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Learning to Detect Memory-related Vulnerabilities
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A comprehensive study on security bug characteristics
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Modeling Relational Data with Graph Convolutional Networks
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Locating faults with program slicing: an empirical analysis
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SPVF: security property assisted vulnerability fixing via attention-based models
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VulLoc: vulnerability localization based on inducing commits and fixing commits
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An algorithm for generating abstract syntax trees
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Improving defect prediction with deep forest
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BGNN4VD: Constructing Bidirectional Graph Neural-Network for Vulnerability Detection
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Evaluating and comparing memory error vulnerability detectors
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HGIVul: Detecting inter-procedural vulnerabilities based on hypergraph convolution
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Combine sliced joint graph with graph neural networks for smart contract vulnerability detection
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Are Similar Bugs Fixed with Similar Change Operations? An Empirical Study
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A deep learning‐based approach for software vulnerability detection using code metrics
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SPEC CPU2000: measuring CPU performance in the New Millennium
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Practical memory checking with Dr. Memory
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Can Deep Learning Models Learn the Vulnerable Patterns for Vulnerability Detection?
inferredcites →https://doi.org/10.1109/icpc.2019.00021openalex-snapshot
Neural Detection of Semantic Code Clones Via Tree-Based Convolution
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Shallow or Deep? An Empirical Study on Detecting Vulnerabilities using Deep Learning
inferredcites →https://doi.org/10.1109/icse.2019.00025openalex-snapshot
SMOKE: Scalable Path-Sensitive Memory Leak Detection for Millions of Lines of Code
inferredcites →https://doi.org/10.1109/icse.2019.00086openalex-snapshot
A Novel Neural Source Code Representation Based on Abstract Syntax Tree
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Improving Java Deserialization Gadget Chain Mining via Overriding-Guided Object Generation
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Vulnerability Detection with Graph Simplification and Enhanced Graph Representation Learning
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Learning Program Semantics with Code Representations: An Empirical Study
inferredcites →https://doi.org/10.1109/sp.2014.44openalex-snapshot
Modeling and Discovering Vulnerabilities with Code Property Graphs
inferredcites →https://doi.org/10.1109/sp46214.2022.9833613openalex-snapshot
Goshawk: Hunting Memory Corruptions via Structure-Aware and Object-Centric Memory Operation Synopsis
inferredcites →https://doi.org/10.1109/sp46215.2023.10179377openalex-snapshot
ODDFuzz: Discovering Java Deserialization Vulnerabilities via Structure-Aware Directed Greybox Fuzzing
inferredcites →https://doi.org/10.1109/tdsc.2019.2942930openalex-snapshot
μVulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection
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.2021.3076142openalex-snapshot
VulDeeLocator: A Deep Learning-Based Fine-Grained Vulnerability Detector
inferredcites →https://doi.org/10.1109/tifs.2020.3044773openalex-snapshot
Combining Graph-Based Learning With Automated Data Collection for Code Vulnerability Detection
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A Comprehensive Survey on Graph Neural Networks
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The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models
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Automatic Feature Learning for Predicting Vulnerable Software Components
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Deep Learning Based Vulnerability Detection: Are We There Yet?
inferredcites →https://doi.org/10.1145/1134285.1134321openalex-snapshot
Static detection of leaks in polymorphic containers
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Practical memory leak detection using guarded value-flow analysis
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Proceedings of the 25th international conference on Machine learning - ICML '08
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Static memory leak detection using full-sparse value-flow analysis
inferredcites →https://doi.org/10.1145/24039.24041openalex-snapshot
The program dependence graph and its use in optimization
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Automated memory leak detection for production use
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Deep learning code fragments for code clone detection
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System-dependence-graph-based slicing of programs with arbitrary interprocedural control flow
inferredcites →https://doi.org/10.1145/3192366.3192418openalex-snapshot
Pinpoint: fast and precise sparse value flow analysis for million lines of code
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code2vec: learning distributed representations of code
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SinkFinder: harvesting hundreds of unknown interesting function pairs with just one seed
inferredcites →https://doi.org/10.1145/3368089.3417923openalex-snapshot
PCA: memory leak detection using partial call-path analysis
inferredcites →https://doi.org/10.1145/3377811.3380386openalex-snapshot
Typestate-guided fuzzer for discovering use-after-free vulnerabilities
inferredcites →https://doi.org/10.1145/3379597.3387501openalex-snapshot
A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries
inferredcites →https://doi.org/10.1145/3437963.3441720openalex-snapshot
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks
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Detecting Missed Security Operations Through Differential Checking of Object-based Similar Paths
inferredcites →https://doi.org/10.1145/3460319.3464807openalex-snapshot
Runtime detection of memory errors with smart status
inferredcites →https://doi.org/10.1145/3468264.3468580openalex-snapshot
Boosting coverage-based fault localization via graph-based representation learning
inferredcites →https://doi.org/10.1145/3468264.3468597openalex-snapshot
Vulnerability detection with fine-grained interpretations
inferredcites →https://doi.org/10.1145/3533767.3534380openalex-snapshot
An empirical study on the effectiveness of static C code analyzers for vulnerability detection
inferredcites →https://doi.org/10.1145/3540250.3558920openalex-snapshot
KVS: a tool for knowledge-driven vulnerability searching
inferredcites →https://doi.org/10.14722/ndss.2018.23158openalex-snapshot
VulDeePecker: A Deep Learning-Based System for Vulnerability Detection
inferredcites →https://doi.org/10.14722/ndss.2018.23326openalex-snapshot
K-Miner: Uncovering Memory Corruption in Linux
inferredcites →https://doi.org/10.14722/ndss.2021.24416openalex-snapshot
Detecting Kernel Memory Leaks in Specialized Modules with Ownership Reasoning
inferredcites →https://doi.org/10.1609/aaai.v30i1.10139openalex-snapshot
Convolutional Neural Networks over Tree Structures for Programming Language Processing
inferredcites →https://doi.org/10.1609/aaai.v35i1.16074openalex-snapshot
TreeCaps: Tree-Based Capsule Networks for Source Code Processing
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.139openalex-snapshot
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
inferredcites →https://doi.org/10.24963/ijcai.2017/423openalex-snapshot
Supervised Deep Features for Software Functional Clone Detection by Exploiting Lexical and Syntactical Information in Source Code
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3115/v1/p15-1150openalex-snapshot
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
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On the naturalness of software
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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MemProfiler: A tracing and analysis system for memory fragmentation
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It Only Gets Worse: Revisiting DL-Based Vulnerability Detectors from a Practical Perspective
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SIExVulTS: Sensitive Information Exposure Vulnerability Detection System Using Transformer Models and Static Analysis
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EXVul: Toward Effective and Explainable Vulnerability Detection for IoT Devices
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HgtJIT: Just-in-Time Vulnerability Detection Based on Heterogeneous Graph Transformer
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KG4VA: Constructing Vulnerability Knowledge Graph for Software Vulnerability Assessment
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Code Language Models for Security Patch Management: How Far are We?
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GNNContext: GNN-based Code Context Prediction for Programming Tasks
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Misactivation-Aware Stealthy Backdoor Attacks on Neural Code Understanding Models
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Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems
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Snopy: Bridging Sample Denoising with Causal Graph Learning for Effective Vulnerability Detection
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Less Is More: Unlocking Semi-Supervised Deep Learning for Vulnerability Detection
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Shining Light on the Inter-procedural Code Obfuscation: Keep Pace with Progress in Binary Diffing
inferred← citeshttps://doi.org/10.1145/3735950.3735954openalex-snapshot
SecureMind: A Framework for Benchmarking Large Language Models in Memory Bug Detection and Repair
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Training on Clean Data but Getting Backdoored Models! A Poisoning Attack on Code Encoders
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Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspective
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Go With the Flow: Improving the Precision of Static Data Flow Analysis with Context-Sensitive Sinks
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CAP: Evidence-Guided Vulnerability-Path Mining for C/C++ Repositories
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Enhance Language Model-based Repair for Memory-related Vulnerabilities via Knowledge-and Semantic-guided Analysis
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RBZZER: A Directed Fuzzing Technique for Efficient Detection of Memory Leaks via Risk Area Analysis
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