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ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability

https://doi.org/10.1109/pac.2017.10

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What this work says

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

inferredcites →https://doi.org/10.1007/978-0-387-36584-8_3openalex-snapshot

Software Security Growth Modeling: Examining Vulnerabilities with Reliability Growth Models

inferredcites →https://doi.org/10.1007/978-3-319-45871-7_21openalex-snapshot

A Bayesian Cogntive Approach to Quantifying Software Exploitability Based on Reachability Testing

inferredcites →https://doi.org/10.1007/978-3-642-23088-2_15openalex-snapshot

An Empirical Study on Using the National Vulnerability Database to Predict Software Vulnerabilities

inferredcites →https://doi.org/10.1007/s11219-015-9274-6openalex-snapshot

Assessing vulnerability exploitability risk using software properties

inferredcites →https://doi.org/10.1016/j.cose.2006.10.002openalex-snapshot

Measuring, analyzing and predicting security vulnerabilities in software systems

inferredcites →https://doi.org/10.1017/cbo9780511804779openalex-snapshot

Bayesian Reasoning and Machine Learning

inferredcites →https://doi.org/10.1109/52.976940openalex-snapshot

Improving security using extensible lightweight static analysis

inferredcites →https://doi.org/10.1109/rams.2005.1408432openalex-snapshot

Quantitative vulnerability assessment of systems software

inferredcites →https://doi.org/10.1109/sp.2006.29openalex-snapshot

Pixy: a static analysis tool for detecting Web application vulnerabilities

inferredcites →https://doi.org/10.1109/sp.2010.37openalex-snapshot

TaintScope: A Checksum-Aware Directed Fuzzing Tool for Automatic Software Vulnerability Detection

inferredcites →https://doi.org/10.1109/sp.2012.31openalex-snapshot

Unleashing Mayhem on Binary Code

inferredcites →https://doi.org/10.1109/sp.2015.50openalex-snapshot

Program-Adaptive Mutational Fuzzing

inferredcites →https://doi.org/10.1109/tr.2008.916872openalex-snapshot

Application of Vulnerability Discovery Models to Major Operating Systems

inferredcites →https://doi.org/10.1109/tse.2010.60openalex-snapshot

An Attack Surface Metric

inferredcites →https://doi.org/10.1145/1314257.1314261openalex-snapshot

Improving vulnerability discovery models

inferredcites →https://doi.org/10.1145/1719030.1719036openalex-snapshot

Quantified security is a weak hypothesis

inferredcites →https://doi.org/10.1145/1835804.1835821openalex-snapshot

Beyond heuristics

inferredcites →https://doi.org/10.1145/2090147.2094081openalex-snapshot

SAGE: Whitebox Fuzzing for Security Testing

inferredcites →https://doi.org/10.1145/2093548.2093564openalex-snapshot

SAGE

inferredcites →https://doi.org/10.1145/2508859.2516736openalex-snapshot

Scheduling black-box mutational fuzzing

inferredcites →https://doi.org/10.1145/2560217.2560219openalex-snapshot

Automatic exploit generation

inferredcites →https://doi.org/10.1145/2857705.2857720openalex-snapshot

Toward Large-Scale Vulnerability Discovery using Machine Learning

inferredcites →https://doi.org/10.1184/r1/6469118openalex-snapshot

Optimizing Seed Selection for Fuzzing

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-032-20018-1_5openalex-snapshot

Predicting IoT Security Vulnerabilities from Device Specifications

inferred← citeshttps://doi.org/10.1016/j.cose.2022.102946openalex-snapshot

Improving fuzzing assessment methods through the analysis of metrics and experimental conditions

inferred← citeshttps://doi.org/10.1063/5.0329199openalex-snapshot

Rewiring transformers for exploit likelihood prediction of cyber vulnerabilities

inferred← citeshttps://doi.org/10.1080/09540091.2024.2312104openalex-snapshot

Dynamic fuzz testing of UAV configuration parameters based on dual guidance of fitness and coverage

inferred← citeshttps://doi.org/10.1109/access.2020.2973043openalex-snapshot

FIRMCORN: Vulnerability-Oriented Fuzzing of IoT Firmware via Optimized Virtual Execution

inferred← citeshttps://doi.org/10.1109/access.2021.3119746openalex-snapshot

A Literature Review of Using Machine Learning in Software Development Life Cycle Stages

inferred← citeshttps://doi.org/10.1109/apsec.2017.30openalex-snapshot

Exniffer: Learning to Prioritize Crashes by Assessing the Exploitability from Memory Dump

inferred← citeshttps://doi.org/10.1109/cds49703.2020.00035openalex-snapshot

Research on Business District Operation Planning Based on Machine Learning

inferred← citeshttps://doi.org/10.1109/issrew.2019.00084openalex-snapshot

Empirical Notes on the Interaction Between Continuous Kernel Fuzzing and Development

inferred← citeshttps://doi.org/10.1109/isssr61934.2024.00024openalex-snapshot

A Comprehensive Review of Learning-based Fuzz Testing Techniques

inferred← citeshttps://doi.org/10.1109/tdsc.2022.3182373openalex-snapshot

xFuzz: Machine Learning Guided Cross-Contract Fuzzing

inferred← citeshttps://doi.org/10.1109/tencon.2018.8650188openalex-snapshot

Assisting Vulnerability Detection by Prioritizing Crashes with Incremental Learning

inferred← citeshttps://doi.org/10.1109/tse.2024.3354739openalex-snapshot

Range Specification Bug Detection in Flight Control System Through Fuzzing

inferred← citeshttps://doi.org/10.1145/3321705.3329840openalex-snapshot

An Empirical Study of Prioritizing JavaScript Engine Crashes via Machine Learning

inferred← citeshttps://doi.org/10.1145/3510003.3510084openalex-snapshot

Control parameters considered harmful

inferred← citeshttps://doi.org/10.1145/3512850.3512862openalex-snapshot

MLPNeuzz: A Novel Neural Program Smoothing Method Based on Multi-Layer Perceptron

inferred← citeshttps://doi.org/10.1145/3529757openalex-snapshot

A Survey on Data-driven Software Vulnerability Assessment and Prioritization

inferred← citeshttps://doi.org/10.1145/3648610openalex-snapshot

A Survey on Software Vulnerability Exploitability Assessment

inferred← citeshttps://doi.org/10.1371/journal.pone.0237749openalex-snapshot

A systematic review of fuzzing based on machine learning techniques

inferred← citeshttps://doi.org/10.48550/arxiv.1809.01266openalex-snapshot

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

inferred← citeshttps://doi.org/10.48550/arxiv.2005.13299openalex-snapshot

Machine Learning for Software Engineering: A Systematic Mapping

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