Evidence map›Paper›PMID 42884498›Full record

ArticleSensors (Basel, Switzerland)2026

Cybersecurity of Smart Sensing Insole Systems: A Threat Modelling Approach to Understanding Security Vulnerabilities.

Padideh Choobdar, Nigel Davies, Emma D Wilson, Steve Hodges, Edward B Jude, Matthew Bradbury, Neil D Reeves

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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
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

7 authors.

Padideh ChoobdarMedical School, Faculty of Health and Medicine, Lancaster University, Lancaster LA1 4AT, UK.
Nigel DaviesSchool of Computing and Communications, Faculty of Science and Technology, Lancaster University, Lancaster LA1 4WA, UK.
Emma D WilsonSchool of Computing and Communications, Faculty of Science and Technology, Lancaster University, Lancaster LA1 4WA, UK.ORCID 0000-0003-1224-9228
Steve HodgesSchool of Computing and Communications, Faculty of Science and Technology, Lancaster University, Lancaster LA1 4WA, UK.
Edward B JudeTameside and Glossop Integrated Care NHS Foundation Trust, Ashton-Under-Lyne, Manchester OL6 9RW, UK.ORCID 0000-0002-3186-4122
Matthew BradburySchool of Computing and Communications, Faculty of Science and Technology, Lancaster University, Lancaster LA1 4WA, UK.ORCID 0000-0003-4661-000X
Neil D ReevesMedical School, Faculty of Health and Medicine, Lancaster University, Lancaster LA1 4AT, UK.ORCID 0000-0001-9213-4580

Funding

Engineering and Physical Sciences Research Council UKRI825
6 · The paper itself

Abstract

Smart sensing insoles are emerging medical IoT devices used primarily in diabetes care to monitor foot pressure, temperature and gait for preventing diabetic foot ulcers and lower-limb amputation. Despite growing healthcare use, the cybersecurity threats to these systems have received limited systematic analysis in the literature. This study aimed to provide a detailed threat modelling analysis of smart insole systems. The study developed a representative smart insole system architecture using public information, the literature, and manufacturer input. A data flow diagram mapped devices, processes, data stores, data flows, and trust boundaries across sensor, edge/mobile, cloud and clinician zones. Potential cybersecurity threats were analysed using STRIDE, MITRE ATT&CK mapping and attack trees. The modelled analysis identified potential threats across all STRIDE categories: spoofing, tampering, repudiation, information disclosure, denial of service and elevation of privilege. Three attacker goals were modelled: stealing health data, reducing trust in the technology and inflicting patient harm. Key modelled threats include BLE interception, weak authentication, data tampering, service disruption, log deletion and manipulation of clinical outputs. Commercial systems varied substantially in their security features. The modelled findings show that cybersecurity threats to smart insoles extend beyond data privacy to include threats to patient safety. Disrupted alerts, altered pressure data or unavailable monitoring could delay clinical action and increase diabetic foot ulcer and amputation risk. The study highlights the need for secure-by-design systems, including BLE encryption, strong authentication, audit logging and clearer regulatory/procurement standards.

Indexed as

Computer SecurityDiabetic FootDigital HealthHumansWearable Electronic DevicesdiabeteshackingIoTsmart insoleSTRIDEthreat modellingwearable medical device

Identifiers

PMID42884498
PMCPMC13667700

What OpenQuestion holds

Textmetadata
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.