On the public citation graph

VulGraB : Graph ‐embedding‐based code vulnerability detection with bi‐directional gated graph neural network

0 signed · 53 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/spe.2905openalex-snapshot
SQVDT: A scalable quantitative vulnerability detection technique for source code security assessment
inferredcites →https://doi.org/10.1002/spe.3057openalex-snapshot
SafeOSL: Ensuring memory safety of C via ownership‐based intermediate language
inferredcites →https://doi.org/10.1007/s00500-021-05994-wopenalex-snapshot
Detecting vulnerability in source code using CNN and LSTM network
inferredcites →https://doi.org/10.1016/j.infsof.2020.106289openalex-snapshot
BVDetector: A program slice-based binary code vulnerability intelligent detection system
inferredcites →https://doi.org/10.1016/j.ins.2020.11.053openalex-snapshot
Neural software vulnerability analysis using rich intermediate graph representations of programs
inferredcites →https://doi.org/10.1109/access.2020.3016774openalex-snapshot
Vulnerability Prediction From Source Code Using Machine Learning
inferredcites →https://doi.org/10.1109/admit57209.2022.00024openalex-snapshot
GVD-net: Graph embedding-based Machine Learning Model for Smart Contract Vulnerability Detection
inferredcites →https://doi.org/10.1109/bigdata50022.2020.9377753openalex-snapshot
Machine Learning Methods for Improving Vulnerability Detection in Low-level Code
inferredcites →https://doi.org/10.1109/compcomm.2017.8322752openalex-snapshot
Vulnerability detection with deep learning
inferredcites →https://doi.org/10.1109/eurosp48549.2020.00012openalex-snapshot
VGRAPH: A Robust Vulnerable Code Clone Detection System Using Code Property Triplets
inferredcites →https://doi.org/10.1109/iceccs.2019.00011openalex-snapshot
Joint Prediction of Multiple Vulnerability Characteristics Through Multi-Task Learning
inferredcites →https://doi.org/10.1109/iceccs.2019.00012openalex-snapshot
Static Detection of Control-Flow-Related Vulnerabilities Using Graph Embedding
inferredcites →https://doi.org/10.1109/icmla.2018.00120openalex-snapshot
Automated Vulnerability Detection in Source Code Using Deep Representation Learning
inferredcites →https://doi.org/10.1109/icsme46990.2020.00096openalex-snapshot
Graph Neural Network-based Vulnerability Predication
inferredcites →https://doi.org/10.1109/msec.2018.2875879openalex-snapshot
Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware
inferredcites →https://doi.org/10.1109/saner.2019.8668039openalex-snapshot
Learning-Based Recursive Aggregation of Abstract Syntax Trees for Code Clone Detection
inferredcites →https://doi.org/10.1109/sp.2017.62openalex-snapshot
VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery
inferredcites →https://doi.org/10.1109/tdsc.2019.2954088openalex-snapshot
Software Vulnerability Discovery via Learning Multi-Domain Knowledge Bases
inferredcites →https://doi.org/10.1109/tdsc.2020.2984505openalex-snapshot
CD-VulD: Cross-Domain Vulnerability Discovery Based on Deep Domain Adaptation
inferredcites →https://doi.org/10.1109/tdsc.2021.3051525openalex-snapshot
SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities
inferredcites →https://doi.org/10.1109/tdsc.2022.3192419openalex-snapshot
How About Bug-Triggering Paths? - Understanding and Characterizing Learning-Based Vulnerability Detectors
inferredcites →https://doi.org/10.1109/tdsc.2022.3192631openalex-snapshot
Enhancing Security Patch Identification by Capturing Structures in Commits
inferredcites →https://doi.org/10.1109/tifs.2019.2895963openalex-snapshot
Large-Scale Empirical Study of Important Features Indicative of Discovered Vulnerabilities to Assess Application Security
inferredcites →https://doi.org/10.1109/tifs.2020.3044773openalex-snapshot
Combining Graph-Based Learning With Automated Data Collection for Code Vulnerability Detection
inferredcites →https://doi.org/10.1109/tse.2018.2869336openalex-snapshot
Value-Flow-Based Demand-Driven Pointer Analysis for C and C++
inferredcites →https://doi.org/10.1109/tse.2021.3087402openalex-snapshot
Deep Learning Based Vulnerability Detection: Are We There Yet?
inferredcites →https://doi.org/10.1145/2351676.2351733openalex-snapshot
Predicting common web application vulnerabilities from input validation and sanitization code patterns
inferredcites →https://doi.org/10.1145/2857705.2857720openalex-snapshot
Toward Large-Scale Vulnerability Discovery using Machine Learning
inferredcites →https://doi.org/10.1145/2939672.2939754openalex-snapshot
node2vec
inferredcites →https://doi.org/10.1145/3428301openalex-snapshot
Flow2Vec: value-flow-based precise code embedding
inferredcites →https://doi.org/10.1145/3436877openalex-snapshot
DeepWukong
inferredcites →https://doi.org/10.1145/3468264.3468597openalex-snapshot
Vulnerability detection with fine-grained interpretations
inferredcites →https://doi.org/10.1145/3533767.3534371openalex-snapshot
Path-sensitive code embedding via contrastive learning for software vulnerability detection
inferredcites →https://doi.org/10.1155/2020/8858010openalex-snapshot
A Survey of Automatic Software Vulnerability Detection, Program Repair, and Defect Prediction Techniques
inferredcites →https://doi.org/10.14722/ndss.2018.23158openalex-snapshot
VulDeePecker: A Deep Learning-Based System for Vulnerability Detection
inferredcites →https://doi.org/10.18653/v1/2021.naacl-main.165openalex-snapshot
Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models
inferredcites →https://doi.org/10.24963/ijcai.2017/214openalex-snapshot
End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks
inferredcites →https://doi.org/10.24963/ijcai.2019/648openalex-snapshot
VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/spe.3407openalex-snapshot
An Event Frequency‐Inverse Session Frequency Based Weighting Mechanism for Data Embedding Methodologies
inferred← citeshttps://doi.org/10.1007/978-3-031-70245-7_26openalex-snapshot
Towards the Use of Domain Knowledge to Enhance Transformer-Based Vulnerability Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-05188-2_20openalex-snapshot
On the Use of Imbalanced Datasets for Learning-Based Vulnerability Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-16649-4_2openalex-snapshot
Bridging Semantics and Structure for Software Vulnerability Detection Using Hybrid Network Models
inferred← citeshttps://doi.org/10.1007/s10664-026-10886-4openalex-snapshot
CMF-Vul: Advancing automated vulnerability detection via contrastive multimodal fusion and challenge-driven representation learning
inferred← citeshttps://doi.org/10.1007/s42979-026-05164-5openalex-snapshot
Beyond the Data: Architectural Choices for Imbalanced Learning in Vulnerability Detection
inferred← citeshttps://doi.org/10.1049/2024/8027037openalex-snapshot
IC‐GraF: An Improved Clustering with Graph‐Embedding‐Based Features for Software Defect Prediction
inferred← citeshttps://doi.org/10.1109/ast66626.2025.00022openalex-snapshot
Incorporating Domain Knowledge into GNNs for Advanced Vulnerability Detection in Java
inferred← citeshttps://doi.org/10.1109/nana63151.2024.00023openalex-snapshot
Probability analysis of system vulnerability distribution based on the matroid theory
inferred← citeshttps://doi.org/10.1109/tifs.2024.3392536openalex-snapshot
Vulnerability Detection Based on Enhanced Graph Representation Learning
inferred← citeshttps://doi.org/10.1145/3671016.3671379openalex-snapshot
Enhancing Deep Learning Vulnerability Detection through Imbalance Loss Functions: An Empirical Study
inferred← citeshttps://doi.org/10.1145/3699602openalex-snapshot
Less Is More: Unlocking Semi-Supervised Deep Learning for Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3777420openalex-snapshot
FORTIFY: Feature-Oriented Representation and Graph Topology Integration for Path-Level Vulnerability Detection
inferred← citeshttps://doi.org/10.32604/cmes.2025.068723openalex-snapshot
Vulnerability2Vec: A Graph-Embedding Approach for Enhancing Vulnerability Classification
inferred← citeshttps://doi.org/10.4108/eetsis.5056openalex-snapshot
E-GVD: Efficient Software Vulnerability Detection Techniques Based on Graph Neural Network
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.