Research Projects

Project 1: Paradigm Shift from Vague Legal Contracts to Blockchain-based Smart Contracts

This project will continue my current research, and I will keep on addressing the open research problems regarding ambiguity and implementation issues of converting an ambiguous legal contract to a blockchain-based smart legal contract.

• Aim 1: Develop formal methodologies that consist of efficient models and algorithms that address current challenges in translating natural language contracts to smart legal contracts.
• Aim 2: Investigate and incorporate the Type-2 Fuzzy Logic and Decision Tree algorithms that help in decision-making for the selection of the most suitable interpretation from a set of ambiguous words and phrases.
• Aim 3: Explore on Contextual AI and NLP-based Fuzzy Logic and how it facilitates the automated generation of a realistic and feasible smart legal contract.
• Aim 4: Explore on how LLMs such as ChatGPT can be used to understand the vague legal contracts and rank the interpretations.

Project 2: Blockchain for Trusted Artificial Intelligence

As both Blockchain and Artificial Intelligence (AI) are two different popular technologies with two entirely different contributions, I plan to research how they both would complement each other, especially how Blockchain would benefit the integrity of the nodes, agents, models, and algorithms in artificial intelligence so that there is more trust and reliability in the decision-making process

• Aim 1: Explore how the smart contract, gas, and transaction costs can be optimized when AI is integrated with Blockchain, as transactions performed in Blockchain are already expensive.
• Aim 2: Analyze the potential of developing and designing the model where all components are on-chain when AI is integrated with Blockchain to ensure its integrity. Additionally, the feasibility of this model would also be studied thoroughly, as reaching the objective of efficiency and optimization is essential.
• Aim 3: Explore the limitations of existing consensus mechanisms through which consensus among the nodes is achieved in Blockchain and develop new consensus mechanisms that overcome the challenges of existing consensus mechanisms, such as the requirement of only a 51% vote for approval of a decision

Project 3: Data Cooperatives for Privacy and Security

Data Cooperatives are a novel area for secure data management which promises its users better protection and control of their personal data than the traditional way of their handling by the data collectors. Taking into account its advantages, I plan to research the development of the integration of Data Coop with Blockchain, challenges that are hindering its growth, and widespread use among data providers and consumers

• Aim 1: Investigate the application of Blockchain on how data owners/providers can have better control of their personal data compared to the traditional approach where the big data companies handle their data for them.
• Aim 2: Explore the application of Game Theory in the design of the consensus mechanism as well as the reward and penalty system to maintain trust and authenticity in the data-sharing/validating agents.
• Aim 3: Investigate the security vulnerabilities that are associated with Data Cooperatives thoroughly and explore the mitigation strategies for each.

Project 4: Multimodal Deep Learning for Secured Metaverse

Metaverse is still in the germination phase, composed of various major technologies that work together and provide users with an unprecedented experience. Nevertheless, the Metaverse also has plenty of severe security threats and vulnerabilities that need immediate action. Therefore, I plan to explore the security threats and mitigation strategies, especially secure auditing technique that helps eliminate these threats.

• Aim 1: Investigate on the potential security threats and vulnerabilities that Metaverse can introduce and their respective mitigation strategies.
• Aim 2: Explore on how Deepfake technologies can be a serious threat to Metaverse and how Blockchain and Deep Learning can help maintain the data provenance and detect the origin of the threat.
• Aim 3: Explore the multi modes of deep learning such as text, audio, video, image, and speech and similarly on the multi modes of Blockchain such as smart contract, oracle, wallet, and cryptocurrency and how we can audit them to find out the hidden security loopholes