Privacy Preserving Data Aggregation Scheme for Mobile Edge Computing Assisted IoT Applications

2019 ◽  
Vol 6 (3) ◽  
pp. 4755-4763 ◽  
Author(s):  
Xiong Li ◽  
Shanpeng Liu ◽  
Fan Wu ◽  
Saru Kumari ◽  
Joel J. P. C. Rodrigues
2021 ◽  
pp. 1-10
Author(s):  
Hongyang Li ◽  
Qingfeng Cheng ◽  
Xinghua Li ◽  
Siqi Ma ◽  
Jianfeng Ma

While Internet of Things (IoT) technology comprises of nodes that are self-configuring and intelligent which are interconnected in a dynamic network, utilization of shared resources has been revolutionized by the cloud computing effectively reducing the cost overheadamong the cloud users.The major concerns of IoT infrastructure are reliability, performance, security and privacy. Cloud computing is popular for its unlimited storage and processing power. Cloud computing is much more matured with the capability to resolve most of the issues in IoT technology. A suitable way to address most of the issues in IoT technology is by integrating IoTparadigm into the Cloud technology.In this regard, we propose a methodology of applying our EPAS scheme for IoT applications. In our previous work[2] , we have proposed an Enhanced Privacy preserving gene based data Aggregation Scheme (EPAS) for private data transmission and storage by utilizing Enhanced P-Gene erasable data hiding approach. Enhanced P-Gene scheme ensures secure transmission and storage of private data by relying on a data aggregation scheme fully dependent on erasable data hiding technique. In the current work we analyse the applicability of the EPAS scheme for IoT applications. Experimental results show the suitability of the proposed scheme for application involving numeric data and also demonstrates performance improvement with existing proposals for data aggregation in cloud.


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