Design a Secure Routing and Monitoring Framework Based on Hybrid Optimization for IoT-Based Wireless Sensor Networks

Rahmani, Mohammad Khalid Imam; Mohammed, Moizuddin; Irshad, Reyazur Rashid; Yasmin, Sadaf; Mishra, Sonali; Asopa, Pooja; Islam, Asharul; Ahmad, Sultan; Ali, Aleem

doi:10.1166/jno.2023.3397

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…Before Surveillance & Monitoring: Homeowners can remotely monitor and identify possible security breaches by using drones fitted with cameras to capture real-time footage of their living spaces. [14] Patrol and Reaction: Drones can be set up to automatically patrol pre-established routes throughout the property, reacting quickly and nimbly to any security warnings or possible threats.…”

Section: Applications Of Drones In Smart Home Securitymentioning

confidence: 99%

Enhancing Home Security with AI-Driven Drone Surveillance

Tallapaneni,

Kumar,

Gautam

et al. 2024

Preprint

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Section: Applications Of Drones In Smart Home Securitymentioning

confidence: 99%

Enhancing Home Security with AI-Driven Drone Surveillance

Tallapaneni,

Kumar,

Gautam

et al. 2024

Preprint

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Enhanced Nanoelectronic Detection and Classification of Motor Imagery Electroencephalogram Signal Using a Hybrid Framework

Rahmani,

Ahmad,

Hussain

et al. 2023

Journal of Nanoelectronics and Optoelectronics

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Motor imagery-based electroencephalogram (MI-EEG) signal classification plays a vital role in the development of brain-computer interfaces (BCIs), particularly in providing assistance to individuals with motor disabilities. In this study, we introduce an innovative and optimized hybrid framework designed for the robust classification of MI-EEG signals. Our approach combines the power of a Deep Convolutional Neural Network (DCRNN) with the efficiency of the Ant Lion Optimization (ALO) algorithm. This framework consists of four key phases: data acquisition, pre-processing, feature engineering, and classification. To enhance the signal quality, our work incorporates adaptive filtering and independent component analysis (ICA) during the pre-processing phase. Feature extraction is carried out using a deep autoencoder. For classification, we employ the DCRNN, and further enhance its performance with the ALO algorithm to optimize training and classification processes. The study is implemented in MATLAB and evaluated using the PhysioNet dataset. Experimental results demonstrate the effectiveness of our proposed method, achieving an impressive accuracy of 99.32%, a precision of 99.41%, a recall of 99.29%, and an f-measure of 99.32%. These results surpass the performance of existing classification strategies, highlighting the potential of our hybrid framework in MI-EEG signal classification for various BCI applications.

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Security in Optical Wireless Communication-Based Vehicular Ad Hoc Networks Using Signature and Certificate Revocation

Rahmani,

Arif,

Ahmad

et al. 2024

Journal of Nanoelectronics and Optoelectronics

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A vehicular ad hoc network is a capable method of making possible road well-being, traffic supervision, as well as information distribution for driving users and travelers. One definitive objective in the blueprint of this type of network is to refuse to accept a variety of malevolent mistreatment and security assaults. The paper analyzed the existing procedure, which has covered the ways of offering security duties and conserving user solitude in the context of wireless access in vehicular environments (WAVE) applications. To make the standards more realistic, it considers techniques of certificate revocation and conditional privacy preservation. These techniques are found to be the most promising ones in vehicular ad hoc networks (VANET). Therefore, a group of narrative security methods is proposed for the safe implementation of the techniques of certificate revocation and conditional privacy preservation. For enhancement of security, the paper proposes that the message should be encapsulated with a proper certificate and be duly signed. For faster communication, we propose the use of optical wireless communication (OWC) between an onboard unit (OBU) and a roadside unit (RSU).

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Design a Secure Routing and Monitoring Framework Based on Hybrid Optimization for IoT-Based Wireless Sensor Networks

Cited by 4 publications

References 28 publications

Enhancing Home Security with AI-Driven Drone Surveillance

Enhancing Home Security with AI-Driven Drone Surveillance

Enhanced Nanoelectronic Detection and Classification of Motor Imagery Electroencephalogram Signal Using a Hybrid Framework

Security in Optical Wireless Communication-Based Vehicular Ad Hoc Networks Using Signature and Certificate Revocation

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