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.

Raso, E., Bianco, G.m., Bracciale, L., Marrocco, G., Occhiuzzi, C., Loreti, P. (2022). Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications. SENSORS, 22(24) [10.3390/s22249692].

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

Bracciale, Lorenzo;Marrocco, Gaetano;Occhiuzzi, Cecilia;Loreti, Pierpaolo
2022-12-10

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.
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/02
English
Near Field Communication
attribute-based encryption
body-area Internet of Things
cybersecurity
healthcare Internet of Things
point-of-care
proxy re-encryption
radio frequency identification
Raso, E., Bianco, G.m., Bracciale, L., Marrocco, G., Occhiuzzi, C., Loreti, P. (2022). Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications. SENSORS, 22(24) [10.3390/s22249692].
Raso, E; Bianco, Gm; Bracciale, L; Marrocco, G; Occhiuzzi, C; Loreti, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/310819
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