Analysis of a 2D Representation for CPS Anomaly Detection in a Context-Based Security Framework

Author:

Baldoni Sara,Carli Marco,Battisti Federica

Abstract

In this contribution, a flexible context-based security framework is proposed by exploring two types of context: distributed and local. While the former consists in processing information from a set of spatially distributed sources, the second accounts for the local environment surrounding the monitored system. The joint processing of these two types of information allows the identification of the anomaly cause, differentiating between natural and attack-related events, and the suggestion of the best mitigation strategy. In this work, the proposed framework is applied the Cyber Physical Systems scenario. More in detail, we focus on the distributed context analysis investigating the definition of a 2D representation of network traffic data. The suitability of four representation variables has been evaluated, and the variable selection has been performed.

Publisher

Frontiers Media SA

Reference27 articles.

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1. A context-based framework for enhancing GNSS performance and security;2023 IEEE/ION Position, Location and Navigation Symposium (PLANS);2023-04-24

2. Unsupervised Network Anomaly Detection by Learning on 2D Data Representations;2022 9th Swiss Conference on Data Science (SDS);2022-06

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