Anomaly Detection in Cloud Using Hexabullus Optimisation-Enabled Fuzzy Classifier with Smart Contract-Enabled Secure Communication

F. Sammy and S. Maria Celestin Vigila ()
Additional contact information
F. Sammy: Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India
S. Maria Celestin Vigila: ��Department of Information Technology, Noorul Islam Centre for Higher Education, Kumaracoil 629180, Tamil Nadu, India

Journal of Information & Knowledge Management (JIKM), 2024, vol. 23, issue 01, 1-25

Abstract: Cloud computing forms a mainstream in the emerging field of Internet of Things (IoT) networks, which provides high storage and access to data whenever needed. The cloud architecture is highly vulnerable to various anomalies due to the centralised process that has the capability of ruining the reputation or causing the loss of trust in an organisation. Preventing anomalies in cloud architecture extends the lifetime of the system and increases privacy preservation. In this research, blockchain technology is adopted for facilitating secure communication in the network, and anomaly detection is performed using the proposed Hexabullus optimisation-based Fuzzy classifier based on the entropy-based rules. The importance of this research relies on the calculation of entropy and anomaly detection using optimal rules generated using the proposed hexabullus optimisation. The experimental results show that the proposed blockchain-enabled cloud architecture prevents the occurrence of attacks more efficiently. The proposed hexabullus optimisation-based anomaly detection is evaluated with existing methods that attained an improved accuracy of 88%, precision of 88%, and recall of 90%, which is highly efficient in rendering the secure communication of the data in the cloud.

Keywords: Cloud computing; anomalies; blockchain; fuzzy if-then rule; hexabullus optimisation; entropy (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219649223500582
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:jikmxx:v:23:y:2024:i:01:n:s0219649223500582

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219649223500582

Access Statistics for this article

Journal of Information & Knowledge Management (JIKM) is currently edited by Professor Suliman Hawamdeh

More articles in Journal of Information & Knowledge Management (JIKM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().