scholarly journals A secure and collaborative data aggregation scheme for fine‐grained data distribution and management in Internet of Things

2020 ◽  
Author(s):  
Oladayo Olufemi Olakanmi ◽  
Kehinde Oluwasesan Odeyemi
Keyword(s):  
Internet Of Things ◽  
Data Aggregation ◽  
Data Distribution ◽  
Fine Grained ◽  
Aggregation Scheme

scholarly journals Edge Computing Assisted an Efficient Privacy Protection Layered Data Aggregation Scheme for IIoT

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Rong Ma ◽  
Tao Feng ◽  
Junli Fang
Keyword(s):  
Internet Of Things ◽  
Data Aggregation ◽  
Privacy Protection ◽  
Chinese Remainder Theorem ◽  
Edge Computing ◽  
Communication Overhead ◽  
Industrial Internet Of Things ◽  
Fine Grained ◽  
Industrial Internet ◽  
Aggregation Scheme

The emergence of edge computing has improved the real time and efficiency of the Industrial Internet of Things. In order to achieve safe and efficient data collection and application in the Industrial Internet of Things, a lot of computing and bandwidth resources are usually sacrificed. From the perspective of low computing and communication overhead, this paper proposes an efficient privacy protection layered data aggregation scheme for edge computing assisted IIoT by combining the Chinese Remainder Theorem (CRT), improved Paillier homomorphic algorithm, and hash chain technology (edge computing assisted an efficient privacy protection layered data aggregation scheme for IIoT, EE-PPDA). In EE-PPDA, first, a layered aggregation architecture based on edge computing is designed. Edge nodes and cloud are responsible for local aggregation and global aggregation, respectively, which effectively reduces the amount of data transmission. At the same time, EE-PPDA achieves data confidentiality through improved Paillier encryption, ensuring that neither attackers nor semitrusted nodes (e.g., edge nodes and clouds) can know the private data of a single device, and it can resist by simply using hash chains to resist tampering and pollution attacks ensure data integrity. Second, according to the CRT, the cloud can obtain the fine-grained aggregation results of subregions from the global aggregation results, thereby providing fine-grained data services. In addition, the EE-PPDA scheme also supports fault tolerance. Even if some IIoT devices or communication links fail, the cloud can still decrypt incomplete aggregated ciphertexts and obtain the expected aggregation results. Finally, the performance evaluation shows that the proposed EE-PPDA scheme has less calculation and communication costs.

Lightweight and Fine-Grained Privacy-Preserving Data Aggregation Scheme in Edge Computing

2021 ◽  
pp. 1-10
Author(s):  
Hongyang Li ◽  
Qingfeng Cheng ◽  
Xinghua Li ◽  
Siqi Ma ◽  
Jianfeng Ma
Keyword(s):  
Data Aggregation ◽  
Privacy Preserving ◽  
Edge Computing ◽  
Fine Grained ◽  
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
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