Provably secured and lightweight authenticated encryption protocol in machine-to-machine communication in industry 4.0

Ashrif, Fatma Foad; Sundararajan, Elankovan A.; Hasan, Mohammad Kamrul; Ahmad, Rami; Hashim, Aisha-Hassan Abdalla; Abu Talib, Azhar

doi:10.1016/j.comcom.2024.02.008

Computer Communications

2024

DOI: 10.1016/j.comcom.2024.02.008

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Provably secured and lightweight authenticated encryption protocol in machine-to-machine communication in industry 4.0

Fatma Foad Ashrif,

Elankovan A. Sundararajan,

Mohammad Kamrul Hasan

et al.

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Cited by 3 publications

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Smart remote sensing network for disaster management: an overview

Ahmad

2024

Telecommun Syst

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Smart remote sensing network for disaster management: an overview

Ahmad

2024

Telecommun Syst

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Secured lightweight authentication for 6LoWPANs in machine-to-machine communications

Ashrif,

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Computers & Security

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Online Adaptive Kalman Filtering for Real-Time Anomaly Detection in Wireless Sensor Networks

Ahmad,

Alkhammash

2024

Sensors

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Wireless sensor networks (WSNs) are essential for a wide range of applications, including environmental monitoring and smart city developments, thanks to their ability to collect and transmit diverse physical and environmental data. The nature of WSNs, coupled with the variability and noise sensitivity of cost-effective sensors, presents significant challenges in achieving accurate data analysis and anomaly detection. To address these issues, this paper presents a new framework, called Online Adaptive Kalman Filtering (OAKF), specifically designed for real-time anomaly detection within WSNs. This framework stands out by dynamically adjusting the filtering parameters and anomaly detection threshold in response to live data, ensuring accurate and reliable anomaly identification amidst sensor noise and environmental changes. By highlighting computational efficiency and scalability, the OAKF framework is optimized for use in resource-constrained sensor nodes. Validation on different WSN dataset sizes confirmed its effectiveness, showing 95.4% accuracy in reducing false positives and negatives as well as achieving a processing time of 0.008 s per sample.

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Provably secured and lightweight authenticated encryption protocol in machine-to-machine communication in industry 4.0

Cited by 3 publications

References 24 publications

Smart remote sensing network for disaster management: an overview

Smart remote sensing network for disaster management: an overview

Secured lightweight authentication for 6LoWPANs in machine-to-machine communications

Online Adaptive Kalman Filtering for Real-Time Anomaly Detection in Wireless Sensor Networks

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