Current Research Areas

I am presently engaged in the application of Artificial Intelligence, Machine Learning, and Collective Intelligence to create a dynamic, decentralized learning BOT ecosystem tailored for inter-app communications within Mobile Applications. This system is designed to effectively manage uncertain knowledge and beliefs.

Collaborative Works

I have experience in collaborating with clients to comprehend their problem statements and requirements, where I propose solutions and architectures to address their challenges. I possess rapid learning capabilities and the aptitude to apply my knowledge to deliver high-quality solutions within specified timelines.

Prior to embarking on my Ph.D. journey, I held the position of Research Scholar at Arizona State University. During my tenure there, I focused on cybersecurity attacks within the Android Open Source Project (AOSP), and my findings were published in HICSS’54. At present, I am actively involved in an Android Security project in partnership with professors from both Arizona State University and Texas A&M University.

Some of my noteworthy research innovations include:

• Trusted Knowledge Orchestration: A novel self-learning map based knowledge orchestration mechanism to classify the knowledge trustworthyness before use them for learning.
• Proximity based Trusted Communication: A dynamic system that define the agent communication payload based on the neighbours and their proximity.
• Ownership-based Encryption Protocol for Inter-component Communication in Android: A combination of Symmetric Key Encryption technique and “Trustless-Computing Base (TCB)”,  protecting apps from unknown IPC attacks.
• Arc Policy Language: Designed a lightweight policy language used in Android IPC to securely communicate between apps.
• Ownership-based Protocol for PendingIntent Communication: A secure lazy ownership-based communication to securly exchange privileges across process.
• Generative AI and Responsible AI based CAPTCHA Image generation adhering to geospatial constraints and policies.
• Mahalanobis Distance-Based Malware Detection Plotting: A lightweight technique that use Mahalanobis distance metrics (rather than using Euclidean) to identify the vulnerable app before installing them on the device.
• Blockchain for E-Governance and Supply Chain Security: Presented a novel Key-Generation technique at Block Chain Innovation Challenge, Tempe, AZ. Also presented a novel technique to solve Shadow Attacks in E-Government Document Sharing.
• Blockchain Metrics: A novel Blockchain Metrics combining Software Automation, NLP, and Blockchain Environment, called “Blockchain Digitizability Metrics” (a method to identify the digitizability from requirements).

Areas of Research

My main areas of research focus encompass Dynamic Knowledge Sharing, Encoding Bots learning and secure communication between Bots, Dynamic Program Analysis, Machine Learning, and Artificial Intelligence.