VORN Naro

Master Student

Department of Big Data, Chungbuk National University

Big Data
LLM
Cybersecurity
Applied AI

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Academic Background

Now

Current

Master's Degree in Big Data (Integrated Student), Chungbuk National University, South Korea (September 2025 to Present)

Bachelor's Degree

Computer Science, Royal University of Phnom Penh, Cambodia (2023)

Recent publications

SCOPUS

ASG-LLM: An LLM-based pipeline for automated scraping code generation in security-sensitive environments

Sokheang Chan, Naro Vorn, Vungsovanreach Kong, Chang Kue Seok, Jong-Hyun Kim, Anand Nayyar, Tae-Kyung Kim

Array, Vol. 31, 101135, Sep. 2026

View Paper

Conference

From AI Policy Principles to Monitoring Dashboard: A Conceptual Governance Framework for AI Policy Implementation in Government

Ratanaktepi Chhor, Naro Vorn, Kimchhor Chiv, Tae-Kyung Kim

BIGDAS 2026, 14th International Conference on Big Data Applications and Services, Aug. 2026

View Conference

Conference

Motion-Aware Open-Vocabulary Video Object Segmentation

Rotanakkosal Chhun, Vungsovanreach Kong, Naro Vorn, Ratanaktepi Chhor, Tae-Kyung Kim

BIGDAS 2026, 14th International Conference on Big Data Applications and Services, Aug. 2026

View Conference

Research Focus

His work explores the intersection of multimodal AI, large language models (LLMs), and cybersecurity applications. This unique combination aims to develop intelligent security systems that leverage AI for enhanced digital protection.

Multimodal Learning (MLLMs)

Integrating multiple data types for comprehensive AI understanding

AI-driven Cybersecurity Systems

Applying AI to detect and prevent security threats

Applied Artificial Intelligence

Real-world problem-solving with AI

Large Language Models

Leveraging LLMs for security applications

Intelligent Automation

Developing AI-driven systems for process automation

Research Projects

IntelliScrape: An AI-assisted Web Scraping Module Generator

An AI-assisted module development system designed to automate COOCON's scraping module creation process. The system leverages artificial intelligence, network traffic analysis, and browser automation technologies to reduce manual effort, minimize human error, and accelerate development lifecycle.

Key Contributions

Backend Architecture & Pipeline Design

Architected and implemented the complete project pipeline for the request transmitter component using Python and FastAPI, ensuring scalable and efficient request processing

Exception Handling & Validation

Developed robust exception handling mechanisms with iSASType engine validation, ensuring system reliability and data integrity throughout the scraping workflow

JavaScript Analysis & Module Generation

Conducted in-depth analysis and tracing of external JavaScript functions to facilitate intelligent and accurate dynamic module generation, bridging frontend-backend integration challenges

Documentation & Visualization

Prepared comprehensive figures, diagrams, and video demonstrations showcasing system architecture and functionality for research dissemination and stakeholder communication

Quality Assurance & Testing

Conducted extensive validation and testing procedures to ensure project implementation meets performance and reliability standards

Technical Documentation

Contributed to the preparation of detailed project documentation, including technical specifications, API documentation, and implementation guides

Technologies: Python, FastAPI, JavaScript Analysis, Large Language Models, Browser Automation, Network Traffic Analysis, Exception Handling

Cybersecurity Background

With one year of focused cybersecurity research experience, Vorn Naro has developed expertise in penetration testing and system security assessment. This background provides valuable insights into security vulnerabilities and defense mechanisms, which he now integrates with AI technologies to create more intelligent and proactive security solutions.

Current Research at AICLab

Exploring multimodal AI for cybersecurity applications

Developing LLM-based security analysis tools

Investigating AI-driven threat detection and prevention

Building scalable security systems using big data analytics

Bridging AI research with practical cybersecurity needs

VORN Naro

Academic Background

Recent publications

ASG-LLM: An LLM-based pipeline for automated scraping code generation in security-sensitive environments

From AI Policy Principles to Monitoring Dashboard: A Conceptual Governance Framework for AI Policy Implementation in Government

Motion-Aware Open-Vocabulary Video Object Segmentation

Research Focus

Research Projects

IntelliScrape: An AI-assisted Web Scraping Module Generator

Key Contributions

Cybersecurity Background

Current Research at AICLab

Professional Experience

Technical Expertise

Research Goals

Unique Perspective

Vision

2026

ASG-LLM: An LLM-based pipeline for automated scraping code generation in security-sensitive environments

From AI Policy Principles to Monitoring Dashboard: A Conceptual Governance Framework for AI Policy Implementation in Government

Motion-Aware Open-Vocabulary Video Object Segmentation

Multi-Agent Scientific Hypothesis Generation & Verification

2025

Evaluating DNSSEC Against DNS Spoofing/MITM Attack in Virtualized Networks

The Role of Continuous Integration and Continuous Deployment in Modern DevOps Practices

AI-Scientist Web-Based System for Streamlined Scientific Paper Generation