3 citations · 5 across the 10 of their papers we have counts for
10 papers
SCRIPTIOC-BENCH: A Benchmark for Recognizing Actionable Threat Intelligence from Script-Based Malware using LLMs
Hanna Kim, Jian Cui, Minkyoo Song +4
Script-based malware remains a prevalent attack technique. These scripts often contain indicators of compromise (IOCs) that provide actionable threat intelligence. However, statica…
SkillMutator: Benchmarking and Defending Language-and-Code Cross-modal Attacks on LLM Agent Skills
Youngduk Kim, Minkyoo Song, Seungwon Shin
Large language model (LLM) agents increasingly extend their capabilities at runtime by loading Agent Skills, which pair natural-language specifications (SKILL.md) with executable s…
Graphs Don't Stay Secret: Practical Subgraph Reconstruction Attacks on Defended Graph RAG
Minkyoo Song, Jaehan Kim, Myungchul Kang +3
Graph-based retrieval-augmented generation (Graph RAG) is increasingly deployed to support LLM applications by augmenting user queries with structured knowledge retrieved from a kn…
: Politically Controversial Content Generation via Jailbreaking Attacks on GPT-based Text-to-Image Models
Wonwoo Choi, Minjae Seo, Minkyoo Song +3
The rapid evolution of text-to-image (T2I) models has enabled high-fidelity visual synthesis on a global scale. However, these advancements have introduced significant security ris…
PassREfinder-FL: Privacy-Preserving Credential Stuffing Risk Prediction via Graph-Based Federated Learning for Representing Password Reuse between Websites
Jaehan Kim, Minkyoo Song, Minjae Seo +3
Credential stuffing attacks have caused significant harm to online users who frequently reuse passwords across multiple websites. While prior research has attempted to detect users…
Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment
Jaehan Kim, Minkyoo Song, Seungwon Shin +1
Recent large language models (LLMs) have increasingly adopted the Mixture-of-Experts (MoE) architecture for efficiency. MoE-based LLMs heavily depend on a superficial safety mechan…
Covering Cracks in Content Moderation: Delexicalized Distant Supervision for Illicit Drug Jargon Detection
Minkyoo Song, Eugene Jang, Jaehan Kim +1
In light of rising drug-related concerns and the increasing role of social media, sales and discussions of illicit drugs have become commonplace online. Social media platforms host…
Obliviate: Neutralizing Task-agnostic Backdoors within the Parameter-efficient Fine-tuning Paradigm
Jaehan Kim, Minkyoo Song, Seung Ho Na +1
Parameter-efficient fine-tuning (PEFT) has become a key training strategy for large language models. However, its reliance on fewer trainable parameters poses security risks, such…
When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs
Hanna Kim, Minkyoo Song, Seung Ho Na +2
Recent advancements in Large Language Models (LLMs) have established them as agentic systems capable of planning and interacting with various tools. These LLM agents are often pair…
Claim-Guided Textual Backdoor Attack for Practical Applications
Minkyoo Song, Hanna Kim, Jaehan Kim +2
Recent advances in natural language processing and the increased use of large language models have exposed new security vulnerabilities, such as backdoor attacks. Previous backdoor…