Evidence map›Paper›PMID 40871830›Full record

ArticleSensors (Basel, Switzerland)2025

Cybersecurity Baseline and Risk Mitigation for Open Data in IoT-Enabled Smart City Systems: A Case Study of the Hradec Kralove Region.

Vladimir Sobeslav, Josef Horalek

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 authors.

Vladimir SobeslavFaculty of Informatics and Management, University of Hradec Kralove, 500 03 Hradec Kralove, Czech Republic.ORCID 0000-0002-0917-5988
Josef HoralekFaculty of Informatics and Management, University of Hradec Kralove, 500 03 Hradec Kralove, Czech Republic.ORCID 0000-0003-3534-026X

Funding

Ministry of the Interior of the Czech Republic Application of Artificial Intelligence for Ensuring Cyber Security in Smart City, n. VJ02010016.
6 · The paper itself

Abstract

This paper explores cybersecurity risk modeling for open data in Smart City environments, with a specific case study focused on the Hradec Kralove Region. The goal is to establish a cybersecurity baseline through automated analysis using extended BPMN modeling, complemented by Business Impact Analysis (BIA). The approach identifies critical data flows and quantifies the impact of disruptions in terms of Recovery Time Objective (RTO), Maximum Tolerable Period of Disruption (MTPD), and Maximum Tolerable Data Loss (MTDL). A framework for automated risk mitigation selection is proposed. Results demonstrate the effectiveness of combining process mapping with security requirements to prioritize protections for Smart City data. As an example from the open data domain, the visualization-publishing process was found to tolerate an outage of up to one week, but required high confidentiality and integrity. The maximum tolerable data loss (MTDL) was set at 24 h, leading to the selection of measures such as encryption, access control, and regular backups. This structured methodology enhances data availability and integrity, supporting resilient urban digital infrastructure.

Indexed as

BPMN modelingBusiness Impact Analysis (BIA)data integrityMTDLopen datarisk mitigationRTOSmart City cybersecurity

Identifiers

PMID40871830
PMCPMC12390161

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.