Evidence map›Paper›PMID 42404426›Full record

ArticleOpen research Europe2026

From Simulation to Healthcare: KINAITICS' AI Framework for Cyber-Physical Security.

Paolo Marcheschi, Maria Pisani, Stefano Dalmiani

Abstract read
In one paragraph

Article in Open research Europe, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Paolo MarcheschiBioInformatica Traslazionale ed eHealth (BITE), Fondazione Toscana Gabriele Monasterio per la Ricerca Medica e di Sanita Pubblica, Pisa, Tuscany, 56011, Italy.ORCID https://orcid.org/0000-0001-6682-705X
Maria PisaniBioInformatica Traslazionale ed eHealth (BITE), Fondazione Toscana Gabriele Monasterio per la Ricerca Medica e di Sanita Pubblica, Pisa, Tuscany, 56011, Italy.
Stefano DalmianiBioInformatica Traslazionale ed eHealth (BITE), Fondazione Toscana Gabriele Monasterio per la Ricerca Medica e di Sanita Pubblica, Pisa, Tuscany, 56011, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing integration of Artificial Intelligence (AI) into Cyber-Physical Systems (CPS) presents complex cybersecurity challenges, necessitating a reevaluation of traditional threat assessment. The KINAITICS project addresses these evolving threats by conducting in-depth research into cyber-kinetic attacks, where malicious cyber activities manifest as real-world physical disruptions. The project is also dedicated to developing resilient, AI-driven defense mechanisms. This paper outlines KINAITICS' foundational work, including the creation of a tailored KINAITICS Threat Matrix (KTM). This innovative framework systematically identifies, categorizes, and assesses threats unique to AI-integrated CPS. The paper details the KTM's practical application across five high-stakes use cases, ranging from safeguarding nuclear facility simulations to protecting electronic health record (EHR) systems from sophisticated phishing attacks. A central focus of the KINAITICS project is the rigorous development and evaluation of both offensive and defensive AI tools. These tools are designed to investigate, understand, and mitigate the multifaceted threats posed by cyber-kinetic adversaries. The overarching objective is to significantly enhance the resilience of critical infrastructures against advanced cyber-physical threats, ensuring the continued safety, security, and operational integrity of systems vital to modern society.

Indexed as

Artificial Intelligence (AI)Behavioral analysisCritical infrastructure Structural Health Monitoring (SHM)Cyber-Physical Systems (CPS)CybersecurityData scrapingElectronic Health Records (EHR)Explainable AI (XAI)Human-in-the-loop (HITL)Social engineering Bot detectionThreat matrix

Identifiers

PMID42404426
PMCPMC13324364

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.