Low Energy-Consuming Cluster-Based Algorithm to Enforce Integrity and Preserve Privacy in Data Aggregation

Guo, Zhengwei; Ding, Xiaojiao

doi:10.1109/dcabes.2014.32

Cited by 3 publications

(2 citation statements)

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“…Based on iPDA and CPDA algorithms, Bista et al (2012) proposed the DCIDA algorithm, which utilizes real part of complex number to protect data privacy and utilized the imaginary part to verify data integrity by introducing the concept of complex number. Guo and Ding (2014) proposed an ILC-CPDA algorithm to reduce data transmission by utilizing the LEACH protocol and simple aggregation methods. This algorithm can detect data integrity by adding homomorphic message authentication code.…”

Section: Introductionmentioning

confidence: 99%

A secure and efficient privacy-preserving data aggregation algorithm

Dou

Chen

Yang

et al. 2021

J Ambient Intell Human Comput

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As a significant part of the Internet of things, wireless sensor networks (WSNs) is frequently implemented in our daily life. Data aggregation in WSNs can realize limited transmission and save energy. In the process of data aggregation, node data information is vulnerable to be eavesdropped and attacked. Therefore, it is of great significance to the research of data aggregation privacy protection in WSNs. We propose a secure and efficient privacy-preserving data aggregation algorithm (SECPDA) based on the original clustering privacy data aggregation algorithm. In this algorithm, we utilize SEP protocol to dynamically select cluster head nodes, introduce slicing idea for the private data slicing, and generate false information for interference. A comprehensive experimental evaluation is conducted to assess the data traffic and privacy protection performance. The results demonstrate that the proposed SECPDA algorithm can effectively reduce data traffic and further improve data privacy of nodes.

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Section: Introductionmentioning

confidence: 99%

A secure and efficient privacy-preserving data aggregation algorithm

Dou

Chen

Yang

et al. 2021

J Ambient Intell Human Comput

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“…Earlier contributions in the URLLC domain have suggested the use of multiuser message aggregation and joint encoding [11]. It is anticipated that the message-aggregated encoding technique could bring significant improvements onto the reliability by leveraging the coding gain and channel frequency diversitygain, at the price of decoding complexity at MCDs, medium access control (MAC) complexities, as well as security and privacy concern [12]- [14]. Nevertheless, it remains unclear how the coding gain and diversity gain behave under various constraints of the temporal DoF; and how the lower MAC protocol should be designed to support the extreme use of available DoF in the time, frequency and spatial domains.…”

Section: Introductionmentioning

confidence: 99%

On URLLC Downlink Transmission Modes for MEC Task Offloading

Wang

et al. 2020

2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

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Multi-access edge computing for mobile computingtask offloading is driving the extreme utilization of available degrees of freedom (DoF) for ultra-reliable low-latency downlink communications. The fundamental aim of this work is to find latency-constrained transmission protocols that can achieve a very-low outage probability (e.g. 0.001%). Our investigation is mainly based upon the Polyanskiy-Poor-Verd ú formula on the finite-length coded channel capacity, which is extended from the quasi-static fading channel to the frequency selective channel. Moreover, the use of a suitable duplexing mode is also critical to the downlink reliability. Specifically, time-division duplexing (TDD) outperforms frequency-division duplexing (FDD) in terms of the frequency diversity-gain. On the other hand, FDD takes the advantage of having more temporal DoF in the downlink, which can be exchanged into the spatial diversity-gain through the use of space-time coding. Numerical study is carried out to compare the reliability between FDD and TDD under various latency constraints.Index Terms-Multi-access edge computing (MEC), task offloading, downlink, aggregate encoding, ultra-reliable low-latency communications (URLLC).

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