Jin-Hee Cho
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View article: Multi-Agent Code-Orchestrated Generation for Reliable Infrastructure-as-Code
Multi-Agent Code-Orchestrated Generation for Reliable Infrastructure-as-Code Open
The increasing complexity of cloud-native infrastructure has made Infrastructure-as-Code (IaC) essential for reproducible and scalable deployments. While large language models (LLMs) have shown promise in generating IaC snippets from natur…
View article: Generative AI for Geospatial Analysis: Fine-Tuning ChatGPT to Convert Natural Language into Python-Based Geospatial Computations
Generative AI for Geospatial Analysis: Fine-Tuning ChatGPT to Convert Natural Language into Python-Based Geospatial Computations Open
This study investigates the potential of fine-tuned large language models (LLMs) to enhance geospatial intelligence by translating natural language queries into executable Python code. Traditional GIS workflows, while effective, often lack…
View article: KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data
KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data Open
We found that using k-mer and fetal fraction reduces errors in NIPT and have integrated this into a pipeline, showing that the traditional read count-based z-score method can be improved. KF-NIPT is implemented in the R and Python environm…
View article: LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models
LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models Open
Recent advancements in Large Language Models (LLMs) have enabled them to approach human-level persuasion capabilities. However, such potential also raises concerns about the safety risks of LLM-driven persuasion, particularly their potenti…
View article: SCVI: Bridging Social and Cyber Dimensions for Comprehensive Vulnerability Assessment
SCVI: Bridging Social and Cyber Dimensions for Comprehensive Vulnerability Assessment Open
The rise of cyber threats on social media platforms necessitates advanced metrics to assess and mitigate social cyber vulnerabilities. This paper presents the Social Cyber Vulnerability Index (SCVI), a novel framework integrating individua…
View article: Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research
Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research Open
Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while computational methods emphasize detection, but their integratio…
View article: RESONANT: Reinforcement Learning-based Moving Target Defense for Credit Card Fraud Detection
RESONANT: Reinforcement Learning-based Moving Target Defense for Credit Card Fraud Detection Open
According to security.org, as of 2023, 65% of credit card (CC) users in the US have been subjected to fraud at some point in their lives, which equates to about 151 million Americans. The proliferation of advanced machine learning (ML) alg…
View article: Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models
Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models Open
In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications. As the use of LLMs expands, precisely estimating the uncertainty in their predictions has become crucial. Cu…
View article: AuSSE: A Novel Framework for Security and Safety Evaluation for Autonomous Vehicles
AuSSE: A Novel Framework for Security and Safety Evaluation for Autonomous Vehicles Open
Autonomous vehicles (AV) are becoming increasingly efficient and equipped with advanced technologies and connectivity. These include over-the-air software updates, connecting telematics data, and software-defined vehicles. However, these a…
View article: Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks
Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks Open
As online social networks (OSNs) become more prevalent, a new paradigm for problem-solving through crowd-sourcing has emerged. By leveraging the OSN platforms, users can post a problem to be solved and then form a team to collaborate and s…
View article: Generating A Crowdsourced Conversation Dataset to Combat Cybergrooming
Generating A Crowdsourced Conversation Dataset to Combat Cybergrooming Open
Cybergrooming emerges as a growing threat to adolescent safety and mental health. One way to combat cybergrooming is to leverage predictive artificial intelligence (AI) to detect predatory behaviors in social media. However, these methods …
View article: Winning the Social Media Influence Battle: Uncertainty-Aware Opinions to Understand and Spread True Information via Competitive Influence Maximization
Winning the Social Media Influence Battle: Uncertainty-Aware Opinions to Understand and Spread True Information via Competitive Influence Maximization Open
Competitive Influence Maximization (CIM) involves entities competing to maximize influence in online social networks (OSNs). Current Deep Reinforcement Learning (DRL) methods in CIM rely on simplistic binary opinion models (i.e., an opinio…
View article: Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty Open
Deep neural networks (DNNs) have been shown to perform well on exclusive, multi-class classification tasks. However, when different classes have similar visual features, it becomes challenging for human annotators to differentiate them. Th…
View article: SusFL: Energy-Aware Federated Learning-based Monitoring for Sustainable Smart Farms
SusFL: Energy-Aware Federated Learning-based Monitoring for Sustainable Smart Farms Open
We propose a novel energy-aware federated learning (FL)-based system, namely SusFL, for sustainable smart farming to address the challenge of inconsistent health monitoring due to fluctuating energy levels of solar sensors. This system equ…
View article: Decision Theory-Guided Deep Reinforcement Learning for Fast Learning
Decision Theory-Guided Deep Reinforcement Learning for Fast Learning Open
This paper introduces a novel approach, Decision Theory-guided Deep Reinforcement Learning (DT-guided DRL), to address the inherent cold start problem in DRL. By integrating decision theory principles, DT-guided DRL enhances agents' initia…
View article: Energy-Adaptive, Robust Monitoring for Solar Sensor-based Smart Farms Under Adversarial Attacks
Energy-Adaptive, Robust Monitoring for Solar Sensor-based Smart Farms Under Adversarial Attacks Open
We propose a solar sensor-based smart farm system to provide high monitoring quality while preserving sensor energy in the presence of adversarial attacks. Since solar sensors are attached to cows to monitor their health under varying weat…
View article: Energy-Adaptive, Robust Monitoring for Solar Sensor-based Smart Farms Under Adversarial Attacks
Energy-Adaptive, Robust Monitoring for Solar Sensor-based Smart Farms Under Adversarial Attacks Open
We propose a solar sensor-based smart farm system to provide high monitoring quality while preserving sensor energy in the presence of adversarial attacks. Since solar sensors are attached to cows to monitor their health under varying weat…
View article: Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation
Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation Open
Artificial neural networks (ANNs) have been broadly utilized to analyze various data and solve different domain problems. However, neural networks (NNs) have been considered a black box operation for years because their underlying computat…
View article: Deception in Drone Surveillance Missions: Strategic vs. Learning Approaches
Deception in Drone Surveillance Missions: Strategic vs. Learning Approaches Open
Unmanned Aerial Vehicles (UAVs) have been used for surveillance operations, search and rescue missions, and delivery services. Given their importance and versatility, they naturally become targets for cyberattacks. Denial-of-Service (DoS) …
View article: 2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making
2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making Open
Uncertainty reasoning and quantification play a critical role in decision making across various domains, prompting increased attention from both academia and industry. As real-world applications become more complex and data-driven, effecti…
View article: End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models
End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models Open
We propose end-to-end multimodal fact-checking and explanation generation, where the input is a claim and a large collection of web sources, including articles, images, videos, and tweets, and the goal is to assess the truthfulness of the …
View article: Text Mining-based Social-Psychological Vulnerability Analysis of Potential Victims To Cybergrooming: Insights and Lessons Learned
Text Mining-based Social-Psychological Vulnerability Analysis of Potential Victims To Cybergrooming: Insights and Lessons Learned Open
Cybergrooming is a serious cybercrime that primarily targets youths through online platforms. Although reactive predator detection methods have been studied, proactive victim protection and crime prevention can also be achieved through vul…
View article: Authentic Dialogue Generation to Improve Youth’s Awareness of Cybergrooming for Online Safety
Authentic Dialogue Generation to Improve Youth’s Awareness of Cybergrooming for Online Safety Open
This paper deals with a cybergrooming and sexual misconduct topic in artificial intelligence-based educational programs. Although cybergrooming has been recognized as a cybercrime, there is a lack of programs to protect youth from cybergro…
View article: Authentic Dialogue Generation to Improve Youth’s Awareness of Cybergrooming for Online Safety
Authentic Dialogue Generation to Improve Youth’s Awareness of Cybergrooming for Online Safety Open
This paper deals with a cybergrooming and sexual misconduct topic in artificial intelligence-based educational programs. Although cybergrooming has been recognized as a cybercrime, there is a lack of programs to protect youth from cybergro…
View article: Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information
Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information Open
Due to various and serious adverse impacts of spreading fake news, it is often known that only people with malicious intent would propagate fake news. However, it is not necessarily true based on social science studies. Distinguishing the …