Search Results for author: Martin Arlitt

Found 3 papers, 1 papers with code

STAN: Synthetic Network Traffic Generation with Generative Neural Models

1 code implementation27 Sep 2020 Shengzhe Xu, Manish Marwah, Martin Arlitt, Naren Ramakrishnan

We evaluate the performance of STAN in terms of the quality of data generated, by training it on both a simulated dataset and a real network traffic data set.

Anomaly Detection

Attention-Based Self-Supervised Feature Learning for Security Data

no code implementations24 Mar 2020 I-Ta Lee, Manish Marwah, Martin Arlitt

While applications of machine learning in cyber-security have grown rapidly, most models use manually constructed features.

Anomaly Detection BIG-bench Machine Learning

ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications

no code implementations1 Dec 2019 Xiao Zhang, Manish Marwah, I-Ta Lee, Martin Arlitt, Dan Goldwasser

In this paper, we introduce Anomaly Contribution Explainer or ACE, a tool to explain security anomaly detection models in terms of the model features through a regression framework, and its variant, ACE-KL, which highlights the important anomaly contributors.

Anomaly Detection

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