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SCGformer: Smart contract vulnerability detection based on control flow graph and transformer

https://doi.org/10.1049/blc2.12046
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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-662-58387-6openalex-snapshot
Financial Cryptography and Data Security
inferredcites →https://doi.org/10.1016/j.comnet.2022.109289openalex-snapshot
Smart contract vulnerability detection combined with multi-objective detection
inferredcites →https://doi.org/10.1016/j.future.2023.05.016openalex-snapshot
DeepVulSeeker: A novel vulnerability identification framework via code graph structure and pre-training mechanism
inferredcites →https://doi.org/10.1016/j.knosys.2021.107312openalex-snapshot
Ponzi scheme detection via oversampling-based Long Short-Term Memory for smart contracts
inferredcites →https://doi.org/10.1109/csf.2018.00022openalex-snapshot
KEVM: A Complete Formal Semantics of the Ethereum Virtual Machine
inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9534324openalex-snapshot
DeeSCVHunter: A Deep Learning-Based Framework for Smart Contract Vulnerability Detection
inferredcites →https://doi.org/10.1109/infocomwkshps54753.2022.9798296openalex-snapshot
SCSGuard: Deep Scam Detection for Ethereum Smart Contracts
inferredcites →https://doi.org/10.1109/issre52982.2021.00047openalex-snapshot
Peculiar: Smart Contract Vulnerability Detection Based on Crucial Data Flow Graph and Pre-training Techniques
inferredcites →https://doi.org/10.1109/tkde.2021.3095196openalex-snapshot
Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection
inferredcites →https://doi.org/10.1109/tnse.2020.2968505openalex-snapshot
ContractWard: Automated Vulnerability Detection Models for Ethereum Smart Contracts
inferredcites →https://doi.org/10.1109/wetseb.2019.00008openalex-snapshot
Slither: A Static Analysis Framework for Smart Contracts
inferredcites →https://doi.org/10.1145/2976749.2978309openalex-snapshot
Making Smart Contracts Smarter
inferredcites →https://doi.org/10.1145/3274694.3274737openalex-snapshot
Osiris
inferredcites →https://doi.org/10.1145/3274694.3274743openalex-snapshot
Finding The Greedy, Prodigal, and Suicidal Contracts at Scale
inferredcites →https://doi.org/10.1145/3524610.3527894openalex-snapshot
Self-supervised learning of smart contract representations
inferredcites →https://doi.org/10.1145/3533767.3534367openalex-snapshot
jTrans: jump-aware transformer for binary code similarity detection
inferredcites →https://doi.org/10.1145/3540250.3558927openalex-snapshot
MANDO-GURU: vulnerability detection for smart contract source code by heterogeneous graph embeddings
inferredcites →https://doi.org/10.1609/aaai.v33i01.33017370openalex-snapshot
Graph Convolutional Networks for Text Classification
inferredcites →https://doi.org/10.24963/ijcai.2020/454openalex-snapshot
Smart Contract Vulnerability Detection using Graph Neural Network
inferredcites →https://doi.org/10.24963/ijcai.2021/379openalex-snapshot
Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-031-94620-2_8openalex-snapshot
Security Analysis of Smart Contracts: Evaluation of Vulnerability Detection Tools
inferred← citeshttps://doi.org/10.1007/978-3-032-13806-4_28openalex-snapshot
SCARF: Smart Contract Analysis and Risk Framework for Detecting Vulnerabilities Using Advanced Deep Learning Hybrid Model
inferred← citeshttps://doi.org/10.1007/978-3-032-17313-3_39openalex-snapshot
Accurate Identification of Smart Contract Attack Paths Based on Large Language Models
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.112968openalex-snapshot
The role of transformer models in advancing blockchain technology: A systematic survey
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.126353openalex-snapshot
Machine learning methods for detecting smart contracts vulnerabilities within Ethereum blockchain − A review
inferred← citeshttps://doi.org/10.1016/j.jss.2025.112454openalex-snapshot
CEGT: Smart contract vulnerability detection via Connectivity-Enhanced GCN-Transformer
inferred← citeshttps://doi.org/10.1049/blc2.12072openalex-snapshot
Enhancing smart contract security: Leveraging pre‐trained language models for advanced vulnerability detection
inferred← citeshttps://doi.org/10.1109/apsec66846.2025.00036openalex-snapshot
Software Defect Prediction Based on Temporal Hypergraph Neural Network*
inferred← citeshttps://doi.org/10.1109/ccwc62904.2025.10903869openalex-snapshot
Leveraging Large Language Models and Machine Learning for Smart Contract Vulnerability Detection
inferred← citeshttps://doi.org/10.1109/icsist70215.2026.11706022openalex-snapshot
Automated Smart Contract Vulnerability Detection using Hybrid Deep Learning and Language Models
inferred← citeshttps://doi.org/10.1145/3726122.3726256openalex-snapshot
A Comparative Analysis of Hybrid Deep Learning Models for Reentrancy Vulnerability Detection in Ethereum Smart Contracts
inferred← citeshttps://doi.org/10.1145/3750042openalex-snapshot
A Review of Learning-based Smart Contract Vulnerability Detection: A Perspective on Code Representation
inferred← citeshttps://doi.org/10.2139/ssrn.5165301openalex-snapshot
An Efficient Source Code Transformation Strategy Based on Graph-Based Machine Learning and Generative Ai Techniques
inferred← citeshttps://doi.org/10.3390/jcp4040040openalex-snapshot
A Comprehensive Review and Assessment of Cybersecurity Vulnerability Detection Methodologies
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