A novel cloud-assisted framework for consumer internet of things based on lanner swarm optimization algorithm in smart healthcare systems

Arulkumar, V.; Aruna, M.; Prakash, D.; Amanullah, M.; Somasundaram, K.; Thavasimuthu, Rajendran

doi:10.1007/s11042-024-18846-0

Cited by 4 publications

References 33 publications

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Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment

Karim,

Varela-Aldás,

Ishak

et al. 2024

Sci Rep

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With the fast-growing interconnection of smart technologies, the Industrial Internet of Things (IIoT) has revolutionized how industries work by connecting devices and sensors and automating regular operations via the Internet of Things (IoTs). IoT devices provide seamless diversity and connectivity in different application domains. This system and its transmission channels are subjected to targeted cyberattacks due to their round-the-clock connectivity. Accordingly, a multilevel security solution is needed to safeguard the industrial system. By analyzing the data packet, the Intrusion Detection System (IDS) counteracts the cyberattack for the targeted attack in the IIoT platform. Various research has been undertaken to address the concerns of cyberattacks on IIoT networks using machine learning (ML) and deep learning (DL) approaches. This study introduces a new Bayesian Machine Learning with the Sparrow Search Algorithm for Cyberattack Detection (BMLSSA-CAD) technique in the IIoT networks. The proposed BMLSSA-CAD technique aims to enhance security in IIoT networks by detecting cyberattacks. In the BMLSSA-CAD technique, the min-max scaler normalizes the input dataset. Additionally, the method utilizes the Chameleon Optimization Algorithm (COA)-based feature selection (FS) approach to identify the optimal feature set. The BMLSSA-CAD technique uses the Bayesian Belief Network (BBN) model for cyberattack detection. The hyperparameter tuning process employs the sparrow search algorithm (SSA) model to enhance the BBN model performance. The performance of the BMLSSA-CAD method is examined using UNSWNB51 and UCI SECOM datasets. The experimental validation of the BMLSSA-CAD method highlighted superior accuracy outcomes of 97.84% and 98.93% compared to recent techniques on the IIoT platform.

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Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment

Karim,

Varela-Aldás,

Ishak

et al. 2024

Sci Rep

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A Comprehensive Introduction to Cloud Computing Revolution

Ashwini,

Balasubramaniam,

Kadry

2024

Advances in Healthcare Information Systems and Administration

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Cloud computing can be considered as a revolution of how commercial enterprises obtain and use computational services. In a narrow sense, cloud computing means the rent of services over the Internet with its characteristics such as storage, computing, and applications. An organization can host an application in minutes and run it without having to invest a week or a month in procuring the necessary hardware and setting it up with the help of cloud. This is made possible by the flexibility brought about by pay as you go, eliminating cases where firms incur bills in resources they did not or will not require. Privacy is an essential aspect within the cloud computing that is still emerging. This is done through nurturance of proper encryption, security check and risk analysis, creation of organizational standards and compliance to other standards. These risks should be well understood by all organizations to make sure that measures are employed to make cloud security not to hinder the adoption of this technology that holds great promises for the growth of their business processes.

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New Trust Based Smart Data Forwarding Mechanism in Vehicular Delay Tolerant Network

Jangra,

Pandit

2024

JMC

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Vehicular Delay Tolerant Network (VDTN) is the growing field with a considerable possibility to handle future wireless application’s requirements. Using vehicles for the data communication purpose can be contemplated as a substitute for the wired and wireless systems. This paper proposes a trust-based data forwarding mechanism for Vehicular Delay Tolerant Network (VDTN). Data forwarding in VDTN requires every vehicular or stationary node to participate in data forwarding. But some time malicious nodes show non-cooperative behaviour in data forwarding. Therefore, malicious nodes must be identified specifically to accelerate the data forwarding. A threshold based social skeleton membership process along with new trust-based data forwarding mechanism is proposed in this paper. We reveal that the social skeleton members perform better in data forwarding in terms of data delivery ratio, data delay and data overhead. Simulation results demonstrate that the trust-based data forwarding improves the data delivery ratio with trust-based data forwarding approach. After simulation a comparative analysis of two different scenarios is presented with epidemic routing, prophet routing and spray and wait routing.

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A novel cloud-assisted framework for consumer internet of things based on lanner swarm optimization algorithm in smart healthcare systems

Cited by 4 publications

References 33 publications

Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment

Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment

A Comprehensive Introduction to Cloud Computing Revolution

New Trust Based Smart Data Forwarding Mechanism in Vehicular Delay Tolerant Network

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