Cover Image

FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Yiling, Lou, Jian, Qin, Zhan, Ren, Kui
Format:	Preprint
Published:	2023
Subjects:	Cryptography and Security Machine Learning Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SeBERTis: A Framework for Producing Classifiers of Security-Related Issue Reports
by: Masoumzadeh, Sogol, et al.
Published: (2025)

Enhancing Cloud Security through Topic Modelling
by: Saleh, Sabbir M., et al.
Published: (2025)

Unintentional Security Flaws in Code: Automated Defense via Root Cause Analysis
by: Islam, Nafis Tanveer, et al.
Published: (2024)

Alleviating Attack Data Scarcity: SCANIA's Experience Towards Enhancing In-Vehicle Cyber Security Measures
by: Sundfeldt, Frida, et al.
Published: (2025)

Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
by: Kharma, Mohammed, et al.
Published: (2025)

Security Vulnerability Detection with Multitask Self-Instructed Fine-Tuning of Large Language Models
by: Yang, Aidan Z. H., et al.
Published: (2024)

Deep Learning Model Security: Threats and Defenses
by: Wang, Tianyang, et al.
Published: (2024)

A Modular Approach to Automatic Cyber Threat Attribution using Opinion Pools
by: Teuwen, Koen T. W.
Published: (2024)

Rethinking the Evaluation of Secure Code Generation
by: Dai, Shih-Chieh, et al.
Published: (2025)

RESCUE: Retrieval Augmented Secure Code Generation
by: Shi, Jiahao, et al.
Published: (2025)

Expanding ML-Documentation Standards For Better Security
by: Appel, Cara Ellen
Published: (2025)

Assessing the Software Security Comprehension of Large Language Models
by: Siddiq, Mohammed Latif, et al.
Published: (2025)

"You still have to study" -- On the Security of LLM generated code
by: Goetz, Stefan, et al.
Published: (2024)

Evaluating and Improving the Robustness of Security Attack Detectors Generated by LLMs
by: Pasini, Samuele, et al.
Published: (2024)

SecureInfer: Heterogeneous TEE-GPU Architecture for Privacy-Critical Tensors for Large Language Model Deployment
by: Nayan, Tushar, et al.
Published: (2025)

How Safe Are AI-Generated Patches? A Large-scale Study on Security Risks in LLM and Agentic Automated Program Repair on SWE-bench
by: Sajadi, Amirali, et al.
Published: (2025)

Large Language Models for Code: Security Hardening and Adversarial Testing
by: He, Jingxuan, et al.
Published: (2023)

Instruction Tuning for Secure Code Generation
by: He, Jingxuan, et al.
Published: (2024)

Beimingwu: A Learnware Dock System
by: Tan, Zhi-Hao, et al.
Published: (2024)

Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
by: Shao, Shuo, et al.
Published: (2024)

Learning to Triage Taint Flows Reported by Dynamic Program Analysis in Node.js Packages
by: Ni, Ronghao, et al.
Published: (2025)

Security study based on the Chatgptplugin system: ldentifying Security Vulnerabilities
by: Ren, Ruomai
Published: (2025)

DeUEDroid: Detecting Underground Economy Apps Based on UTG Similarity
by: Chen, Zhuo, et al.
Published: (2022)

VulCatch: Enhancing Binary Vulnerability Detection through CodeT5 Decompilation and KAN Advanced Feature Extraction
by: Chukkol, Abdulrahman Hamman Adama, et al.
Published: (2024)

An Exploratory Study on the Engineering of Security Features
by: Hermann, Kevin, et al.
Published: (2025)

Constrained Decoding for Secure Code Generation
by: Fu, Yanjun, et al.
Published: (2024)

A Practical Adversarial Attack against Sequence-based Deep Learning Malware Classifiers
by: Tan, Kai, et al.
Published: (2025)

Prompting Techniques for Secure Code Generation: A Systematic Investigation
by: Tony, Catherine, et al.
Published: (2024)

BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer
by: Jha, Piyush, et al.
Published: (2023)

Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection
by: Luan, Xiaokun, et al.
Published: (2024)

THEMIS: Towards Practical Intellectual Property Protection for Post-Deployment On-Device Deep Learning Models
by: Huang, Yujin, et al.
Published: (2025)

Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMs
by: Camporese, Maria, et al.
Published: (2025)

Towards Predicting Multi-Vulnerability Attack Chains in Software Supply Chains from Software Bill of Materials Graphs
by: Baird, Laura, et al.
Published: (2026)

Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?
by: Le, Triet H. M., et al.
Published: (2024)

ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data
by: Wang, Weizhou, et al.
Published: (2024)

Basic Legibility Protocols Improve Trusted Monitoring
by: Sreevatsa, Ashwin, et al.
Published: (2026)

A Large-Scale Exploit Instrumentation Study of AI/ML Supply Chain Attacks in Hugging Face Models
by: Casey, Beatrice, et al.
Published: (2024)

On Training a Neural Network to Explain Binaries
by: Interrante-Grant, Alexander, et al.
Published: (2024)

Using ML filters to help automated vulnerability repairs: when it helps and when it doesn't
by: Camporese, Maria, et al.
Published: (2025)

REBENCH: A Procedural, Fair-by-Construction Benchmark for LLMs on Stripped-Binary Types and Names (Extended Version)
by: Won, Jun Yeon, et al.
Published: (2026)