Abstract
Internet of Things (IoT) is the backbone of telemedicine and its data security has become a significant concern that requires further attention. Therefore, this study was conducted with the aim of analyzing telemedicine systems, focusing on data security measures. Thirty peer-reviewed research studies published in 2018 were reviewed and compared according to certain parameters, viz., algorithms, IoT sensors, data encryption ability, communication mechanisms, mobile accessibility, protocols, software, and platforms. The results illustrate that transmitting sensitive medical data over the Internet has been identified as a major threat, and solutions such as ciphertext-policy attribute-based encryption and Secure Better Portable Graphics (SBPG) architecture have been developed to authenticate and protect data by concurrent encryption and watermarking. Furthermore, the comparison reveals that data encryption is the most frequently used secure data transmission method and 32% of the reviewed studies have focused on this. Regarding the most frequently used technologies, Raspberry Pi3 Edge platform (with the usage percentage of 60), TCP/IP protocol (with usage of 38%), and ECG and temperature sensors (with usage of 20%) have been discussed. Additionally, telemedicine has focused on standalone systems, and, in this context, integrated systems with micro-services are yet to be improved. Therefore, this study compares and analyzes the significant technical trends, security trends, widely used IoT sensors, platforms, and protocols; the aim is to help the researchers to gain a better insight into telemedicine to improve healthcare services by maximizing the capabilities of Internet of Things.
Original language | English |
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Title of host publication | Security, privacy and trust in the IoT environment |
Editors | Zaigham Mahmood |
Place of Publication | Cham, Switzerland |
Publisher | Springer |
Chapter | 9 |
Pages | 181-202 |
Number of pages | 22 |
Edition | 1st |
ISBN (Electronic) | 9783030180751 |
ISBN (Print) | 978303018744 |
DOIs | |
Publication status | Published - Jun 2019 |