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Enterprise Security Patch Management with Deep Reinforcement Learning

https://doi.org/10.2139/ssrn.4816905
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Outgoing claims: the papers this work cites, builds on, or argues with.

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A multi-target approach to estimate software vulnerability characteristics and severity scores
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Human-level control through deep reinforcement learning
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Update now or later? Effects of experience, cost, and risk preference on update decisions
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Enhancing Vulnerability Prioritization: Data-Driven Exploit Predictions with Community-Driven Insights
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Common Vulnerability Scoring System
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152 Simple Steps to Stay Safe Online: Security Advice for Non-Tech-Savvy Users
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Towards Optimal Triage and Mitigation of Context-Sensitive Cyber Vulnerabilities
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Beyond heuristics
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Characterizing and Modeling Patching Practices of Industrial Control Systems
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Characterizing and Modeling Patching Practices of Industrial Control Systems
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VULCON
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Fighting N-day vulnerabilities with automated CVSS vector prediction at disclosure
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An Approach to Discover and Assess Vulnerability Severity Automatically in Cyber-Physical Systems
inferredcites →https://doi.org/10.1145/3436242openalex-extracted
Exploit Prediction Scoring System (EPSS)
inferredcites →https://doi.org/10.1145/3529757openalex-extracted
A Survey on Data-driven Software Vulnerability Assessment and Prioritization
inferredcites →https://doi.org/10.1145/3555087openalex-extracted
Why, How and Where of Delays in Software Security Patch Management: An Empirical Investigation in the Healthcare Sector
inferredcites →https://doi.org/10.1145/3613904.3642456openalex-extracted
Not as easy as just update: Survey of System Administrators and Patching Behaviours
inferredcites →https://doi.org/10.1287/ijoc.2014.0638openalex-extracted
Optimal Policies for Security Patch Management
inferredcites →https://doi.org/10.1287/mksc.2022.1403openalex-extracted
Dynamic Coupon Targeting Using Batch Deep Reinforcement Learning: An Application to Livestream Shopping
inferredcites →https://doi.org/10.1287/mnsc.1070.0794openalex-extracted
Security Patch Management: Share the Burden or Share the Damage?
inferredcites →https://doi.org/10.1287/msom.2020.0939openalex-extracted
A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization
inferredcites →https://doi.org/10.1371/journal.pone.0228439openalex-extracted
FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm
inferredcites →https://doi.org/10.1609/aaai.v32i1.11428openalex-extracted
DarkEmbed: Exploit Prediction With Neural Language Models
inferredcites →https://doi.org/10.1631/fitee.1900533openalex-extracted
Deep reinforcement learning: a survey
inferredcites →https://doi.org/10.4230/oasics.dx.2024.16openalex-extracted
Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1509.02971openalex-extracted
Continuous control with deep reinforcement learning
inferredcites →https://doi.org/10.48550/arxiv.1602.01783openalex-extracted
Asynchronous Methods for Deep Reinforcement Learning
inferredcites →https://doi.org/10.6028/nist.sp.800-40r3openalex-extracted
Guide to Enterprise Patch Management Technologies
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