The research center carries out cutting-edge fundamental research to devise rigorous concepts, methods, and tools for the systematic construction of a dependable IoT that is resilient against failures and attacks. These methods will allow us to make quantitative predictions and guarantees about the level of dependability offered in adverse environments. The methods will be implemented in tools and prototypes: examples are hardware prototypes of adaptive RF front-ends, security-aware computing platforms and operating systems, protocols for dependable communication and localization, and tools for verification of protocols among composed smart items.
The seed of the research center is the LEAD project “Dependable Internet of Things in Adverse Environments” that is funded through an excellence initiative sponsored by TU Graz to foster excellent research areas of strategic importance. The LEAD project is intended to run for three years and can be extended by another three years after successful evaluation (see more).
The LEAD project will devise methods and tools to predict, guarantee, and ultimately raise the level of dependability of the IoT. The project is structured around the four subprojects summarized below which tackle the vulnerability of IoT systems to harsh environmental conditions and to physical and remote attacks, as well as the increasing complexity of IoT systems, where many devices cooperate using a dynamically changing communication network.
Wireless technologies suffer from physical and man-made impairments, e.g., multipath propagation and interferences from competing transmissions, as well as from the effect of temperature variations and other environmental properties. This impairs the accuracy, latency, loss, and energy consumption of wireless services. Our key objective is to offer statistical guarantees on the reliability and availability of correct wireless localization and communication by automatically adapting system parameters using models of the transceiver hardware and the environment.
A central requirement of tomorrow’s IoT is the ability to execute software dependably on all kinds of devices. Dependable software execution in particular means that operations are completed within guaranteed response times (availability), the software is not altered due to environmental perturbation or deliberate attacks (integrity), and secret information is not revealed via physical side-channels or via communication interfaces (confidentiality). Our key objective is to research methods in hardware and software that allow to make software execution dependable in the IoT setting of physical attacks and that address the inherent complexity of mixed-criticality real-time applications as well as the fact that the software on IoT devices has to be modular and changes dynamically during system lifetime.
In the IoT, Smart Things collaborate to provide a service. The type and number of devices involved in such collaboration is typically unknown at design time. Hence, even if the individual devices are dependable by themselves, their composition may suffer from bugs in communication protocols, but also from malicious or faulty third parties that participate in the collaboration. Our key objective is to build systematic methods and a tool to ascertain (1) whether systems employed in the IoT are able to interact with an adverse environment, and (2) whether the composition of individually correct components acts correctly. We will focus on techniques that provide (statistical) guarantees for the dependability of the communication protocols and help in designing them systematically under realistic and practical assumptions
Communication between smart items is prone to errors and likely to be corrupted by unpredictable distortions and losses. The topology of feedback loops might change abruptly due to loss of connection between items. These phenomena are inherent to the Internet of Things which motivates the need for innovative robust methods for the design of networked control systems. Our key objective is to answer the question how to provide guarantees on the control performance such as stability and convergence despite harsh environments and physical attacks.