9 papers
Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research
Heajun An, Marcos Silva, Qi Zhang +8
Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while comp…
Grounded but Misleading: Evaluating Semantic Alignment in AI-Generated Security Explanations
Heajun An, Connor Ng, Sandesh Sharma Dulal +2
Online scams increasingly leverage fluent and context-aware social engineering strategies, creating growing demand for AI systems that explain why a message may be risky. However,…
CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety
Heajun An, Qi Zhang, Vedanth Achanta +1
Large language models (LLMs) are increasingly embedded in adolescent digital environments, mediating information seeking, advice, and emotionally sensitive interactions. Yet existi…
From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming Advances
Xinyi Zhang, Mamtaj Akter, Heajun An +6
Cybergrooming is a form of online abuse that threatens teens' mental health and physical safety. Yet, most prior work has focused on detecting perpetrators' behaviors, leaving a li…
Scam Shield: Multi-Model Voting and Fine-Tuned LLMs Against Adversarial Attacks
Chen-Wei Chang, Shailik Sarkar, Hossein Salemi +7
Scam detection remains a critical challenge in cybersecurity as adversaries craft messages that evade automated filters. We propose a Hierarchical Scam Detection System (HSDS) that…
LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models
Minqian Liu, Zhiyang Xu, Xinyi Zhang +8
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…