Secure Healthcare Data Aggregation Scheme for Internet of Things

2019 ◽  
pp. 175-186
Author(s):  
Muhammad Azeem ◽  
Ata Ullah
Keyword(s):  
Internet Of Things ◽  
Data Aggregation ◽  
Healthcare Data ◽  
Aggregation Scheme

Fog-assisted secure healthcare data aggregation scheme in IoT-enabled WSN

2019 ◽  
Vol 13 (1) ◽  
pp. 163-174 ◽  
Author(s):  
Ata Ullah ◽  
Ghawar Said ◽  
Muhammad Sher ◽  
Huansheng Ning
Keyword(s):  
Data Aggregation ◽  
Healthcare Data ◽  
Aggregation Scheme

scholarly journals Non-Interactive and Secure Data Aggregation Scheme for Internet of Things

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2464
Author(s):  
Yanxia Fu ◽  
Yanli Ren ◽  
Guorui Feng ◽  
Xinpeng Zhang ◽  
Chuan Qin
Keyword(s):  
Internet Of Things ◽  
Mobile Devices ◽  
Data Aggregation ◽  
Mobile User ◽  
Current Data ◽  
Multidimensional Data ◽  
Massive Data ◽  
Sensitive Information ◽  
User Privacy ◽  
Aggregation Scheme

The popularity of mobile devices in Internet of Things has brought great convenience to the lives of the people. Massive data generated in the IoT are outsourced and stored on cloud platforms so that data aggregation and analysis can be performed on the massive data. However, these data often contain sensitive information of mobile devices, so effective protection of mobile user privacy is the primary condition for further development of IoT. Most of the current data aggregation schemes require a lot of interactions between users, and thus this paper designs a non-interactive secure multidimensional data aggregation scheme. This scheme adopts an additive secret sharing technique to mask the shared data and send it to two non-colluding servers, and then the servers aggregate the ciphertext respectively. Different from the existing schemes, our proposed scheme achieves non-interaction between users, and the aggregation result is kept confidential to the server and supports mobile users offline. Finally, we perform an experimental evaluation which proves the effectiveness of our scheme.

EDAS: Efficient Data Aggregation Scheme for Internet of Things

2018 ◽  
Vol 13 (3) ◽  
pp. 347-375 ◽  
Author(s):  
Sunday Oyinlola Ogundoyin ◽  
Sunday Oladele Awoyemi
Keyword(s):  
Internet Of Things ◽  
Data Aggregation ◽  
Efficient Data ◽  
Aggregation Scheme

scholarly journals EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Faris A. Almalki ◽  
Ben Othman Soufiene
Keyword(s):  
Data Aggregation ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Data Integrity ◽  
Privacy Preserving ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Secure Data ◽  
Aggregation Scheme ◽  
Secure Data Aggregation

Nowadays, IoT technology is used in various application domains, including the healthcare, where sensors and IoT enabled medical devices exchange data without human interaction to securely transmit collected sensitive healthcare data towards healthcare professionals to be reviewed and take proper actions if needed. The IoT devices are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. In healthcare applications, many miniaturized devices are exploited for healthcare data collection and transmission. Thus, there is a need for secure data aggregation while preserving the data integrity and privacy of the patient. For that, the security, privacy, and aggregation of health data are very important aspects to be considered. This paper proposes a novel secure data aggregation scheme called “An Efficient and Privacy-Preserving Data Aggregation Scheme with authentication for IoT-Based Healthcare applications” (EPPDA). EPPDA is based to verification and authorization phase to verify the legitimacy of the nodes that need to join the process of aggregation. EPPDA, also, uses additive homomorphic encryption to protect data privacy and combines it with homomorphic MAC to check the data integrity. The major advantage of homomorphic encryption is allowing complex mathematical operations to be performed on encrypted data without knowing the contents of the original plain data. The proposed system is developed using MySignals HW V2 platform. Security analysis and experimental results show that our proposed scheme guarantees data privacy, messages authenticity, and integrity, with lightweight communication overhead and computation.

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