WIPP - Towards a Delay-Sensitive Provenance Framework for Operational Technology Networks

In the rapidly advancing age of cybersecurity, detecting and mitigating advanced cyber threats is a critical challenge. This work-in-progress paper (WIPP) explores the use of low-level system log auditing for effective threat detection, focusing on the innovative use of provenance-based techniques. We focus our attention on three advanced systems —ShadeWatcher, SPADE, and UNICORN, which leverage data provenance to enhance cyber-threat detection capabilities. By analyzing their methods and integrating their strengths, we propose a delay-sensitive audit tracking system suitable for critical infrastructure networks. Our system aims to detect anomalous activities with high precision and reduce false alarms within a guaranteed time bound, thus providing robust protection against cyber threats.

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Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1109/rws62797.2024.10799471
Primary Topic
Service-Oriented Architecture and Web Services
Type
article
Field-Weighted Citation Impact
0.00

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article

WIPP - Towards a Delay-Sensitive Provenance Framework for Operational Technology Networks

Deepak K. Tosh, Christopher Porras
Service-Oriented Architecture and Web Services
article

WIPP - Towards a Delay-Sensitive Provenance Framework for Operational Technology Networks

Deepak K. Tosh, Christopher Porras
article en

Abstract

In the rapidly advancing age of cybersecurity, detecting and mitigating advanced cyber threats is a critical challenge. This work-in-progress paper (WIPP) explores the use of low-level system log auditing for effective threat detection, focusing on the innovative use of provenance-based techniques. We focus our attention on three advanced systems —ShadeWatcher, SPADE, and UNICORN, which leverage data provenance to enhance cyber-threat detection capabilities. By analyzing their methods and integrating their strengths, we propose a delay-sensitive audit tracking system suitable for critical infrastructure networks. Our system aims to detect anomalous activities with high precision and reduce false alarms within a guaranteed time bound, thus providing robust protection against cyber threats.

The University of Texas at El Paso (US)
National Science Foundation
Openalex Percentile: Top 63%
Service-Oriented Architecture and Web Services
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