ASU Blockchain Research Initiatives
Peer to Peer Energy Trading
The United States electrical grid outdated, legacy systems are inefficient, vulnerable to attack and impractical in our growing digital age. Furthermore, the energy production landscape is being reshaped by distributed energy resources (DERs) remotely controllable items part of the Internet of Things (IoT). DERs in the form of photovoltaic panels, electric vehicles, smart appliances, and battery storage systems are great examples of some of the technologies revolutionizing our energy dependent world. When used intelligently, these DERs can reduce cost, improve reliability, and integrate renewable resources in the electric grid.
Stakeholders of the healthcare industry are operating in the technological stone age. Insurance providers rely on outdated medical data, clinics communicate inefficiently, and in turn, patients receive inadequate service. As other industries adopt technologies to make practices more efficient, healthcare has been forgotten and effectively left in the dust.
MedFabric4Me provides a simple, yet effective blockchain based solution to mitigate the drawbacks of this broken system and build a healthcare environment that supports patient-centered data integrity and security. By utilizing the technology presented byMedFabric4Me we can provide better record management for patients, faster emergency response times, and improved security of sensitive information.
Blockchain technology, although revolutionary in principle is not without it’s set of challenges in practice. At our current state, these blockchain networks have propagation methods that result in bottlenecks leading to high latency and more frequent orphaned blocks. High latency meaning long delays in network transmission, and orphaned blocks referring to blocks that have failed to propagate to the network. These challenges create long delays in transactions, high bandwidth requirments, and opens the door for malicious activity.
The BLADE expedition proposal aims to eliminate the exploitation, misuse, and fraud of personal data online. Currently, internet users have zero control over their digital identity, they don’t have the ability to choose who has access to their data or for what purposes.
Through the use of blockchain supported secure Multi-Party Computation (MPC), this expedition hopes to solve some of these key issues contributing to the exploitation of personal data. This approach will allow for applications and computations to run directly on the network while guaranteeing the security and privacy of the end-users. Since the end user never loses control of their identity, companies can leverage data without the risk of fraudulent activity or personal exploitation.
BAAS IoT Solution
Making our data more valuable, our cities smarter, and our lives more connected than ever before, the Internet of Things (IoT) is rapidly accelerating the concept of global digital connectivity. Bridging the gap between the internet, and our physical lives, IoT is on it’s way to disrupting every company, industry, and market in the world. Although adoption is taking place, academic institutions, governments, and industry professionals must overcome some technical complications if they want their IoT systems running as efficiently, safely, and sustainably as envisioned. Some of these technical complications are as followed; IoT device resource constraints, data security, end-user privacy, lack of flexibility, and high cost paired with high latency which prevents sustainable growth.
Carbon Trading on a Blockchain
The motivation to go green has not only increasingly become part of many company’s corporate social responsibilities, but also as an aspect of remaining relevant in the future business environment. Besides, there are more and more environmental concerns that can only be addressed through green initiatives in terms of production, servicing and manufacturing.
Companies are therefore seeking more innovative methods of promoting eco-friendly environments by integrating green practices in their business functions. Carbon offsetting is one such process that companies use to reduce their carbon emissions. A Carbon offset is a way to compensate for your emissions by funding an equivalent carbon dioxide saving elsewhere. Everyday actions of a company consume energy and produce carbon emissions, such as driving, flying and heating buildings. Carbon offsetting is used to balance out these emissions by helping to pay for emission savings in other parts of the world.
Smart Contract Insurance
Principal Investigator Petar Jevtic, and Associate Professor Nicolas Lanchier make up the team of researchers on the ASU Smart Contract Insurance Project. An initiative funded by the Arizona State University Center for Assured and Scalable Data Engineering, and in partnership with the ASU School of Mathematical and Statistical Sciences. Petar Jevtic has a background in developing and using tools from actuarial sciences and mathematical finance to assess and manage risks in insurance and finance. Nicolas Lanchier, having received his Ph.D. in probability theory, uses his research experience to explore how the geometric patterns of random structures affect contagion on systems. Recently, the team issued a patent application with the United States Patent and Trademark Office on the research “Systems and methods for a simulation program of percolation model for the loss distribution caused by a cyber attack.” Now, with their proprietary knowledge secure, their research is in full swing as they look to map out the financial risks associated with smart contracts and their liability.
Satoshi Nakamoto created the world’s first Nakamoto network called Bitcoin. Since that fateful day on January 3rd, 2009 the question “How big can this actually scale?” has been asked by supports and speculators alike. The Arizona State University Blockchain Research Lab was funded by the Dash Treasury Fund almost a year ago to answer that same question. Dragan Boscovic, Nakul Chawla, and Darren Tapp just published their white paper entitled “Block Propagation Applied to Nakamoto Networks” to answer two questions: How can the Dash network scale to support mass adoption? And what is the practical limit to Dash scaling?