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Assessment of Software Vulnerability Contributing Factors by Model-Agnostic Explainable AI

https://doi.org/10.3390/make6020050

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What this work says

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

inferredcites →https://doi.org/10.1002/spy2.100openalex-snapshot

VYPER: Vulnerability detection in binary code

inferredcites →https://doi.org/10.1007/978-0-387-73003-5_196openalex-snapshot

Gaussian Mixture Models

inferredcites →https://doi.org/10.1007/978-3-030-30490-4_58openalex-snapshot

Towards Attention Based Vulnerability Discovery Using Source Code Representation

inferredcites →https://doi.org/10.1007/s10664-011-9190-8openalex-snapshot

Can traditional fault prediction models be used for vulnerability prediction?

inferredcites →https://doi.org/10.1007/s10664-022-10216-4openalex-snapshot

SPVF: security property assisted vulnerability fixing via attention-based models

inferredcites →https://doi.org/10.1016/j.artint.2022.103774openalex-snapshot

PredDiff: Explanations and interactions from conditional expectations

inferredcites →https://doi.org/10.1016/j.cose.2021.102286openalex-snapshot

HAN-BSVD: A hierarchical attention network for binary software vulnerability detection

inferredcites →https://doi.org/10.1016/j.cose.2021.102422openalex-snapshot

Information security vulnerability prediction based on business process model using machine learning approach

inferredcites →https://doi.org/10.1016/j.cose.2022.103023openalex-snapshot

BinVulDet: Detecting vulnerability in binary program via decompiled pseudo code and BiLSTM-attention

inferredcites →https://doi.org/10.1016/j.future.2022.04.008openalex-snapshot

Proximal Instance Aggregator networks for explainable security vulnerability detection

inferredcites →https://doi.org/10.1016/j.inffus.2024.102301openalex-snapshot

Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

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/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1093/biomet/30.1-2.81openalex-snapshot

A NEW MEASURE OF RANK CORRELATION

inferredcites →https://doi.org/10.1109/access.2020.3034766openalex-snapshot

Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey

inferredcites →https://doi.org/10.1109/bigdata50022.2020.9377803openalex-snapshot

Explainable Software vulnerability detection based on Attention-based Bidirectional Recurrent Neural Networks

inferredcites →https://doi.org/10.1109/bigdata55660.2022.10020313openalex-snapshot

The Analysis and Development of an XAI Process on Feature Contribution Explanation

inferredcites →https://doi.org/10.1109/comst.2016.2615098openalex-snapshot

Identifying Propagation Sources in Networks: State-of-the-Art and Comparative Studies

inferredcites →https://doi.org/10.1109/dsc.2016.33openalex-snapshot

Survey on Software Vulnerability Analysis Method Based on Machine Learning

inferredcites →https://doi.org/10.1109/ibf50092.2020.9034888openalex-snapshot

An Empirical Study of High-Impact Factors for Machine Learning-Based Vulnerability Detection

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/icse-companion55297.2022.9793807openalex-snapshot

ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection

inferredcites →https://doi.org/10.1109/icse48619.2023.00088openalex-snapshot

Fine-grained Commit-level Vulnerability Type Prediction by CWE Tree Structure

inferredcites →https://doi.org/10.1109/icsm.2013.85openalex-snapshot

srcML: An Infrastructure for the Exploration, Analysis, and Manipulation of Source Code: A Tool Demonstration

inferredcites →https://doi.org/10.1109/icst.2010.32openalex-snapshot

Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista

inferredcites →https://doi.org/10.1109/ijcnn55064.2022.9892280openalex-snapshot

VulBERTa: Simplified Source Code Pre-Training for Vulnerability Detection

inferredcites →https://doi.org/10.1109/jproc.2020.2993293openalex-snapshot

Software Vulnerability Detection Using Deep Neural Networks: A Survey

inferredcites →https://doi.org/10.1109/mc.2022.3233806openalex-snapshot

A Trustworthy View on Explainable Artificial Intelligence Method Evaluation

inferredcites →https://doi.org/10.1109/msr.2019.00015openalex-snapshot

Semantic Source Code Models Using Identifier Embeddings

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.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

inferredcites →https://doi.org/10.1109/tii.2018.2821768openalex-snapshot

Cross-Project Transfer Representation Learning for Vulnerable Function Discovery

inferredcites →https://doi.org/10.1109/tse.2010.81openalex-snapshot

Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities

inferredcites →https://doi.org/10.1109/tse.2018.2881961openalex-snapshot

Automatic Feature Learning for Predicting Vulnerable Software Components

inferredcites →https://doi.org/10.1109/tse.2021.3087402openalex-snapshot

Deep Learning Based Vulnerability Detection: Are We There Yet?

inferredcites →https://doi.org/10.1126/scirobotics.aay7120openalex-snapshot

XAI—Explainable artificial intelligence

inferredcites →https://doi.org/10.1145/1135777.1135817openalex-snapshot

SecuBat

inferredcites →https://doi.org/10.1145/1414004.1414065openalex-snapshot

An empirical model to predict security vulnerabilities using code complexity metrics

inferredcites →https://doi.org/10.1145/2184512.2184604openalex-snapshot

High false positive detection of security vulnerabilities

inferredcites →https://doi.org/10.1145/24039.24041openalex-snapshot

The program dependence graph and its use in optimization

inferredcites →https://doi.org/10.1145/2420950.2420981openalex-snapshot

Augmenting vulnerability analysis of binary code

inferredcites →https://doi.org/10.1145/2746194.2746198openalex-snapshot

Challenges with applying vulnerability prediction models

inferredcites →https://doi.org/10.1145/2939672.2939778openalex-snapshot

"Why Should I Trust You?"

inferredcites →https://doi.org/10.1145/3243734.3243792openalex-snapshot

LEMNA

inferredcites →https://doi.org/10.1145/3290353openalex-snapshot

code2vec: learning distributed representations of code

inferredcites →https://doi.org/10.1145/3297001.3297023openalex-snapshot

DeepTriage

inferredcites →https://doi.org/10.1145/3524610.3527921openalex-snapshot

An exploratory study on code attention in BERT

inferredcites →https://doi.org/10.1145/3538969.3543809openalex-snapshot

Explainability-based Debugging of Machine Learning for Vulnerability Discovery

inferredcites →https://doi.org/10.1145/3542944openalex-snapshot

Towards Learning Generalizable Code Embeddings Using Task-agnostic Graph Convolutional Networks

inferredcites →https://doi.org/10.1145/3585386openalex-snapshot

VulANalyzeR: Explainable Binary Vulnerability Detection with Multi-task Learning and Attentional Graph Convolution

inferredcites →https://doi.org/10.1145/390013.808479openalex-snapshot

Control flow analysis

inferredcites →https://doi.org/10.1155/2022/5203217openalex-snapshot

Deep Neural Embedding for Software Vulnerability Discovery: Comparison and Optimization

inferredcites →https://doi.org/10.1162/tacl_a_00051openalex-snapshot

Enriching Word Vectors with Subword Information

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/10.18653/v1/p19-1320openalex-snapshot

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

inferredcites →https://doi.org/10.24963/ijcai.2019/648openalex-snapshot

VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities

inferredcites →https://doi.org/10.4230/oasics.dx.2024.27openalex-snapshot

On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

inferredcites →https://doi.org/10.48550/arxiv.1702.04595openalex-snapshot

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis

inferredcites →https://doi.org/10.48550/arxiv.2009.08366openalex-snapshot

GraphCodeBERT: Pre-training Code Representations with Data Flow

inferredcites →https://doi.org/10.48550/arxiv.2011.14878openalex-snapshot

Explaining by Removing: A Unified Framework for Model Explanation

inferredcites →https://doi.org/10.5281/zenodo.2546487openalex-snapshot

Import2vec - Learning Embeddings for Software Libraries

inferredcites →https://doi.org/10.5455/jjcit.71-1597824949openalex-snapshot

EFFICIENT DEEP FEATURES LEARNING FOR VULNERABILITY DETECTION USING CHARACTER N-GRAM EMBEDDING

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-031-89063-5_35openalex-snapshot

A Robust Adversarial Attack Framework for Enhanced Software Vulnerability Detection Systems

inferred← citeshttps://doi.org/10.1007/978-981-95-6786-7_11openalex-snapshot

Dynamic Source Code Vulnerability Characteristics Selection for Enhanced Vulnerability Discovery

inferred← citeshttps://doi.org/10.1007/s00500-025-10751-4openalex-snapshot

Explainable-AI-assisted feature selection for software change-proneness prediction

inferred← citeshttps://doi.org/10.1109/access.2025.3555860openalex-snapshot

Vulnerability Time Series Forecasting: A Comparative Study of Hierarchical and Non-Hierarchical Approaches

inferred← citeshttps://doi.org/10.1109/access.2025.3574246openalex-snapshot

A Comprehensive Content-Based Recommendation System for Programming Problems Through Multi-Faceted Code Analysis

inferred← citeshttps://doi.org/10.1109/cisat71030.2026.11682178openalex-snapshot

Logic-Aware Vulnerability Knowledge Graph Model for Precise Vulnerability Assessment

inferred← citeshttps://doi.org/10.1109/ic-icns68863.2026.11537431openalex-snapshot

A Comparative Analysis of CodeBERT, LSTM, and GRU Deep Learning Models for Vulnerability Detection in C/C++

inferred← citeshttps://doi.org/10.1109/rait65068.2025.11088900openalex-snapshot

Leveraging Explainable AI for Pointer Usage-based Software Vulnerability Analysis

inferred← citeshttps://doi.org/10.1145/3793638.3793639openalex-snapshot

Leveraging Transformers to Discover Software Vulnerabilities based on Source Code Slices

inferred← citeshttps://doi.org/10.3390/electronics15010008openalex-snapshot

Research on Binary Decompilation Optimization Based on Fine-Tuned Large Language Models for Vulnerability Detection

inferred← citeshttps://doi.org/10.3390/jcp4040040openalex-snapshot

A Comprehensive Review and Assessment of Cybersecurity Vulnerability Detection Methodologies

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.