Our research is to apply simulation methodologies in the analysis of blockchain with focus on vulnerability and risk assessment. Specifically,
- Conduct a thorough literature review of the simulation modeling and statistical analysis of blockchain.
Build a series of simulation models (discrete-event and agent based). We plan to apply the agent-based simulation modeling of the blockchain to conduct sensitivity analysis and risk assessment. Specifically,
- Identify metrics to measure the performance of blockchain.
- Introduce systematic stochastic components to test the vulnerability and volatility of the system.
- Using the simulation model to benchmark the performance of emerging blockchain-based system performance and build a standard similar to S&P. There will be a huge impact of this work, which requires that the simulation models be updated in real time.
Blockchain for IoT / supply chain
The Internet of Things (IoT) is a fast-growing industry destined to transform homes, cities, farms, factories, and practically everything else by making them smart and more efficient. It will be very challenging for the current infrastructure and architecture underlying the Internet and online services to support huge IoT ecosystems of the future. Blockchain technology, on the other hand, will enable the creation of secure mesh networks, where IoT devices will interconnect in a reliable way while avoiding threats such as device spoofing and impersonation. Our research plan on this topic includes:
- Conduct a thorough literature review of IoT and blockchain.
- Study the impact of block technology on IoT and Supply Chain Management as blockchain settles security, privacy, and reliability concerns in the these areas. Specifically, we plan to study blockchain technology under different market structures and game structures to test how and when blockchain technology can be useful.
Blockchain for big data and AI
Blockchain technology, in essence, is database. It has the potential to change the way that the world approaches big data, with enhanced security and data quality just two of the benefits afforded to businesses. Our research on this topic will focus on the following two tracks
- Edge computing. The decentralized nature of blockchain calls for new AI protocol as traditional AI methods focus on model training in a centralized manner. Edge computing, on the other hand, utilizes the nodes distributed over the blockchain to compute and train the AI model.
- Real-Time Analytics. Real-time fraud detection has only been a pipe dream and banking institutions have always relied on using technologies to identify fraudulent transactions retrospectively. Since the blockchain has a database record for every single transaction, it provides a way for institutions to mine for patterns in real-time, if need be.