Security Issues and Privacy Concerns in Industry 4.0 Applications. Группа авторов

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      1 *Corresponding author: [email protected]

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      Fourth Industrial Revolution Application: Network Forensics Cloud Security Issues

       Abdullah Ayub Khan1, Asif Ali Laghari1*, Shafique Awan2 and Awais Khan Jumani3

       ¹ Department of Computer Science, Sindh Madressatul Islam University, Karachi, Sindh, Pakistan

       ² Department of Computing Science & Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, Sindh, Pakistan

       ³ Department of Computer Science, ILMA University Karachi, Sindh, Pakistan

       Abstract

      This chapter studies the cloud security issues in network forensics and a large-scale machine-to-machine (M2M) communication impact on the fourth industrial revolution. The parameters help to gather, analyze, and document information about incidentals security and network-based crime activities. It also supports the solving of a complication related to the network traffic in the cloud, virtual machine dynamic migration, virtual resources of cloud clients, provides an environment like multi-tenancy, does not infringe on the security and protection of other cloud users, and most important, avoids transferring costs of large sets of data and processed directly. Cloud security and M2M communication permit the discovery of the best conceivable security configuration, improve communication, self-monitoring, and diagnose cloud security issues without the need for human intervention. Restrictions and crucial points are emphasized to arrange for initial forensics investigations and also further studies in this area. This chapter presents a model that is generic in nature for network forensics in the cloud environment as well as defines prototype artifact that articulates the M2M communication security issue that impacts on fourth industrial revolution application. We validate the architecture prototype with an implementation based on the OpenNebula Hypervisor web-based interface and the NetworkMiner analysis framework.

Keywords: Network forensic, digital forensics, cloud forensics, cloud computing services, M2M communication application, fourth industrial revolution, impact and issues in Industry 4.0 cloud application

2.1 Introduction

      Nowadays, several organizations use cloud resources offered by a cloud service provider as an external IT-infrastructure for their organization. Cloud computing has emerged as a highly powerful and most popular field over the past few years, the significant aspect of which is getting more focus on virtual crime and cyber-threat activities that are IT-based services [1]. As a result, digital forensics has gained increasing importance as a cloud investigation technology. Cloud computing security imposes several new challenges in between M2M communication technology [2, 3]. In this chapter, we address critical cloud security issues, network forensics investigation challenges, machine communication interruption, and the impact on industry 4.0 application.

      2.1.1 Network Forensics

      Network forensics (NF) is a crucial sub-branch of digital forensics (DF), itself a branch of forensics science, in which experts and law enforcement capture, record and analyze network events, and discover the source of attacks and cyber incidents [4] that enhance security in the cyber environment. Simson Garfinkel writes, “network forensics systems can be one of two kinds either catch-it-as-you-can or stop, look and listen to system” [5]. Catch-it-as-you-can is a network approach in which packages pass through a certain traffic point, catch packages, and subsequently store analysis in batch mode. The approach requires a huge amount of memory storage that usually involves a Redundant Array of Inexpensive Disks or Redundant Array of Independent Disks (RAID) system. On the other side, Stop, Look, and Listen is a network approach in which individual package analysis is carried out in an initial way; only certain information stores in the memory for future analysis. Undoubtedly, this type of method used less memory storage but needs more processing power to tackle the incoming traffic on the network environment.

In computer forensics, data is more often seized in disk storage, which makes it easier to obtain; unlike DF, NF is more difficult to carry out data while it is transmitted across the network and then lost in a short time [6]. Anyone planning to apply NF tools for analysis data needs to know about the privacy laws; privacy and data protection laws restrict active tracking as well as analysis of network traffic without explicit permission. In the network and IT infrastructure, NF is used in a proactive fashion to dig out flaws; however, the scope includes shoring up defenses by the officers of information security and IT administrators against future cyber-attacks.

      2.1.2 The Fourth Industrial Revolution

      The digital transformation of production, manufacturing, and several other related industries that value process creation have led to the fourth industrial revolution [9], is a new phase in the organization and control of chain value interchangeably [7]. Industry 4.0 is concerned with those areas that are not usually classified such as smart cities where industry applications cannot perform their own rights [8]. In the first industrial revolution, the advent of mechanization, water, and steam power made a huge and positive impact on the traditional industry. In short, the first revolution boosted industrial production; the second industrial revolution revolved around using electricity, mass production, and assembly lines. Industry 3.0 was the revolution of electronics, IT systems, and automation at the industrial level that led to Industry 4.0, which is [10] associated with the cyber-physical system.

      The Industry 4.0 briefly elaborates the automation growth trend and data exchange in industrial technology as well as processes within the manufacturing industry, such as Artificial Intelligence (AI), Cloud Computing (CC), the Internet of Things (IoT), the Industrial Internet of Things (IIoT), Cyber-Physical Systems (CPS), Cognitive Computing, Smart Manufacture (SM), and Smart