# Unified Host and Network Data Set

arXiv: https://arxiv.org/abs/1708.07518 · HTML: https://mlsanity.com/paper/1708.07518/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2017.

## Built on by (most cited first, 11 of 11)

- [Dynamic Network Reconfiguration for Entropy Maximization using Deep Reinforcement Learning](https://mlsanity.com/paper/2205.13578/) (2022)
- [Local2Global: A distributed approach for scaling representation learning on graphs](https://mlsanity.com/paper/2201.04729/) (2022)
- [Deception for Cyber Defence: Challenges and Opportunities](https://mlsanity.com/paper/2208.07127/) (2022)
- [Learning to Detect: A Data-driven Approach for Network Intrusion Detection](https://mlsanity.com/paper/2108.08394/) (2021)
- [Contextual Learning for Anomaly Detection in Tabular Data](https://mlsanity.com/paper/2509.09030/) (2025)
- [Secure solutions for Smart City Command Control Centre using AIOT](https://mlsanity.com/paper/2108.00003/) (2021)
- [DeepTaskAPT: Insider APT detection using Task-tree based Deep Learning](https://mlsanity.com/paper/2108.13989/) (2021)
- [A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection](https://mlsanity.com/paper/2510.26307/) (2025)
- [TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation](https://mlsanity.com/paper/2601.15663/) (2026)
- [Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation](https://mlsanity.com/paper/2606.18190/) (2026)
- [Hybrid Latent-Structural Fusion (HLSF) for Cyber Anomaly Detection](https://mlsanity.com/paper/2607.18479/) (2026)

## Abstract (arXiv)

The lack of data sets derived from operational enterprise networks continues to be a critical deficiency in the cyber security research community. Unfortunately, releasing viable data sets to the larger com- munity is challenging for a number of reasons, primarily the difficulty of balancing security and privacy concerns against the fidelity and utility of the data. This chapter discusses the importance of cyber secu- rity research data sets and introduces a large data set derived from the operational network environment at Los Alamos National Laboratory. The hope is that this data set and associated discussion will act as a catalyst for both new research in cyber security as well as motivation for other organizations to release similar data sets to the community.