats, distributed denial of service and others. Finally, the chapter aims at investigating the different methods to handle these types of attacks. The first approach is the prevention of security attacks, which includes techniques like identity authentication, access control and cryptographic schemes. The second approach for data privacy and security handling is detection. The chapter delves deeper with methods like intrusion detection, data integrity check and network traffic analysis. The last approach covered by the chapter is recovery, which covers recovery schemes suited to tackle specific attacks. Thus, the chapter intends to impart an intensive and multi-faceted understanding of data security and privacy in fog data analytics.