An Efficient Privacy-Preserving Data Aggregation Scheme for IoT

Hu, Chunqiang; Luo, Jin; Pu, Yuwen; Yu, Jiguo; Zhao, Ruifeng; Huang, Hongyu; Xiang, Tao

doi:10.1007/978-3-319-94268-1_14

Cited by 12 publications

(8 citation statements)

References 29 publications

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“…Then the immediate result after computation is reported to the aggregator. Analysis signifies that both data integrity and confidentiality can be achieved here thus it helps to defy external, internal and colluding attack, and likewise [18].…”

Section: Related Workmentioning

confidence: 99%

A Novel Framework for Privacy-Preserving Using Data Aggregation in Internet of Things (Iot)

Mohapatra¹

2020

ijarcs

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Today with the development of Internet of Things (IoT) technology its security and privacy becomes very much essential because this technology provide the facility for accessing the devices or resources from anywhere and anytime. For providing the security and privacy to IoT various technologies has been developed but in this we propose data aggregation mechanism in which it uses one-time pad and symmetric key to make our data secure and preserve the privacy of it. This mechanism takes less computation time, improve processing speed and also require less cost in implementation. The implementation of proposed approach is done in widely used Python technology which produces better results. In last the proposed mechanism provides more security and preserves our data.

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Section: Related Workmentioning

confidence: 99%

A Novel Framework for Privacy-Preserving Using Data Aggregation in Internet of Things (Iot)

Mohapatra¹

2020

ijarcs

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“…We consider the architecture in Figure 1 as the basis of our following discussion. Figure 1 reproduced from Hu et al [44]. ere are three entities, including server, aggregator, and devices in our system model of the proposed schemes.…”

Section: System Modelmentioning

confidence: 99%

“…e previous work [44] was published in International Conference on Wireless Algorithms, Systems, and Applications 2018.…”

Section: Data Availabilitymentioning

confidence: 99%

Two Secure Privacy-Preserving Data Aggregation Schemes for IoT

Luo

et al. 2019

Wireless Communications and Mobile Computing

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As the next generation of information and communication infrastructure, Internet of Things (IoT) enables many advanced applications such as smart healthcare, smart grid, smart home, and so on, which provide the most flexibility and convenience in our daily life. However, pervasive security and privacy issues are also increasing in IoT. For instance, an attacker can get health condition of a patient via analyzing real-time records in a smart healthcare application. Therefore, it is very important for users to protect their private data. In this paper, we present two efficient data aggregation schemes to preserve private data of customers. In the first scheme, each IoT device slices its actual data randomly, keeps one piece to itself, and sends the remaining pieces to other devices which are in the same group via symmetric encryption. Then, each IoT device adds the received pieces and the held piece together to get an immediate result, which is sent to the aggregator after the computation. Moreover, homomorphic encryption and AES encryption are employed to guarantee secure communication. In the second scheme, the slicing strategy is also employed. Noise data are introduced to prevent the exchanged actual data of devices from disclosure when the devices blend data each other. AES encryption is also employed to guarantee secure communication between devices and aggregator, compared to homomorphic encryption, which has significantly less computational cost. Analysis shows that integrity and confidentiality of IoT devices’ data can be guaranteed in our schemes. Both schemes can resist external attack, internal attack, colluding attack, and so on.

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“…Their construction relies on fog nodes computation resources to perform heavy computation-consuming functions. Later, Hu et al introduced a privacy preserving data aggregation scheme for IoT applications [10]. The proposed scheme relies on Secure Multiparty Computation (SMC) techniques, such that each device has to first divide sensory data, locally keeps one piece, and sends the remaining pieces to other group devices.…”

Section: Related Workmentioning

confidence: 99%

“…Then each IoT device adds the received shares and the held piece together to get immediate result. The [10] construction provides heavy computation and communication costs. Hence, it makes it unsuitable for resource-constrained devices.…”

Section: Related Workmentioning

confidence: 99%

Coop-DAAB: Cooperative Attribute Based Data Aggregation for Internet of Things Applications

Belguith

Kaaniche

Mohamed

et al. 2018

Lecture Notes in Computer Science

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The deployment of IoT devices is gaining an expanding interest in our daily life. Indeed, IoT networks consist in interconnecting several smart and resource constrained devices to enable advanced services. Security management in IoT is a big challenge as personal data are shared by a huge number of distributed services and devices. In this paper, we propose a Cooperative Data Aggregation solution based on a novel use of Attribute Based signcryption scheme (Coop-DAAB). Coop-DAAB consists in distributing data signcryption operation between different participating entities (i.e., IoT devices). Indeed, each IoT device encrypts and signs in only one step the collected data with respect to a selected sub-predicate of a general access predicate before forwarding to an aggregating entity. This latter is able to aggregate and decrypt collected data if a sufficient number of IoT devices cooperates without learning any personal information about each participating device. Thanks to the use of an attribute based signcryption scheme, authenticity of data collected by IoT devices is proved while protecting them from any unauthorized access.

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An Efficient Privacy-Preserving Data Aggregation Scheme for IoT

Cited by 12 publications

References 29 publications

A Novel Framework for Privacy-Preserving Using Data Aggregation in Internet of Things (Iot)

A Novel Framework for Privacy-Preserving Using Data Aggregation in Internet of Things (Iot)

Two Secure Privacy-Preserving Data Aggregation Schemes for IoT

Coop-DAAB: Cooperative Attribute Based Data Aggregation for Internet of Things Applications

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