Evidence map›Paper›PMID 41839956›Full record

ArticleScientific reports2026

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

Basant Kumar, Shashi Kant Gupta, Rashmi Dwivedi, Deema Mohammed Alsekai, Diaa Salama AbdElminaam, Ozlem Kilickaya

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Basant KumarLincoln University College, 47301, Petaling Jaya, Selangor, Malaysia.
Shashi Kant GuptaLincoln University College, 47301, Petaling Jaya, Selangor, Malaysia.
Rashmi DwivediMuscat University, Muscat, Oman.
Deema Mohammed AlsekaiDepartment of Information Technology,College of Computer and Information Sciences , Princess Nourah Bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia. dmalsekait@pnu.edu.sa.
Diaa Salama AbdElminaamFaculty of Computing and IT, Sohar University, Sohar, Oman. diaa.salama@miuegypt.edu.eg.
Ozlem KilickayaUniversity of the People, Pasadena, USA. ozlem.kilickaya@uopeople.edu.

Funding

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R435), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia PNURSP2025R435
6 · The paper itself

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.

Indexed as

Artificial intelligence (AI)Backup data integrity (BDI)Cyber resilience (CR)Cyber-security (CS)Energy efficiency (EE)Green smart infrastructure (GSI)Ransomware attack (RA)

Identifiers

PMID41839956
PMCPMC13121715

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.