Internet-of-Things (IoT) systems play critical roles in supporting diverse vertical applications by connecting massive heterogeneous devices, machines, and industrial processes. Any potential security risk in IoT systems could lead to catastrophic consequences and even system failure of critical infrastructures, particularly for applications relying on tight collaborations among distributed devices and facilities. While security is the cornerstone for many IoT applications, trust among entities and data analytics are becoming increasingly important to effectively support future IoT systems. Existing solutions often feature various distinctive weaknesses, including drastically increased time latency and communication/ computation overheads, which are extremely undesirable for delay-sensitive and resource- constrained IoT communications. Those isolated designs for a specific network, application, or a certain layer of protocol stacks treat network contexts separately as well, leading to low efficiency, robustness, and effectiveness.
To overcome the above difficulties, this talk will provide a collaborative perspective for secure and trustworthy communications as well as efficient data analytics by intelligently exploring the interactions of network contexts, communication process, and devices involved in the tasks. I will first present some results on intelligent security provision in IoT systems and graph signal processing-based IoT data analytics. Afterwards, I will briefly discuss scope for future research, including autonomous communication process-based security, trustworthy collaboration intelligence, and data analytics-oriented intelligent IoT systems.