# On the use of neurosymbolic AI for defending against cyber attacks

arXiv: https://arxiv.org/abs/2408.04996 · HTML: https://mlsanity.com/paper/2408.04996/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 88 references that are in the map.
- First posted on arXiv 9 Aug 2024.

## Builds on (most cited first, 30 of 30)

- [GNNExplainer: Generating Explanations for Graph Neural Networks](https://mlsanity.com/paper/1903.03894/) (2019)
- [Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://mlsanity.com/paper/2306.08302/) (2023)
- [Neural Probabilistic Logic Programming in DeepProbLog](https://mlsanity.com/paper/1907.08194/) (2019)
- [The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision](https://mlsanity.com/paper/1904.12584/) (2019)
- [Learning Explanatory Rules from Noisy Data](https://mlsanity.com/paper/1711.04574/) (2017)
- [Logic Tensor Networks](https://mlsanity.com/paper/2012.13635/) (2020)
- [Logical Neural Networks](https://mlsanity.com/paper/2006.13155/) (2020)
- [NeurASP: Embracing Neural Networks into Answer Set Programming](https://mlsanity.com/paper/2307.07700/) (2023)
- [DeepStochLog: Neural Stochastic Logic Programming](https://mlsanity.com/paper/2106.12574/) (2021)
- [Ontology Reasoning with Deep Neural Networks](https://mlsanity.com/paper/1808.07980/) (2018)
- [NeuPSL: Neural Probabilistic Soft Logic](https://mlsanity.com/paper/2205.14268/) (2022)
- [AttacKG: Constructing Technique Knowledge Graph from Cyber Threat Intelligence Reports](https://mlsanity.com/paper/2111.07093/) (2021)
- [Neurosymbolic Reinforcement Learning and Planning: A Survey](https://mlsanity.com/paper/2309.01038/) (2023)
- [Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions](https://mlsanity.com/paper/2208.11561/) (2022)
- [PyReason: Software for Open World Temporal Logic](https://mlsanity.com/paper/2302.13482/) (2023)
- [AGIR: Automating Cyber Threat Intelligence Reporting with Natural Language Generation](https://mlsanity.com/paper/2310.02655/) (2023)
- [SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection](https://mlsanity.com/paper/2305.00550/) (2023)
- [Neuro-Symbolic Learning of Answer Set Programs from Raw Data](https://mlsanity.com/paper/2205.12735/) (2022)
- [Reliable Natural Language Understanding with Large Language Models and Answer Set Programming](https://mlsanity.com/paper/2302.03780/) (2023)
- [Automatic Mapping of Unstructured Cyber Threat Intelligence: An Experimental Study](https://mlsanity.com/paper/2208.12144/) (2022)
- [Temporal Answer Set Programming on Finite Traces](https://mlsanity.com/paper/1804.10227/) (2018)
- [STIXnet: A Novel and Modular Solution for Extracting All STIX Objects in CTI Reports](https://mlsanity.com/paper/2303.09999/) (2023)
- [A review of knowledge graph application scenarios in cyber security](https://mlsanity.com/paper/2204.04769/) (2022)
- [An Assessment of the Usability of Machine Learning Based Tools for the Security Operations Center](https://mlsanity.com/paper/2012.09013/) (2020)
- [Threat Actor Type Inference and Characterization within Cyber Threat Intelligence](https://mlsanity.com/paper/2103.02301/) (2021)
- [Multi-Stage Attack Detection via Kill Chain State Machines](https://mlsanity.com/paper/2103.14628/) (2021)
- [Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods](https://mlsanity.com/paper/2212.13991/) (2022)
- [dPASP: A Comprehensive Differentiable Probabilistic Answer Set Programming Environment For Neurosymbolic Learning and Reasoning](https://mlsanity.com/paper/2308.02944/) (2023)
- [LLMs Perform Poorly at Concept Extraction in Cyber-security Research Literature](https://mlsanity.com/paper/2312.07110/) (2023)
- [Cybersecurity Playbook Sharing with STIX 2.1](https://mlsanity.com/paper/2203.04136/) (2022)

## Built on by (most cited first, 3 of 3)

- [Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities](https://mlsanity.com/paper/2509.06921/) (2025)
- [Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey](https://mlsanity.com/paper/2508.07163/) (2025)
- [RefinementEngine: Automating Intent-to-Device Filtering Policy Deployment under Network Constraints](https://mlsanity.com/paper/2604.01627/) (2026)

## Abstract (arXiv)

It is generally accepted that all cyber attacks cannot be prevented, creating a need for the ability to detect and respond to cyber attacks. Both connectionist and symbolic AI are currently being used to support such detection and response. In this paper, we make the case for combining them using neurosymbolic AI. We identify a set of challenges when using AI today and propose a set of neurosymbolic use cases we believe are both interesting research directions for the neurosymbolic AI community and can have an impact on the cyber security field. We demonstrate feasibility through two proof-of-concept experiments.