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Home/Authors/Hyoungshick Kim

Hyoungshick Kim

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

Crypto×3Software Eng.×1

Frequent co-authors

Michael Robinson1×
Sajal Halder1×
Muhammad Ejaz Ahmed1×
Muhammad Ikram1×
Seyit Camtepe1×
Bushra Sabir1×

Research Timeline

2026
When the Abyss Looks Back: Unveiling Evolving Dark Patterns in Cookie Consent Banners

The paper introduces UMBRA, a novel system that detects evolved and subtle dark patterns in cookie consent banners, demonstrating that systematic non-compliance and user autonomy erosion are widespread across major websites.

Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval

The paper evaluates multi-LLM strategies for secure code generation, finding that hybrid pipelines combining ensembling, static analysis, and patching achieve the strongest security performance, outperforming single models and purely collaborative systems.

Original Sin of npm: A Study on Vulnerability Propagation in JavaScript Dependency Networks

The paper analyzes a large dataset of JavaScript packages to demonstrate that a small number of vulnerable dependencies can propagate vulnerabilities across a disproportionately large number of packages, highlighting systemic risks in the npm ecosystem.

Highlighted terms show continued research focus across papers

Papers

cs.CRRecentApr 19, 2026

Original Sin of npm: A Study on Vulnerability Propagation in JavaScript Dependency Networks

Michael Robinson, Sajal Halder, Muhammad Ejaz Ahmed, Muhammad Ikram +2 more

The paper analyzes a large dataset of JavaScript packages to demonstrate that a small number of vulnerable dependencies can propagate vulnerabilities across a disproportionately large number of packag…

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cs.CRcs.SERecentMar 24, 2026

Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval

Bushra Sabir, Shigang Liu, Seung Ick Jang, Sharif Abuadbba +5 more

The paper evaluates multi-LLM strategies for secure code generation, finding that hybrid pipelines combining ensembling, static analysis, and patching achieve the strongest security performance, outpe…

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cs.CRRecentMar 23, 2026

When the Abyss Looks Back: Unveiling Evolving Dark Patterns in Cookie Consent Banners

Nivedita Singh, Seyoung Jin, Hyoungshick Kim

The paper introduces UMBRA, a novel system that detects evolved and subtle dark patterns in cookie consent banners, demonstrating that systematic non-compliance and user autonomy erosion are widesprea…

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