Monitoring the health and integrity of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) will play a major role in the Internet of Things collecting the data that will support decision-making and enable the automation of many applications. Nevertheless, the introduction of these devices into our daily life raises serious concerns about their integrity. Therefore, at any given point, one must be able to tell whether or not a node has been compromised. Moreover, it is crucial to understand how the compromise of a particular node or set of nodes may affect the network operation. In this thesis, we present a framework to monitor the health and integrity of WSNs that allows us to detect compromised devices and comprehend how they might impact a network’s performance. We start by investigating the use of attestation to identify malicious nodes and advance the state of the art by exploring limitations of existing mechanisms. Firstly, we tackle effectiveness and scalability by combining attestation with measurements inspection and show that the right combination of both schemes can achieve high accuracy whilst significantly reducing power consumption. Secondly, we propose a novel stochastic software-based attestation approach that relaxes a fundamental and yet overlooked assumption made in the literature significantly reducing time and energy consumption while improving the detection rate of honest devices. Lastly, we propose a mathematical model to represent the health of a WSN according to its abilities to perform its functions. Our model combines the knowledge regarding compromised nodes with additional information that quantifies the importance of each node. In this context, we propose a new centrality measure and analyse how well existing metrics can rank the importance each sensor node has on the network connectivity. We demonstrate that while no measure is invariably better, our proposed metric outperforms the others in the vast majority of cases.Open Acces

Ensuring the resilience of wireless sensor networks to malicious data injections through measurements inspection

Malicious data injections pose a severe threat to the systems based on \emph{Wireless Sensor Networks} (WSNs) since they give the attacker control over the measurements, and on the system's status and response in turn. Malicious measurements are particularly threatening when used to spoof or mask events of interest, thus eliciting or preventing desirable responses. Spoofing and masking attacks are particularly difficult to detect since they depict plausible behaviours, especially if multiple sensors have been compromised and \emph{collude} to inject a coherent set of malicious measurements. Previous work has tackled the problem through \emph{measurements inspection}, which analyses the inter-measurements correlations induced by the physical phenomena. However, these techniques consider simplistic attacks and are not robust to collusion. Moreover, they assume highly predictable patterns in the measurements distribution, which are invalidated by the unpredictability of events. We design a set of techniques that effectively \emph{detect} malicious data injections in the presence of sophisticated collusion strategies, when one or more events manifest. Moreover, we build a methodology to \emph{characterise} the likely compromised sensors. We also design \emph{diagnosis} criteria that allow us to distinguish anomalies arising from malicious interference and faults. In contrast with previous work, we test the robustness of our methodology with automated and sophisticated attacks, where the attacker aims to evade detection. We conclude that our approach outperforms state-of-the-art approaches. Moreover, we estimate quantitatively the WSN degree of resilience and provide a methodology to give a WSN owner an assured degree of resilience by automatically designing the WSN deployment. To deal also with the extreme scenario where the attacker has compromised most of the WSN, we propose a combination with \emph{software attestation techniques}, which are more reliable when malicious data is originated by a compromised software, but also more expensive, and achieve an excellent trade-off between cost and resilience.Open Acces

Distributed IoT Attestation via Blockchain (Extended Version)

The growing number and nature of Internet of Things (IoT) devices makes these resource-constrained appliances particularly vulnerable and increasingly impactful in their exploitation. Current estimates for the number of connected things commonly reach the tens of billions. The low-cost and limited computational strength of these devices can preclude security features. Additionally, economic forces and a lack of industry expertise in security often contribute to a rush to market with minimal consideration for security implications. It is essential that users of these emerging technologies, from consumers to IT professionals, be able to establish and retain trust in the multitude of diverse and pervasive compute devices that are ever more responsible for our critical infrastructure and personal information. Remote attestation is a well-known technique for building such trust between devices. In standard implementations, a potentially untrustworthy prover attests, using public key infrastructure, to a verifier about its configuration or properties of its current state. Attestation is often performed on an ad hoc basis with little concern for historicity. However, controls and sensors manufactured for the Industrial IoT (IIoT) may be expected to operate for decades. Even in the consumer market, so-called smart things can be expected to outlive their manufacturers. This longevity combined with limited software or firmware patching creates an ideal environment for long-lived zero-day vulnerabilities. Knowing both if a device is vulnerable and if so when it became vulnerable is a management nightmare as IoT deployments scale. For network connected machines, with access to sensitive information and real-world physical controls, maintaining some sense of a device\u27s lifecycle would be insightful. In this paper, we propose a novel attestation architecture, DAN: a distributed attestation network, utilizing blockchain to store and share device information. We present the design of this new attestation architecture, and describe a virtualized simulation, as well as a prototype system chosen to emulate an IoT deployment with a network of Raspberry Pi, Infineon TPMs, and a Hyperledger Fabric blockchain. We discuss the implications and potential challenges of such a network for various applications such as identity management, intrusion detection, forensic audits, and regulatory certification

Detecting Compromised Nodes in Wireless Sensor Networks

While wireless sensor networks are proving to be a versatile tool, many of the applications in which they are utilized have sensitive data. Therefore, security is crucial in many of these applications. Once a sensor node has been compromised, the security of the network degrades quickly if measures are not taken to deal with this event. There have been many approaches researched to tackle the issue. In this thesis, an anomaly-based intrusion detection protocol is developed to detect compromised nodes in wireless sensor networks. The proposed protocol is implemented after the sensors are deployed into the environment in which they will be used. They will start to learn the normal behavior of each of their neighbors with whom they communicate. All legitimate sensor nodes have the same code running on them. A compromised node that is present in the network is assumed to have different code running on it in order to cause some form of damage to the network. These malicious nodes are detected when one of its neighboring nodes identifies its behavior as deviating from what is expected, or in other words an anomaly. The base station is then contacted to confirm whether the suspected node is in fact compromised. If the base station concludes that the node is compromised, the rest of the network will be informed, and the appropriate actions will be taken. One of the unique features of the algorithm is that it is not only capable of sustaining security in wireless sensor networks, but handling the computing restraints as well as other limitations characteristic of these systems. Extensive simulations are performed to verify the algorithm designed

A survey on cyber security for smart grid communications

A smart grid is a new form of electricity network with high fidelity power-flow control, self-healing, and energy reliability and energy security using digital communications and control technology. To upgrade an existing power grid into a smart grid, it requires significant dependence on intelligent and secure communication infrastructures. It requires security frameworks for distributed communications, pervasive computing and sensing technologies in smart grid. However, as many of the communication technologies currently recommended to use by a smart grid is vulnerable in cyber security, it could lead to unreliable system operations, causing unnecessary expenditure, even consequential disaster to both utilities and consumers. In this paper, we summarize the cyber security requirements and the possible vulnerabilities in smart grid communications and survey the current solutions on cyber security for smart grid communications. © 2012 IEEE