Artificial intelligence driven approach for securing backup data and enhancing cyber resilience in sustainable smart infrastructure

A crucial factor for smart cities, which are more vulnerable to cyber threats, is Cyber Resilience (CR). Nevertheless, the conventional frameworks didn't concentrate on assuring the Backup Data (BD) integrity before restoration, showing less resilience. Therefore, this article implements an AI-powered BD integrity verification approach for CR in smart infrastructure using Murmur Polytopes Hash (MPH). Initially, the nodes are initialized in the smart city, followed by node clustering, data security, and storage (cloud server and Interplanetary File System (IPFS) (backup)). Now, the hash code is generated and updated in the Merkle tree. Besides, to perform data collection, pre-processing, clustering, correlation heatmap generation, feature extraction, and attack classification, the proposed ransomware attack detection module is designed. If the data is attacked, then the BD verification is done using MPH. Then, the BD is restored. If the data is normal, then the data is downloaded from the cloud server. Thus, the proposed work had a high security level and accuracy of 98.45% and 98.65%, respectively, showing better resilience.

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Publication Details

Journal
Scientific Reports
Published
2026-03-16
DOI
https://doi.org/10.1038/s41598-026-37802-6
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial intelligence driven approach for securing backup data and enhancing cyber resilience in sustainable smart infrastructure

Ozlem Kilickaya, B. V. Ravi Kumar, Shilpi Gupta, Rashmi Dwivedi et al.
Scientific Reports
Smart Grid Security and Resilience
article

Artificial intelligence driven approach for securing backup data and enhancing cyber resilience in sustainable smart infrastructure

Ozlem Kilickaya, B. V. Ravi Kumar, Shilpi Gupta, Rashmi Dwivedi, Diaa Salama AbdElminaam, Deema Mohammed Alsekai
article en

Abstract

A crucial factor for smart cities, which are more vulnerable to cyber threats, is Cyber Resilience (CR). Nevertheless, the conventional frameworks didn't concentrate on assuring the Backup Data (BD) integrity before restoration, showing less resilience. Therefore, this article implements an AI-powered BD integrity verification approach for CR in smart infrastructure using Murmur Polytopes Hash (MPH). Initially, the nodes are initialized in the smart city, followed by node clustering, data security, and storage (cloud server and Interplanetary File System (IPFS) (backup)). Now, the hash code is generated and updated in the Merkle tree. Besides, to perform data collection, pre-processing, clustering, correlation heatmap generation, feature extraction, and attack classification, the proposed ransomware attack detection module is designed. If the data is attacked, then the BD verification is done using MPH. Then, the BD is restored. If the data is normal, then the data is downloaded from the cloud server. Thus, the proposed work had a high security level and accuracy of 98.45% and 98.65%, respectively, showing better resilience.

Scientific Reports
Princess Nourah bint Abdulrahman University (SA), Udayana University (ID), Alliance University (IN), Jadara University (JO), Muscat College (OM), Lincoln University College (MY), Modern College of Business and Science (OM), Sohar University (OM), Chitkara University (IN)
Princess Nourah Bint Abdulrahman University
Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Smart Grid Security and Resilience
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