Evidence map›Paper›PMID 36560061›Full record

ArticleSensors (Basel, Switzerland)2022

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications.

Emanuele Raso, Giulio Maria Bianco, Lorenzo Bracciale, Gaetano Marrocco, Cecilia Occhiuzzi, Pierpaolo Loreti

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

6 authors.

Emanuele RasoDepartment of Electronic Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0003-1195-6529
Giulio Maria BiancoPervasive Electromagnetics Lab, Department of Civil Engineering and Computer Science Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0002-3216-5884
Lorenzo BraccialeDepartment of Electronic Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0002-6673-3157
Gaetano MarroccoPervasive Electromagnetics Lab, Department of Civil Engineering and Computer Science Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0003-3151-3071
Cecilia OcchiuzziPervasive Electromagnetics Lab, Department of Civil Engineering and Computer Science Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0002-7761-8293
Pierpaolo LoretiDepartment of Electronic Engineering, University of Rome Tor Vergata, 00133 Roma, Italy.ORCID 0000-0002-2348-5077

Funding

Regione Lazio CUP: E85F21001040002
6 · The paper itself

Abstract

World population and life expectancy have increased steadily in recent years, raising issues regarding access to medical treatments and related expenses. Through last-generation medical sensors, NFC (Near Field Communication) and radio frequency identification (RFID) technologies can enable healthcare internet of things (H-IoT) systems to improve the quality of care while reducing costs. Moreover, the adoption of point-of-care (PoC) testing, performed whenever care is needed to return prompt feedback to the patient, can generate great synergy with NFC/RFID H-IoT systems. However, medical data are extremely sensitive and require careful management and storage to protect patients from malicious actors, so secure system architectures must be conceived for real scenarios. Existing studies do not analyze the security of raw data from the radiofrequency link to cloud-based sharing. Therefore, two novel cloud-based system architectures for data collected from NFC/RFID medical sensors are proposed in this paper. Privacy during data collection is ensured using a set of classical countermeasures selected based on the scientific literature. Then, data can be shared with the medical team using one of two architectures: in the first one, the medical system manages all data accesses, whereas in the second one, the patient defines the access policies. Comprehensive analysis of the H-IoT system can be useful for fostering research on the security of wearable wireless sensors. Moreover, the proposed architectures can be implemented for deploying and testing NFC/RFID-based healthcare applications, such as, for instance, domestic PoCs.

Indexed as

Internet of ThingsRadio Frequency Identification DeviceCommunicationDelivery of Health CareHumansPrivacyattribute-based encryptionbody-area Internet of Thingscybersecurityhealthcare Internet of ThingsNear Field Communicationpoint-of-careproxy re-encryptionradio frequency identification

Identifiers

PMID36560061
PMCPMC9785613

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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.