Reza Soltani

Reza Soltani, Uyen Trang Nguyen, Aijun An

In this paper, we introduce a data capsule model, a self-contained and self-enforcing data container based on emerging self-sovereign identity standards, blockchain, and attribute-based encryption. A data capsule allows for a transparent, privacy-respecting, and secure exchange of personal data, enabling a progressive trust scheme in a semi-trusted environment. Each data capsule is bundled with its own access policy structure and verifiable data, drastically reducing the number of interactions needed among the user, the service providers, and data custodians. Moreover, by relying on the decentralized nature of blockchain and attribute-based encryption our proposed model ensures the access policies published by service providers are public, transparent, and strictly followed.

Reza Soltani, Uyen Trang Nguyen, Aijun An

Self-sovereign identity is the next evolution of identity management models. This survey takes a journey through the origin of identity, defining digital identity and progressive iterations of digital identity models leading up to self-sovereign identity. It then states the relevant research initiatives, platforms, projects, and regulatory frameworks, as well as the building blocks including decentralized identifiers, verifiable credentials, distributed ledger, and various privacy engineering protocols. Finally, the survey provides an overview of the key challenges and research opportunities around self-sovereign identity.

Reza Soltani, Eun-Young Kang, Juan Esteban Heredia Mena

Optimizing CPS behavior in terms of energy consumption can have a significant impact on system reliability. The environment influences the system's behavior, and neglecting the environmental behavior has an indirect negative impact on optimizing the system's behavior. In this work, to increase the system's flexibility, the behavior of the environment is modeled dynamically to apply the disorderliness of its behavior. The resulting models are formally verified. By examining the past environmental behavior and predicting its future behavior, energy optimization is done more dynamically. The verification results acquired using a UPPAAL-SMC show that the optimization of system behavior by predicting the environmental behavior has been successful. Our approach is demonstrated using a case study within an I4 setting.