Decentralized Zero-Trust IoT Data Infrastructure

Overview. This research initiative aims to create a decentralized zero-trust data infrastructure based on web 3.0 and blockchain principles. In this system, each data owner has the full control of his/her own data, and can grant/revoke the read/write access to anyone without a broker. All the data revisions and access records will be traceable and auditable. Below we describe the vision and design using the Internet of Things (IoT) as a study case, but the design principles may broadly apply to many applications and systems.

If the Internet is viewed as the world circulatory system enabling fast information sharing and exchanges, the Internet of Things (IoT) is envisioned to be the world neural system enabling autonomous sensing, intelligence and response. In biology, the neural system coordinates actions and sensory information by transmitting signals to and from different body parts and working in tandem with the endocrine system to respond to events. The biological neural system consists of two main parts, the central neural system (CNS) and the peripheral neural system (PNS). The CNS consists of the brain and spinal cord; the PNS consists mainly of nerves that connect the CNS to every other part of the body. The IoT system today, equivalent to PNS connecting sensors and actuators, is individually managed by isolated central/cloud servers of different organizations. Scalability, fault-tolerance, security and privacy are major challenges, and the interconnection of IoT systems needs a transformative approach. There lacks incentive and trust mechanism for different organizations to jointly build the IoT systems and share the data for larger benefits. For example, the pervasive Artificial Intelligence needs a large amount of data to learn and build. Blockchain technology sheds lights on the incentives of building trust and synergy among decentralized participants toward a bigger goal.


Figure 1. Decentralized Zero-Trust IoT Data Fabric. 

Inspired by the biological neural system, we propose to create a Web3 Neural System (WNS) connecting IoT based on web 3.0 and blockchain principles. Where Web 2.0 was driven by the advent of mobile, social and cloud, Web 3.0 is built largely on three new layers of technological innovation: edge computing, decentralised data networks and artificial intelligence (with the aid of security and privacy techniques). WNS is a secure, scalable and trustworthy data fabric consisting of BridgeNS, DataNS, ComNS and BlockNS. BridgeNS, as the bridge of IoT device/system and WNS, provides the data integrity and ownership protection through the data lifetime; DataNS and ComNS provide scalable data and computation management and interfaces; BlockNS incentivizes participation and builds trust through blockchain, smart contract and token award/penalty mechanisms. 

BridgeNS: Bridge of IoT and WNS. A BridgeNS connects an IoT device/system to WNS and creates signatures and privacy policies for ensuring the data integrity and ownership in DataNS and ComNS. BridgeNS can be a physical device or a software or both. BridgeNS will get rewarded as a miner in the B-Chain of BlockNS based on the proof of data delivery. BridgeNS can also implement cyber-security approaches (based on AI, firewall and zero-trust) to ensure the device, network and data integrity.

DataNS: Data Storage and Sharing. DataNS provides scalable, secure and auditable IoT data storage, sharing, search and access services. It may interconnect a variety of storage solutions, including the cloud storage and IPFS-based storage, to provide a simple unified storage and permission control interface to users. Users may interact with DataNS file browser, database browser, or terminal, just as if they interact with them in a computer. DataNS will get rewarded as a miner in the D-Chain of BlockNS based on the proof of data storage. We have built a prototype system called Web3DB.

ComNS: Data Analytics and Computation. ComNS provides a scalable, secure and auditable data analytics and computation environment. It may interconnect a variety of computing resources, including the cloud centers and personal computers, to provide a simple unified computing interface to users. Users can write and run a program in the ComNS as if it is in a single computer, while the programs may actually run in many computers of the Internet. ComNS will get rewarded as a miner in the C-Chain of BlockNS based on the proof of data computation.

BlockNS: Blockchain of WNS. BlockNS serves the distributed ledger for managing trust and assets, coordinating resources, smart contracts and consensus protocols. Tentatively, four chains make up its mainnet: the D-Chain (for DataNS), C-Chain (for ComNS), B-Chain (for BridgeNS) and A-Chain (for Admin). A-Chain manages the B, C and D chains, and each may have its own token assets and credit/reputation scores. Randomness and DAG may be adopted in consensus to maximize efficiency, not necessarily involving all participants all the time.

Zero-trust and Traceable Data Infrastructure for Health IoT Data Storage and Sharing

NSF-2312974, $600K, 2023-2026, PIs: Taeho Jung, WenZhan Song

Overview: Personal data, such as health IoT data, nowadays is possessed by service providers’ central data centers, and individuals do not have ultimate control over the data they produce. This is a growing concern due to the sensitive nature of such user-generated data. The proposed Web 3.0-based data infrastructure is an evolution of the current centralized data ecosystem, aiming to address some of its limitations and challenges. This project aims to build a zero-trust and traceable data-sharing ecosystem Web3DB, where data ownership and control are returned to the individuals who generate the data. In Web3DB, the data owners will be able to define the data access and sharing policy that will be enforced in a zero-trust manner, i.e., without relying on central coordinators or infrastructure. During such access control, users’ identities and credentials will always remain encrypted for their privacy. Access and usage of individuals? data will be logged securely such that only the data owners can monitor the access and usage of their data. Furthermore, this research will support the development of a diverse cohort of Ph.D., undergraduate, and high school students.

Underlying the proposed work is a novel zero-trust infrastructure for traceable data sharing. The project will entail research activities that result in (1) novel decentralized/self-sovereign identity management and access control with such decentralized identities in a zero-trust manner, (2) new theories and capabilities in the field of accountable data sharing as well as secure and privacy-preserving data auditing, and (3) new theories for optimizing distributed storage network and new understandings of the capacity of layer 2 blockchain extensions in the non-cryptocurrency blockchain. The research outcomes will be implemented and integrated into the prototype system of the Web 3.0 database the team has been building. Realistic simulations and real-world emulations will be conducted. The project outcomes include (1) open-source projects of Web3DB, a zero-trust traceable data sharing infrastructure, (2) an actively maintained and growing Web 3.0-based zero-trust data sharing ecosystem with multiple institutions, and (3) education materials for teaching and learning research components of Web3DB among undergraduate and high school students.

Faculty

WenZhan Song (UGA)
Taeho Jung (University of Norte Dame)
Haijian Sun(UGA)
Brad Phillips (UGA)

Students

Chenglin Miao

Qi Li
Soumya Pal
Jake Chandler
Darpan Shrivastava
Jane Odum
Aishwarya Pravin Lonarkar
Omkar Vishwanath Wagle