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2019 | Buch

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Security and Privacy Trends in the Industrial Internet of Things

herausgegeben von: Prof. Cristina Alcaraz

Verlag: Springer International Publishing

Buchreihe : Advanced Sciences and Technologies for Security Applications

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book, written by leaders in the protection field of critical infrastructures, provides an extended overview of the technological and operative advantages together with the security problems and challenges of the new paradigm of the Internet of Things in today’s industry, also known as the Industry Internet of Things (IIoT).

The incorporation of the new embedded technologies and the interconnected networking advances in the automation and monitoring processes, certainly multiplies the functional complexities of the underlying control system, whilst increasing security and privacy risks. The critical nature of the application context and its relevance for the well-being of citizens and their economy, attracts the attention of multiple, advanced attackers, with stealthy abilities to evade security policies, ex-filter information or exploit vulnerabilities. Some real-life events and registers in CERTs have already clearly demonstrated how the control industry can become vulnerable to multiple types of advanced threats whose focus consists in hitting the safety and security of the control processes.

This book, therefore, comprises a detailed spectrum of research papers with highly analytical content and actuation procedures to cover the relevant security and privacy issues such as data protection, awareness, response and resilience, all of them working at optimal times. Readers will be able to comprehend the construction problems of the fourth industrial revolution and are introduced to effective, lightweight protection solutions which can be integrated as part of the new IIoT-based monitoring ecosystem.

Inhaltsverzeichnis

Frontmatter

Security Analysis and Advanced Threats

Frontmatter

Securing Industrial Control Systems

Abstract

We propose controllability, observability, and operability as the core security objectives of a control system, whilst the much-used triad of confidentiality, integrity, and availability captures the security requirements on IT infrastructures. We discuss how the deployment of IT in industrial control systems has changed the attack surface, how this invalidates assumptions about independent failure modes crucial in safety design, and explain why stronger IT infrastructure security does not necessarily imply better ICS security. We show how process physics can be used to carry attack payloads and thus become an instrument for the attacker, and argue that ICS security standards should expand their scope to the physical processes layer.

Marina Krotofil, Klaus Kursawe, Dieter Gollmann

Towards a Secure Industrial Internet of Things

Abstract

The Industrial Internet of Things (IIoT), being one of the underlying and enabling technologies of the Industry 4.0 initiative, brings about expectations for unprecedented value creation opportunities in industry. Unfortunately, these do not come without a price; in this case the price to pay is the increased vulnerabilities, the increased threats and the increased attack surface that result when industrial systems originally designed with little or no cybersecurity in mind connect to the Internet. Consequently, the cybersecurity of the IIoT becomes of paramount importance. Research has started focusing on this area, as well as on the related areas of cyber-physical systems security and industrial network security, but a multitude of issues still remain to be addressed. In this chapter, we review recent research results in the area of IIoT security, with an eye towards identifying trends on one hand and areas where research seems to lag behind on the other, by classifying research results using the security lifecycle model of the National Institute of Standards and Technology (NIST) framework for improving the cybersecurity of critical infrastructures.

Georgios Spathoulas, Sokratis Katsikas

Advanced Persistent Threats and Zero-Day Exploits in Industrial Internet of Things

Abstract

Manufacturing industry, electricity networks, supply chain, food production and water treatment plants have been heavily depended on Industrial Automation and Control (IAC) Systems. Integration of Information and Communication Technology (ICT) played a significant role in the evolution of these systems. New emerging trends and technologies, such as Internet-of-Things (IoT) interact with traditional, isolated IAC systems. Sectors such as manufacturing, electric grids, pharmaceuticals, and water treatment facilities incorporate part of these “smart” technologies in order to increase efficiency, performance and reduce production costs. But despite of its benefits, interconnectivity between smart and legacy IAC systems also creates complex interdependencies, which in turn, make imperative the need for more safety and security countermeasures. This rapid evolution has also affected greatly the threat landscape. In order to comprehend this radical change we present and analyze recent, well documented attacks that target mission critical IAC systems, which incorporate Industrial IoT technologies. In particular, we focus on highly profiled, sophisticated attacks against interconnected automation and monitoring field devices, related software platforms and systems (e.g., Programmable Logical Controllers – PLCs, industrial robots) installed on industrial facilities and smart grid generation, transmission and distribution networks and systems.

Ioannis Stellios, Panayiotis Kotzanikolaou, Mihalis Psarakis

Secure Interconnection Mechanisms

Frontmatter

A Survey on Lightweight Authenticated Encryption and Challenges for Securing Industrial IoT

Abstract

Embedded systems are widely deployed nowadays in various domains like smart cards, automobiles, telecommunications, home automation systems, computer networking, digital consumer electronics, defense and aerospace. IoT is the technology enabling the inter-connection of these embedded devices (composed of sensors, actuators etc.) through the internet to exchange data, optimize processes, monitor devices in order to generate benefits for the industry, the economy, and the end user. These operations typically consists of sensitive or critical information that needs to be protected against outside world. Therefore their security comes as a primary concern. However the main challenges while providing security for these devices are resource constrained environment in terms of computing power, memory capacity, chip area and the power usage. The limited capabilities of these devices necessitate the adoption of Lightweight Cryptography (LWC). Lightweight cryptography is a field dealing with cryptographic algorithms or cryptographic protocols specially designed for the usage in constrained environments which includes RFID tags, contactless smart cards, sensors, embedded systems, health-care devices and so on. This work provides a survey of existing lightweight authenticated encryption algorithms. We surveyed 17 lightweight AE schemes (LWAE), out of which 9 schemes are from the ongoing CAESAR competition.

Megha Agrawal, Jianying Zhou, Donghoon Chang

Access Control in the Industrial Internet of Things

Abstract

The Industrial Internet of Things (IIoT) is an ecosystem that consists of – among others – various networked sensors and actuators, achieving mainly advancements related with lowering production costs and providing workflow flexibility. Introducing access control in such environments is considered to be challenging, mainly due to the variety of technologies and protocols in IIoT devices and networks. Thus, various access control models and mechanisms should be examined, as well as the additional access control requirements posed by these industrial environments. To achieve these aims, we elaborate on existing state-of-the-art access control models and architectures and investigate access control requirements in IIoT, respectively. These steps provide valuable indications on what type of an access control model and architecture may be beneficial for application in the IIoT. We describe an access control architecture capable of achieving access control in IIoT using a layered approach and based on existing virtualization concepts (e.g., the cloud). Furthermore, we provide information on the functionality of the individual access control related components, as well as where these should be placed in the overall architecture. Considering this research area to be challenging, we finally discuss open issues and anticipate these directions to provide interesting multi-disciplinary insights in both industry and academia.

Stavros Salonikias, Antonios Gouglidis, Ioannis Mavridis, Dimitris Gritzalis

A Distributed Usage Control Framework for Industrial Internet of Things

Abstract

This work presents a distributed Usage Control framework designed to ensure high flexibility, performance and fault tolerance in security and safety policy enforcement. The framework has been designed for distributed Peer-to-Peer (P2P) systems, without a root of trust, being thus suitable for Industrial Internet of Things (IIoT) settings. The proposed framework benefits from the presence of a set of Usage Control Systems, logically interconnected through a DHT which enables shared and replicated memory, distributed evaluation and distributed attribute retrieval. Furthermore, being based on the Usage Control paradigm, it is able to enforce policies with mutable attributes, revoking ongoing sessions when policies are not matched anymore with the current request context. The presented framework is validated through performance experiments performed in both an emulated and real settings.

Antonio La Marra, Fabio Martinelli, Paolo Mori, Andrea Saracino

Advanced Protection Techniques

Frontmatter

Profiling Communications in Industrial IP Networks: Model Complexity and Anomaly Detection

Abstract

Profiling communication patterns between devices in the Industrial Internet of Things (IIoT) ecosystems is important for deploying security measures like detecting anomalies and potential cyber-attacks. In this chapter we perform deep-packet inspection of various industrial protocols to generate models of communications between pairs of IIoT devices; in particular, we use discrete-time Markov chain models applied to four different industrial networks: (1) an electrical substation, (2) a small-scale water testbed, (3) a large-scale water treatment facility, and (4) an energy management system of a university campus. These datasets represent a variety of modern industrial protocols communicating over IP-compatible networks, including EtherNet/IP (Ethernet/Industrial Protocol), DNP3 (Distributed Network Protocol), and Modbus/TCP (Transmission Control Protocol).

Mustafa Amir Faisal, Alvaro A. Cardenas, Avishai Wool

Improving Security in Industrial Internet of Things: A Distributed Intrusion Detection Methodology

Abstract

The interaction among networking, sensing, and control in the modern industry results in a variety of new devices used in many sectors such as health, energy distribution, and transportation. The on-going tendency of exploiting automation and data exchange in manufacturing technologies leads to the Industry 4.0. The fourth industrial revolution deals with Cyber-Physical Systems, the Internet of Things, cloud computing, and cognitive computing converging towards the Industrial Internet of Things. To be successful, this new era requires innovative paradigms to ensure the security of provided services and connected systems. In the industrial field, the problem gets more complex due to the need of protecting a large attack surface while guaranteeing the availability of the systems and the real-time response to the presence of threats. In this chapter, we perform an analysis of the existing industrial threats and we present a distributed intrusion detection methodology to deal with attacks affecting the Industrial Internet of Things scenarios.

Giuseppe Bernieri, Federica Pascucci

Who’s There? Evaluating Data Source Integrity and Veracity in IIoT Using Multivariate Statistical Process Control

Abstract

The security landscape in Industrial settings has completely changed in the last decades. From the initial primitive setups, industrial networks have evolved into massively interconnected environments, thus developing the Industrial Internet of Things (IIoT) paradigm. In IIoT, multiple, heterogeneous devices collaborate by collecting, sending and processing data. These data-driven environments have made possible to develop added-value services based on data that improve industrial process operation. However, it is necessary to audit incoming data to determine that the decisions are made based on correct data. In this chapter, we present an IIoT Anomaly Detection System (ADS), that audits the integrity and veracity of the data received from incoming connections. For this end, the ADS includes field data (physical qualities based on data) and connection metadata (interval between incoming connections and packet size) in the same anomaly detection model. The approach is based on multivariate statistical process Control and has been validated using data from a real water distribution plant.

Iñaki Garitano, Mikel Iturbe, Enaitz Ezpeleta, Urko Zurutuza

Secure Machine to Machine Communication in Industrial Internet of Things

Abstract

In todays world, Internet of Things (IoT), is an emerging technology, where many smart devices are connected with each other. The rapidly growing deployment of IoT in real-world applications and the advancement in technology has attracted the concept of Industrial Internet of Things (IIoTs). The large number of applications such as smart oil and gas industry, smart transportation, smart grid, smart health-care and smart metering are the few examples of the use of smart devices in IIoTs. These intelligent devices have the capabilities of sensing, actuating, storing, and processing of the data, and it causes challenge-able problems (e.g., communication security and reliability) in the network. In this book chapter, first we present the key benefits and challenges of the use of IoT technologies in today’s industries. Second, to address few of the identify challenges, we propose SCOUT, which is a secure machine to machine communication technique for IIoTs. In particular, SCOUT makes efficient use of the Routing Protocol for Low Power and Lossy Networks (RPL), the de facto routing protocol for IoT and an optimized remote software attestation algorithm to improve the communication security and scalability in large scale heterogeneous IIoT network scenarios. Finally, to show the deployment feasibility and working efficiency of SCOUT, we explain it with a real-world industrial use case.

Mauro Conti, Pallavi Kaliyar, Chhagan Lal

Privacy Issues in Industrial Connected Networks

Frontmatter

Modelling the Privacy Impact of External Knowledge for Sensor Data in the Industrial Internet of Things

Abstract

Some type of privacy-preserving transformation must be applied to any data record from Industrial Internet of Things (IIoT) before it is disclosed to the researchers or analysts. Based on the existing privacy models such as Differential Privacy (DP) and k-anonymity, we extend the DP model to explicitly incorporate feature dependencies, and to produce guarantees of privacy in a probabilistic form that generalize k-anonymity. We assume that additional (external) knowledge of these relations and models can be represented in the form of joint probability distributions, such as Mutual Information (MI). We propose an enhanced definition of DP in conjunction with a realisation for non-randomizing anonymizing strategies such as binning, reducing the extent of binning required and preserving more valuable information for researchers. This allows the formulation of privacy conditions over the evolving set of features such that each feature can be associated its own allowance for privacy budget. As a case study, we consider an example from the Industrial Medical Internet of Things (IMIoT). We have identified some challenges that are not completely addressed by existing privacy models. Unlike physiological measurements in conventional medical environments, IMIoT is likely to result in duplicate and overlapping measurements, which can be associated with different personally identifiable items of information. As an example, we present a model of sequential feature collection.

Salaheddin Darwish, Ilia Nouretdinov, Stephen Wolthusen

Security and Privacy Techniques for the Industrial Internet of Things

Abstract

The wide employment of Internet of Things (IoT) across industrial sectors creates the Industrial Internet of Things (IIoT). In practical applications, however, the IIoT has many attack surfaces. As a result, the IIoT is vulnerable to kinds of attacks, including physical attacks (such as the invasive hardware attacks, side-channel attacks and reverse-engineering attacks), malicious code (such as Trojans, viruses and runtime attacks), and other attacks (such as phishing and sabotage). To ensure the security and privacy of the IIoT, many countermeasures have been proposed, a non-exhaustive list includes authentication techniques, secure routing techniques, intrusion detection techniques, signature techniques, and key establishment techniques. As a fundamental countermeasure, key establishment has been extensively and intensively studied. In this chapter, we will present a survey and taxonomy of the key establishment protocols. Specifically, we will review the conventional key establishment protocols which are designed at higher layers and the physical layer. By reviewing the conventional key establishment protocols, we aim to illustrate the necessity of designing cross-layer key establishment protocols for the IIoT. Then, we will provide the detailed review of cross-layer key establishment protocols. The review illustrates that, the cross-layer design enables the IIoT devices to establish communication keys without the trusted entity and the secret sharing assumption. At the end of this chapter, we will provide a conclusion and point out some future research trends of the IIoT.

Yuexin Zhang, Xinyi Huang

Application Scenarios

Frontmatter

IIoT in the Hospital Scenario: Hospital 4.0, Blockchain and Robust Data Management

Abstract

The Industrial Internet of Things (IIoT) consists of the pervasive application of the IoT paradigm in conjunction with analytics and artificial intelligence (AI) in industrial scenarios. Industry 4.0 (I4.0) extends further the IIoT model with the inclusion of robotics and automation, whereas Hospital 4.0 (H4.0) is the application of the I4.0 paradigm to the healthcare sector. H4.0 relies on cyber-physical systems managing several devices and software components. and the exchange of a huge amount of sensible data that includes medical records. Medical records can be much more valuable to criminals than financial data, indeed the control of medical data allows criminals to plan and realize different frauds, that the victims may identify only too late. Furthermore, the complexity of a typical H4.0 cyber-physical system makes healthcare records particularly vulnerable. Blockchain is today an emerging technology for the management of data that may avoid or mitigate the impact of threats related to data storage and management, in general, and to the administration, in particular, of healthcare records. The blockchain technology relies on cryptography and distributed consensus to guarantee data integrity, accountability and security. The exploitation of such technology is considered in this chapter, showing the advantages when used in a H4.0 scenario.

Luca Faramondi, Gabriele Oliva, Roberto Setola, Luca Vollero

Design and Realization of Testbeds for Security Research in the Industrial Internet of Things

Abstract

Research on the (cyber) security of industrial control systems requires holistic understanding of practical systems in the field. In particular, important differences to IT security scenarios are related to industrial networking protocols and programming languages such as ladder logic. Arguably, access to realistic testbeds with physical process and related controls would enable researchers to understand the scenarios better, to develop attacks, and test countermeasures. While the implementation of such testbeds presents significant investments and efforts, the implementation process itself is often not discussed in literature. In this chapter, we discuss the design and realization of such industrial control system testbeds for security research. In particular, we discuss a process in which testbeds are designed by security researchers to resemble existing (and future) plants, and are then implemented by commercial system integrators using industry’s best practises. As use cases, we provide details on design decisions, cost, and outcomes for three testbeds established at the Singapore University of Technology and Design.

Nils Ole Tippenhauer

Titel: Security and Privacy Trends in the Industrial Internet of Things
herausgegeben von: Prof. Cristina Alcaraz
Verlag: Springer International Publishing
Electronic ISBN: 978-3-030-12330-7
Print ISBN: 978-3-030-12329-1
DOI: https://doi.org/10.1007/978-3-030-12330-7