Analysis of PHP WebShell Detection Based on Large Language Model (LLM) in Resource-Constrained Environment
- 2 July 2026
- book chapter
- Published by Springer Nature
- p. 264-274
Abstract
No abstract availableKeywords
This publication has 11 references indexed in Scilit:
- Exploring the Cybercrime Potential of LLMs: A Focus on Phishing and Malware Generation2025
- Webshell Detection by Transformer Model2025
- LeoDroid: An LLM-Based Few-Shot Multi-Label Detection for Android Malware2025
- Feasibility Study for Supporting Static Malware Analysis Using LLM2025
- Malware Detection at the Edge with Lightweight LLMs: A Performance EvaluationarXiv, 2025
- Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT ModelsarXiv, 2025
- Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls2024
- Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure ApproachesarXiv, 2024
- Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape SamplesarXiv, 2024
- MSDetector: A Static PHP Webshell Detection System Based on Deep-Learning2022