Abstract

A revolution in manufacturing systems is underway: substantial recent investment has been directed towards the development of smart manufacturing systems that are able to respond in real time to changes in customer demands, as well as the conditions in the supply chain and in the factory itself. Smart manufacturing is a key component of the broader thrust towards Industry 4.0, and relies on the creation of a bridge between digital and physical environments through Internet of Things (IoT) technologies, coupled with enhancements to those digital environments through greater use of cloud systems, data analytics and machine learning. Whilst these individual technologies have been in development for some time, their integration with industrial systems leads to new challenges as well as potential benefits. In this paper, we explore the challenges faced by those wishing to secure smart manufacturing systems. Lessons from history suggest that where an attempt has been made to retrofit security on systems for which the primary driver was the development of functionality, there are inevitable and costly breaches. Indeed, today's manufacturing systems have started to experience this over the past few years; however, the integration of complex smart manufacturing technologies massively increases the scope for attack from adversaries aiming at industrial espionage and sabotage. The potential outcome of these attacks ranges from economic damage and lost production, through injury and loss of life, to catastrophic nation-wide effects. In this paper, we discuss the security of existing industrial and manufacturing systems, existing vulnerabilities, potential future cyber-attacks, the weaknesses of existing measures, the levels of awareness and preparedness for future security challenges, and why security must play a key role underpinning the development of future smart manufacturing systems.

Highlights

  • Levels of investment in smart manufacturing have been rising rapidly – more than half of manufacturers have invested at least $100 million in the activity

  • Most of this advice is based on studies on corporate networks and, despite the awareness and training programmes, users continue to become victims of social engineering methods: they regularly fall for phishing attacks [6], for example there is a lack of empirical studies looking at the human factors in security management at the plant level and on factory floors; the importance of this will grow with the increase in attacks

  • The move to commercial off-the-shelf (COTS) technologies reduces the protection currently afforded by the implicit requirement for specialised knowledge in attacking manufacturing systems: there is a wealth of prior knowledge for attackers to draw upon

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Summary

Introduction

Levels of investment in smart manufacturing have been rising rapidly – more than half of manufacturers have invested at least $100 million in the activity. It is no surprise that many manufacturers – with numbers reaching as high as 67% for industrial manufacturing – have smart factory initiatives and, if Capgemini's estimates are to be believed, the result will be a gain to the global economy of $500 billion to $1.5 trillion over the five years Much of this projected growth is predicated on the use of Internet of Things (IoT) technologies, coupled with cloud computing, data analytics, machine learning and AI. To extend network infrastructure to remote areas, increase sensing capacity, handle mobility and reduce installation costs, there is an increase in the deployment of wireless networks Both approaches have the potential to leave networks vulnerable and the scale of this vulnerability is under-appreciated in the industry: according to data collected from Project SHINE, between April 2012 and January 2014, an excess of 500,000 Internet-accessible manufacturing devices in control system environments were found [5].

Current manufacturing systems
Smart manufacturing systems
Reported incidents against manufacturing systems
Reported incidents against smart manufacturing systems technologies
Difference between manufacturing systems and IT systems
Vulnerabilities
Attack types
Adversary model
Lifecycle of a targetted attack
Security solutions for manufacturing systems
Cryptographic techniques
Intrusion detection systems for production or process systems
Security skills training and human factors
Post incident management
Future research directions
Findings
Conclusions
Full Text
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