Evidence map›Paper›PMID 42207806›Full record

ArticlePloS one2026

Post-quantum cognitive zero trust architecture for healthcare IoT devices.

Hashim Hussain, Shailendra Mishra, Reem Alshenaifi

Abstract read
In one paragraph

Article in PloS one, 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.

Hashim HussainDepartment of Information Technology, College of Computer and Information Sciences, Majmaah University, Al Majmaah, Saudi Arabia.
Shailendra MishraDepartment of Computer Engineering, College of Computer and Information Sciences, Majmaah University, Al Majmaah, Saudi Arabia.ORCID https://orcid.org/0000-0002-0227-7148
Reem AlshenaifiDepartment of Information Technology, College of Computer and Information Sciences, Majmaah University, Al Majmaah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-enabled cyber threats, but introduced heightened cybersecurity risks, particularly from emerging quantum computing threats that can break conventional encryption such as RSA and ECC. This study addresses the urgent need to secure resource-constrained healthcare IoT systems against both classical and post-quantum attacks while maintaining low-latency performance suitable for non-real-time clinical traffic.This study proposed the Post-Quantum Cognitive Zero-Trust Architecture (PQ-CZTA), which integrates NIST-standardized post-quantum cryptography,CRYSTALS-Kyber for key encapsulation and SPHINCS+ for stateless digital signatures,with a lightweight cognitive engine. The engine employs three machine learning classifiers (Random Forest as primary, Logistic Regression, and Multi-Layer Perceptron) trained with SMOTE oversampling and 5-fold cross-validation on six diverse intrusion detection datasets (NSL-KDD, CIC-IDS2017, MedBIoT, Edge-IIoTset, IoT-23, TON_IoT). Intrusion probabilities are converted to dynamic trust scores that drive zero-trust policy decisions (ALLOW, MONITOR, DENY, QUARANTINE) in a layered architecture enforcing least privilege and hop-by-hop re-authentication.Evaluations demonstrate excellent detection performance with F1-scores ranging from 0.972 to 1.000 across datasets, particularly strong on modern IoT traffic. The full post-quantum handshake incurs 3.1-4.4 seconds latency (dominated by SPHINCS+), which remains acceptable for periodic vital-sign reporting, alerts, and firmware updates. An ablation study proves the importance of the components, with SMOTE contributing 5-20% to the F1 score on imbalanced data and cognitive ML providing the advantage of adaptive policies over static policies.PQ-CZTA provides a practical, quantum-resilient framework that enhances patient data privacy (HIPAA compliance via adaptive risk scoring), predicts attacks on limited devices, and supports resilient IoT-enabled healthcare systems against future quantum threats.

Indexed as

Computer SecurityInternet of ThingsDigital HealthHumansMachine LearningTrust

Identifiers

PMID42207806
PMCPMC13218509

What OpenQuestion holds

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Registered trials

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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.