How Secure Is Your IoT Network?

The proliferation of IoT devices in smart homes, hospitals, and enterprise networks is widespread and continuing to increase in a superlinear manner. With this unprecedented growth, how can one assess the security of an IoT network holistically? In this article, we explore two dimensions of security assessment, using vulnerability information of IoT devices and their underlying components ($\textit{compositional security scores}$) and SIEM logs captured from the communications and operations of such devices in a network ($\textit{dynamic activity metrics}$) to propose the notion of an $\textit{attack circuit}$. These measures are used to evaluate the security of IoT devices and the overall IoT network, demonstrating the effectiveness of attack circuits as practical tools for computing security metrics (exploitability, impact, and risk to confidentiality, integrity, and availability) of heterogeneous networks. We propose methods for generating attack circuits with input/output pairs constructed from CVEs using natural language processing (NLP) and with weights computed using standard security scoring procedures, as well as efficient optimization methods for evaluating attack circuits. Our system provides insight into possible attack paths an adversary may utilize based on their exploitability, impact, or overall risk. We have performed experiments on IoT networks to demonstrate the efficacy of the proposed techniques.Comment: IEEE International Congress on Internet of Thing

Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids

Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart grids, cybersecurity of IoT is paramount. To this end, use of cryptographic security methods is prevalent in existing IoT. Non-cryptographic methods such as radio frequency fingerprinting (RFF) have been on the horizon for a few decades but are limited to academic research or military interest. RFF is a physical layer security feature that leverages hardware impairments in radios of IoT devices for classification and rogue device detection. The article discusses the potential of RFF in wireless communication of IoT devices to augment the cybersecurity of smart grids. The characteristics of a deep learning (DL)-aided RFF system are presented. Subsequently, a deployment framework of RFF for smart grids is presented with implementation and regulatory aspects. The article culminates with a discussion of existing challenges and potential research directions for maturation of RFF.publishedVersio

A Design Approach to IoT Endpoint Security for Production Machinery Monitoring

The Internet of Things (IoT) has significant potential in upgrading legacy production machinery with monitoring capabilities to unlock new capabilities and bring economic benefits. However, the introduction of IoT at the shop floor layer exposes it to additional security risks with potentially significant adverse operational impact. This article addresses such fundamental new risks at their root by introducing a novel endpoint security-by-design approach. The approach is implemented on a widely applicable production-machinery-monitoring application by introducing real-time adaptation features for IoT device security through subsystem isolation and a dedicated lightweight authentication protocol. This paper establishes a novel viewpoint for the understanding of IoT endpoint security risks and relevant mitigation strategies and opens a new space of risk-averse designs that enable IoT benefits, while shielding operational integrity in industrial environments

The industrial internet of things (IIoT) : an analysis framework

Historically, Industrial Automation and Control Systems (IACS) were largely isolated from conventional digital networks such as enterprise ICT environments. Where connectivity was required, a zoned architecture was adopted, with firewalls and/or demilitarized zones used to protect the core control system components. The adoption and deployment of ‘Internet of Things’ (IoT) technologies is leading to architectural changes to IACS, including greater connectivity to industrial systems. This paper reviews what is meant by Industrial IoT (IIoT) and relationships to concepts such as cyber-physical systems and Industry 4.0. The paper develops a definition of IIoT and analyses related partial IoT taxonomies. It develops an analysis framework for IIoT that can be used to enumerate and characterise IIoT devices when studying system architectures and analysing security threats and vulnerabilities. The paper concludes by identifying some gaps in the literature

A Vulnerability Management Solution for constrained IoT devices with a Trusted Execution Environment using a Hardware Root of Trust

The popularity and prevalence of Internet of Things (IoT) devices has been ever increasing. They have found their way into our everyday lives and increasingly transform our living environments into smart homes. However, most of these constrained devices do not possess sufficient computational power, memory, and battery runtime in order to implement security features that are common for general purpose personal computers. Hence, the increasing numbers of interconnected consumer IoT devices are followed by an increase of their attack surface and vulnerabilities. The following thesis approaches this security issue by providing a novel approach for a Runtime IoT Security Score that provides the inexperienced user of a smart home system with profound insight into the security state of the connected IoT devices during runtime. This is achieved by combining Vulnerability Assessment with Trustworthiness Assessment of the connected devices, which has never been proposed before and represents a very valuable contribution to the state of current research. In addition to the Runtime Security Score, a holistic concept for a Vulnerability Assessment and Management (VAM) solution is proposed as another main contribution of this thesis. The effective and functional interoperability of all relevant components specified in this concept is shown with a Proof of Concept implementation.Die Popularität und Verbreitung von Geräten des Internets der Dinge (engl.~Internet of Things, IoT) nimmt ständig zu. Sie haben Einzug in unser tägliches Leben gehalten und verwandeln unsere Wohnumgebung zunehmend in ein intelligentes Zuhause. Die meisten dieser eingeschränkten Geräte verfügen jedoch nicht über genügend Rechenleistung, Speicher und Akkulaufzeit, um Sicherheitsfunktionen zu implementieren, die für allgemeine Personal Computer üblich sind. Mit der zunehmenden Zahl der vernetzten IoT-Geräte für Verbraucher steigen daher auch deren Angriffsfläche und Schwachstellen. Die vorliegende Arbeit widmet sich diesem Sicherheitsproblem, indem sie einen neuartigen Ansatz für einen Runtime IoT Security Score vorstellt, der dem unerfahrenen Benutzer eines Smart-Home-Systems einen tiefen Einblick in den Sicherheitszustand der angeschlossenen IoT-Geräte zur Laufzeit gibt. Dies wird durch die Kombination von Vulnerability Assessment mit einer Bewertung der Vertrauenswürdigkeit der angeschlossenen Geräte erreicht. Dies stellt einen neuartigen Ansatz darf und leistet damit einen sehr wertvollen Beitrag zum aktuellen Stand der Forschung. Neben dem Runtime Security Score wird als weiterer wichtiger Beitrag dieser Arbeit ein ganzheitliches Konzept für eine Vulnerability Assessment and Management (VAM) Lösung vorgeschlagen. Die effektive und funktionale Interoperabilität aller relevanten Komponenten, die in diesem Konzept spezifiziert sind, wird mit einer Proof of Concept Implementierung gezeigt

A review of cyber-ranges and test-beds:current and future trends

Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable environments that necessitate more diligent management. The rapid proliferation in the automation of cyber-attacks is reducing the gap between information and operational technologies and the need to review the current levels of robustness against new sophisticated cyber-attacks, trends, technologies and mitigation countermeasures has become pressing. A deeper characterisation is also the basis with which to predict future vulnerabilities in turn guiding the most appropriate deployment technologies. Thus, refreshing established practices and the scope of the training to support the decision making of users and operators. The foundation of the training provision is the use of Cyber-Ranges (CRs) and Test-Beds (TBs), platforms/tools that help inculcate a deeper understanding of the evolution of an attack and the methodology to deploy the most impactful countermeasures to arrest breaches. In this paper, an evaluation of documented CR and TB platforms is evaluated. CRs and TBs are segmented by type, technology, threat scenarios, applications and the scope of attainable training. To enrich the analysis of documented CR and TB research and cap the study, a taxonomy is developed to provide a broader comprehension of the future of CRs and TBs. The taxonomy elaborates on the CRs/TBs dimensions, as well as, highlighting a diminishing differentiation between application areas