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

Code Integrity Attestation for PLCs using Black Box Neural Network Predictions

Cyber-physical systems (CPSs) are widespread in critical domains, and significant damage can be caused if an attacker is able to modify the code of their programmable logic controllers (PLCs). Unfortunately, traditional techniques for attesting code integrity (i.e. verifying that it has not been modified) rely on firmware access or roots-of-trust, neither of which proprietary or legacy PLCs are likely to provide. In this paper, we propose a practical code integrity checking solution based on privacy-preserving black box models that instead attest the input/output behaviour of PLC programs. Using faithful offline copies of the PLC programs, we identify their most important inputs through an information flow analysis, execute them on multiple combinations to collect data, then train neural networks able to predict PLC outputs (i.e. actuator commands) from their inputs. By exploiting the black box nature of the model, our solution maintains the privacy of the original PLC code and does not assume that attackers are unaware of its presence. The trust instead comes from the fact that it is extremely hard to attack the PLC code and neural networks at the same time and with consistent outcomes. We evaluated our approach on a modern six-stage water treatment plant testbed, finding that it could predict actuator states from PLC inputs with near-100% accuracy, and thus could detect all 120 effective code mutations that we subjected the PLCs to. Finally, we found that it is not practically possible to simultaneously modify the PLC code and apply discreet adversarial noise to our attesters in a way that leads to consistent (mis-)predictions.Comment: Accepted by the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

Investigating Security for Ubiquitous Sensor Networks

The availability of powerful and sensor-enabled mobile and Internet-connected devices have enabled the advent of the ubiquitous sensor network paradigm which is providing various types of solutions to the community and the individual user in various sectors including environmental monitoring, entertainment, transportation, security, and healthcare. We explore and compare the features of wireless sensor networks and ubiquitous sensor networks and based on the differences between these two types of systems, we classify the security-related challenges of ubiquitous sensor networks. We identify and discuss solutions available to address these challenges. Finally, we briefly discuss open challenges that need to be addressed to design more secure ubiquitous sensor networks in the future