Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases

The rapid growth of Internet of Things (IoT) deployment has led to an unprecedented volume of interconnected, resource-constrained devices. Securing their communication is essential, especially in vehicular environments, where sensitive data exchange requires robust authentication, integrity, and co...

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Main Authors: Nikolaos Orestis Gavriilidis, Spyros T. Halkidis, Sophia Petridou
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/15/8398
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author Nikolaos Orestis Gavriilidis
Spyros T. Halkidis
Sophia Petridou
author_facet Nikolaos Orestis Gavriilidis
Spyros T. Halkidis
Sophia Petridou
author_sort Nikolaos Orestis Gavriilidis
collection DOAJ
description The rapid growth of Internet of Things (IoT) deployment has led to an unprecedented volume of interconnected, resource-constrained devices. Securing their communication is essential, especially in vehicular environments, where sensitive data exchange requires robust authentication, integrity, and confidentiality guarantees. In this paper, we present an empirical evaluation of TLS (Transport Layer Security)-enhanced MQTT (Message Queuing Telemetry Transport) on low-cost, quad-core Cortex-A72 ARMv8 boards, specifically the Raspberry Pi 4<i>B</i>, commonly used as prototyping platforms for On-Board Units (OBUs) and Road-Side Units (RSUs). Three MQTT entities, namely, the broker, the publisher, and the subscriber, are deployed, utilizing Elliptic Curve Cryptography (ECC) for key exchange and authentication and employing the AES_256_GCM and ChaCha20_Poly1305 ciphers for confidentiality via appropriately selected libraries. We quantify resource consumption in terms of CPU utilization, execution time, energy usage, memory footprint, and goodput across TLS phases, cipher suites, message packaging strategies, and both Ethernet and WiFi interfaces. Our results show that (i) TLS 1.3-enhanced MQTT is feasible on Raspberry Pi 4<i>B</i> devices, though it introduces non-negligible resource overheads; (ii) batching messages into fewer, larger packets reduces transmission cost and latency; and (iii) ChaCha20_Poly1305 outperforms AES_256_GCM, particularly in wireless scenarios, making it the preferred choice for resource- and latency-sensitive V2X applications. These findings provide actionable recommendations for deploying secure MQTT communication on an IoT platform.
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spelling doaj-art-75aeddd658d9474abe2ecbdfd8635fe62025-08-20T03:02:48ZengMDPI AGApplied Sciences2076-34172025-07-011515839810.3390/app15158398Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use CasesNikolaos Orestis Gavriilidis0Spyros T. Halkidis1Sophia Petridou2Department of Applied Informatics, University of Macedonia, 54636 Thessaloniki, GreeceDepartment of Applied Informatics, University of Macedonia, 54636 Thessaloniki, GreeceDepartment of Applied Informatics, University of Macedonia, 54636 Thessaloniki, GreeceThe rapid growth of Internet of Things (IoT) deployment has led to an unprecedented volume of interconnected, resource-constrained devices. Securing their communication is essential, especially in vehicular environments, where sensitive data exchange requires robust authentication, integrity, and confidentiality guarantees. In this paper, we present an empirical evaluation of TLS (Transport Layer Security)-enhanced MQTT (Message Queuing Telemetry Transport) on low-cost, quad-core Cortex-A72 ARMv8 boards, specifically the Raspberry Pi 4<i>B</i>, commonly used as prototyping platforms for On-Board Units (OBUs) and Road-Side Units (RSUs). Three MQTT entities, namely, the broker, the publisher, and the subscriber, are deployed, utilizing Elliptic Curve Cryptography (ECC) for key exchange and authentication and employing the AES_256_GCM and ChaCha20_Poly1305 ciphers for confidentiality via appropriately selected libraries. We quantify resource consumption in terms of CPU utilization, execution time, energy usage, memory footprint, and goodput across TLS phases, cipher suites, message packaging strategies, and both Ethernet and WiFi interfaces. Our results show that (i) TLS 1.3-enhanced MQTT is feasible on Raspberry Pi 4<i>B</i> devices, though it introduces non-negligible resource overheads; (ii) batching messages into fewer, larger packets reduces transmission cost and latency; and (iii) ChaCha20_Poly1305 outperforms AES_256_GCM, particularly in wireless scenarios, making it the preferred choice for resource- and latency-sensitive V2X applications. These findings provide actionable recommendations for deploying secure MQTT communication on an IoT platform.https://www.mdpi.com/2076-3417/15/15/8398Elliptic Curve CryptographyTLS cipher suitesInternet of ThingsMQTTVehicle to Everythingefficiency
spellingShingle Nikolaos Orestis Gavriilidis
Spyros T. Halkidis
Sophia Petridou
Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
Applied Sciences
Elliptic Curve Cryptography
TLS cipher suites
Internet of Things
MQTT
Vehicle to Everything
efficiency
title Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
title_full Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
title_fullStr Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
title_full_unstemmed Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
title_short Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
title_sort empirical evaluation of tls enhanced mqtt on iot devices for v2x use cases
topic Elliptic Curve Cryptography
TLS cipher suites
Internet of Things
MQTT
Vehicle to Everything
efficiency
url https://www.mdpi.com/2076-3417/15/15/8398
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