A Secure and Energy-Efficient Cross-Layer Network Architecture for the Internet of Things

A secure and energy-efficient network architecture is essential due to the rapid proliferation of Internet of Things (IoT) devices in critical sectors such as healthcare, smart cities, and industrial automation. In this paper, we propose a secure and energy-efficient cross-layer IoT architecture. The security features and energy-saving techniques across various open-system interconnected protocol layers are incorporated in the proposed architecture. The improved security and energy efficiency are achieved using the lightweight Speck and Present ciphers, as well as adaptive communication strategies. The system performance is evaluated by testbeds and extensive simulation experiments using Cooja (Contiki operating systems) and NS-3. The simulation results obtained show a 95% attack mitigation effectiveness, 30% reduction in energy usage, and 95% packet delivery ratio. In a 20-node network scenario, Speck uses 5.2% less radio power than the Advanced Encryption Standard (AES), making it the best tradeoff among the investigated encryption techniques. The NS-3 simulation results confirm that lightweight encryption, such as Present and Speck, uses much less power than the traditional AES, which makes them more appropriate for IoT contexts with limited energy. The scalability across various IoT contexts is ensured through a hybrid assessment approach that combines hardware testbeds and simulation for system validation. Our research findings highlight opportunities for advancing IoT systems toward secure and energy-efficient smart ecosystems.

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Publication Details

Journal
Sensors
Published
2025-05-30
DOI
https://doi.org/10.3390/s25113457
Citations
4
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
4.46
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article

A Secure and Energy-Efficient Cross-Layer Network Architecture for the Internet of Things

Shahbaz Pervez, Mahsa Mohaghegh, Nurul I. Sarkar, Robert Morados et al.
4 citations
Sensors
IoT and Edge/Fog Computing
4.46
article

A Secure and Energy-Efficient Cross-Layer Network Architecture for the Internet of Things

Shahbaz Pervez, Mahsa Mohaghegh, Nurul I. Sarkar, Robert Morados, Rashid Mustafa
article en
4 citations

Abstract

A secure and energy-efficient network architecture is essential due to the rapid proliferation of Internet of Things (IoT) devices in critical sectors such as healthcare, smart cities, and industrial automation. In this paper, we propose a secure and energy-efficient cross-layer IoT architecture. The security features and energy-saving techniques across various open-system interconnected protocol layers are incorporated in the proposed architecture. The improved security and energy efficiency are achieved using the lightweight Speck and Present ciphers, as well as adaptive communication strategies. The system performance is evaluated by testbeds and extensive simulation experiments using Cooja (Contiki operating systems) and NS-3. The simulation results obtained show a 95% attack mitigation effectiveness, 30% reduction in energy usage, and 95% packet delivery ratio. In a 20-node network scenario, Speck uses 5.2% less radio power than the Advanced Encryption Standard (AES), making it the best tradeoff among the investigated encryption techniques. The NS-3 simulation results confirm that lightweight encryption, such as Present and Speck, uses much less power than the traditional AES, which makes them more appropriate for IoT contexts with limited energy. The scalability across various IoT contexts is ensured through a hybrid assessment approach that combines hardware testbeds and simulation for system validation. Our research findings highlight opportunities for advancing IoT systems toward secure and energy-efficient smart ecosystems.

SensorsVol. 25(11)
Auckland University of Technology (NZ), Whitecliffe College of Arts and Design (NZ)
Openalex Percentile: Top 6%
IoT and Edge/Fog Computing
4.46
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A Secure and Energy-Efficient Cross-Layer Network Architecture for the Internet of Things — Shahbaz Pervez, Mahsa Mohaghegh, et al. · Sensors (2025) | TGRS Research Map | TGRS