Digital Twins and Self-sovereign Identity:
Building next-generation emulation with privacy preservation
The rise of advanced analytics, machine learning (ML) / artificial intelligence (AI), and the Internet of Things (IoT) has made possible digital twin simulation. Digital twins are virtual digital models of physical entities that are used to experiment and ultimately make better decisions for the real world things being emulated. The digital models are usually dependent on sensors and include two-way interaction with the physical system.
The growth of smart IoT devices—those with an increasing amount of processing capability—has resulted in more use cases where devices enact complex and independent functions. These devices must both provide cryptographic trust to participate in data exchange and be assured they can trust the network and nodes with which they communicate. Managing IoT devices and user identities, as well as the relationships among various devices and their digital twins, involves significant challenges. A lack of Identity Credential and Access Management (ICAM) standards for IoT causes proprietary standards and a lack of interoperability. The world needs a digital trust framework, decentralized architecture, and decentralized identity. In addition, especially in industries such as healthcare, digital twins encounter volumes of sensitive data regulated for privacy. Both the digital twin and the person whose data is being used would greatly benefit from a privacy-preserving data-protection capability afforded by decentralized identity.
Join this session to learn about:
- The IoT and healthcare digital twin landscape
- Challenges of digital identity and ICAM in IoT and digital twins
- How to apply decentralized identity
- How TIBCO and LFPH is advancing SSI in IoT for industry use