KYoT: Self-sovereign IoT Identification with a Physically Unclonable Function

The integration of Internet-of-Things (IoT) and Blockchains (BC) for trusted and decentralized approaches enabled modern use cases, such as supply chain tracing, smart cities, and IoT data marketplaces. For these it is essential to identify reliably IoT devices, since the producer-consumer trust is not guaranteed by a Trusted Third Party (TTP). Therefore, this work proposes a Know Your IoT device platform (KYoT), which enables the self-sovereign identification of IoT devices on the Ethereum BC. KYoT permits manufacturers and device owners to register and verify IoT devices in a self-sovereign fashion, while data storage security is ensured. KYoT deploys an SRAM-based (Static Random Access Memory) Physically Unclonable Function (PUF), which takes advantage of the manufacturing variability of devices’ SRAM chips to derive a unique identifying key for each IoT device. The self-sovereign identification mechanism introduced is based on the ERC 734 and ERC 735 Ethereum identity standards

Bow-tie structure of the Polkadot transfer network

While there are many data collection and analysis tools for Ethereum - the largest smart contract blockchain by market capitalization, development of similar tools for other smart contract blockchains is lacking. Reasons for this are non-existent standards, changing specifications d ue t o rapid development, common usage of the off-chain storage, and lack of developers. One of such blockchains is Polkadot - a layer- zero blockchain featuring a single relay chain whose role is to secure smart contract transactions on multiple other parachains. In this paper we describe a data collection pipeline for Polkadot blockchain that we then use to perform an analysis of the bow-tie structure of its transfer network over time, with special emphasis on the role of nominators and validators in this structure. We find evidence that t he Polkadot ecosystem iss lowly maturing from a system dominated by nominators and validators, both of which require some technical skill as well as willingness to bond sufficient amount of funds, into a system increasingly populated by regular users using the financial services of Polkadot

Experimental study of turbulent jet and lifted jet flame unsteadiness from a non-linear dynamics perspective

This research aims to investigate the nonlinear dynamics of the non-reacting jets and non-premixed lifted jet flames. The goal is to understand better how the flow system dynamics change over time and identify the path toward unwanted conditions such as flashback, extinction, or blowout to limit combustors' dynamical failure. The existence of these undesirable conditions is bound to the fluid's history, meaning that initiated perturbation may persist in the system for time scales comparable to large-scale flow timescales. Hence, the notion is to utilize jet and jet flames as a study test case to work out how the flow evolves dynamically with the hope of understanding how to limit occurrences of the chaotic unwanted condition. Initially, planar particle image velocimetry has been used for the development of the methodologies. I have used planar data to investigate the nonlinear dynamics of non-reacting turbulent jets, with a low-to-moderate Reynolds number using the single-trajectory framework and ensemble framework. I have used Lyapunov exponents to calculate the spectra of scaling indices of the attractor. Then, I used Lagrangian Coherent Structures (LCSs), which are defined as manifolds that are locally Euclidean and invariant, to study the relationship between Lyapunov exponent changes with flow topological features. These LCSs behave as hypersurfaces with maximally repelling or attracting properties. These various methodologies were used to investigate flame-turbulence interaction in lifted jet flames. The Lagrangian framework is shown to be effective at revealing the kinematics associated with flame-turbulence interaction. The LCSs' time history represents how eddy structures interact with the flame and highlight their role in the dynamics of the lifted jet flames. Finally, I have investigated the flame and turbulence interaction using high-speed luminosity imaging and simultaneous three-dimensional particle image velocimetry. The three-dimensional Lagrangian structures provide us a more detailed flow-flame interaction. It is shown that the flow features associated with attracting LCSs can create a barrier attracting the flame that makes the flame move upstream. In contrast, the presence of repelling LCSs near stationary flames breaks the balance between the gas velocity and flame propagation speed, causing the flame to become non-stationary and move downstream. It was also found that the repelling LCSs induce negative curvature on the flame surface whereas pushing the flame toward the products. However, the attracting LCSs induce positive curvature on the flame surface and draws the flame toward the reactantsAerospace Engineerin

ITrade: A Blockchain-based, Self-Sovereign, and Scalable Marketplace for IoT Data Streams

In recent years, the interest grew in the Internet- of-Things (IoT) and Blockchain (BC) integration for additional trust and decentralization. This opened potentials in various use cases, such as supply chain tracing, smart cities, and recently IoT data marketplaces. Therefore, this paper presents the de- sign, implementation, and evaluation of the BC-based IoT data trading platform “ITrade". ITrade proposes a highly scalable microservice-based architecture based on clouds. ITrade enables end-to-end data streaming from IoT devices toward data buyers. The Smart Contract (SC)-oriented design of ITrade enables decentralized management of autonomous and distributed IoT data trading. ITrade evaluations attest its scalability as a reliable peer-to-peer data transmission platform

DLIT: A Scalable Distributed Ledger for IoT Data

The integration of the Internet-of-Things (IoT) and Blockchain (BC) for strong trust and decentralization shows potentials in use cases, such as supply chain tracing, smart cities, and health care. As a great number of IoT devices interacting in such cases, it is crucial to provide scalable and secure mechanisms for IoT data persistence within BCs. In this regard, sharding mechanisms have been employed to enhance the scalability of BCs. However, disconnections and delays of a BC’s distributed network can cause concerns for inter-shard and inter-miner synchronizations, eventually preventing the BC from reaching a high throughput. Thus, this work develops an IoT-oriented permissioned BC, which covers via a scalable Distributed Ledger (DL) a novel sharding mechanism for unstable distributed networks. Therefore, DLIT (Distributed Ledger for IoT Data) offers a novel two-layered transaction distribution, validation, and inter-shard synchronization, combined with authentication and verification mechanisms in support of a viable security level