Testbeds and evaluation frameworks for anomaly detection within built environments: a systematic review

Alosaimi, Mohammed, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646 and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346 2025. Testbeds and evaluation frameworks for anomaly detection within built environments: a systematic review. ACM Computing Surveys 57 (9) , 227. 10.1145/3722213

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Abstract

The Internet of Things (IoT) has revolutionized built environments by enabling seamless data exchange among devices such as sensors, actuators, and computers. However, IoT devices often lack robust security mechanisms, making them vulnerable to cyberattacks, privacy breaches, and operational anomalies caused by environmental factors or device faults. While anomaly detection techniques are critical for securing IoT systems, the role of testbeds in evaluating these techniques has been largely overlooked. This systematic review addresses this gap by treating testbeds as first-class entities essential for the standardized evaluation and validation of anomaly detection methods in built environments. We analyze testbed characteristics, including infrastructure configurations, device selection, user-interaction models, and methods for anomaly generation. We also examine evaluation frameworks, highlighting key metrics and integrating emerging technologies such as edge computing and 5G networks into testbed design. By providing a structured and comprehensive approach to testbed development and evaluation, this paper offers valuable guidance to researchers and practitioners in enhancing the reliability and effectiveness of anomaly detection systems. Our findings contribute to the development of more secure, adaptable, and scalable IoT systems, ultimately improving the security, resilience, and efficiency of built environments.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Association for Computing Machinery (ACM)
ISSN:	0360-0300
Date of First Compliant Deposit:	10 April 2025
Date of Acceptance:	1 March 2025
Last Modified:	10 Apr 2025 09:00
URI:	https://orca.cardiff.ac.uk/id/eprint/176813

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