Architecture of a Wireless Wearable Body Area Sensor Network for Work Risk Assessment

Author(s):  
Stefano di Modica ◽  
Marco di Rienzo ◽  
Fabio di Francesco ◽  
Enzo Pasquale Scilingo ◽  
Antonio Lanata
Author(s):  
Antonio Lanata ◽  
Alberto Greco ◽  
Stefano Di Modica ◽  
Francesco Niccolini ◽  
Federico Vivaldi ◽  
...  

2020 ◽  
pp. 1-1
Author(s):  
Amir Mehmood ◽  
Adnan Nadeem ◽  
Muhammad Ashraf ◽  
Muhammad Shoaib Siddiqui ◽  
Kashif Rizwan ◽  
...  

2012 ◽  
Vol 50 (5) ◽  
pp. 116-125 ◽  
Author(s):  
U. Mitra ◽  
B. A. Emken ◽  
Sangwon Lee ◽  
Ming Li ◽  
V. Rozgic ◽  
...  

Author(s):  
Theodoros Mavroeidakos ◽  
Nikolaos Peter Tsolis ◽  
Dimitrios D. Vergados ◽  
Stavros Kotsopoulos

Machine-to-machine (M2M) communication is an emerging technology with unrivaled benefits in the fields of e Health and m-Health. The wireless body area networks (WBANs) consist of a major subdomain of M2M communications. The WBANs coupled with the Cloud Computing (CC) paradigm introduce a supreme infrastructure in terms of performance and Quality of Services (QoS) for the development of eHealth applications. In this article, a risk assessment aiming to disclose potential threats and highlight exploitation of health care services, is introduced. The proposed assessment is based upon the implementation of a series of steps. Initially, the health care WBAN-CC infrastructure is scrutinized; then, its threats' taxonomy is identified. Then, a risk assessment is carried out based on an attack-tree consisting of the most hazardous threats against Personally Identifiable Information (PII) disclosure. Thus, the implementation of several countermeasures is realized as a means to mitigate gaps.


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