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Fault-Tolerant Multisubset Aggregation Scheme for Smart Grid

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TLDR
A fault-tolerant multisubset data aggregation scheme that prevents the leakage of single data, as well as guarantees the efficiency when new user joins and existing user leaves is proposed.
Abstract
As smart cities and nations are fast becoming a reality, so does the underpinning infrastructure, such as smart grids. One particular challenge associated with smart grid implementation is the need to ensure privacy preserving multisubset data aggregation. Existing approaches generally require the collaboration of a trusted third party (TTP), which may not be practical. This also increases the threat exposure, as the attacker can now target the TTP who may be servicing several smart grid operators. Therefore, in this article, a fault-tolerant multisubset data aggregation scheme is proposed. Our scheme aggregates the total electricity consumption value, and obtains the number of users and the total electricity consumption in different numerical intervals, without relying on any TTP. Detailed system analysis shows that our scheme prevents the leakage of single data, as well as guarantees the efficiency when new user joins and existing user leaves. Findings from our evaluation also demonstrate that system robustness is achieved with negligible cost.

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Citations
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Boosting quantum rotation gate embedded slime mould algorithm

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A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller

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Journal ArticleDOI

Double-Target Based Neural Networks in Predicting Energy Consumption in Residential Buildings

Hossein Moayedi, +1 more
- 01 Mar 2021 - 
TL;DR: Three novel hybrid intelligent methods, namely the grasshopper optimization algorithm (GOA), wind-driven optimization (WDO), and biogeography-based optimization (BBO), are employed to optimize the multitarget prediction of heating loads (HLs) and cooling loads (CLs) in the heating, ventilation and air conditioning (HVAC) systems.
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Enhanced Harris hawks optimization with multi-strategy for global optimization tasks

TL;DR: An effective hybrid model of kernel extreme learning machine is developed on the basis of RLHHO to cope with bankruptcy prediction problem and the experimental results show that this hybrid model is highly competitive with other mainstream classifiers regarding stability and prediction accuracy.
Journal ArticleDOI

Edge Computing for IoT-Enabled Smart Grid: The Future of Energy

TL;DR: This work performs a comprehensive survey of edge computing for IoT-enabled smart grid systems and hopes that these study results will contribute important guidelines for in-depth research in the field of smart grids and green energy in the future.
References
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Journal ArticleDOI

A Practical Privacy-Preserving Data Aggregation (3PDA) Scheme for Smart Grid

TL;DR: A practical privacy-preserving data aggregation scheme is proposed without TTP, in which the users with some extent trust construct a virtual aggregation area to mask the single user's data, and meanwhile, the aggregation result almost has no effect for the data utility in large scale applications.
Journal ArticleDOI

Efficient and Privacy-Preserving Data Aggregation Scheme for Smart Grid Against Internal Adversaries

TL;DR: The proposed P2DA scheme against internal attackers using Boneh–Goh–Nissim public key cryptography is proposed, which is more computationally efficient and provably secure and can meet various security requirements.
Journal ArticleDOI

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

TL;DR: The proposed privacy preserving data aggregation scheme not only guarantees data privacy of the TDs but also provides source authentication and integrity, and is very suitable for MEC assisted IoT applications.
Journal ArticleDOI

PPMA: Privacy-Preserving Multisubset Data Aggregation in Smart Grid

TL;DR: Detailed security analysis shows that PPMA can protect individual user's electricity consumption privacy against a strong adversary, and extensive experiments results demonstrate thatPPMA has less computation overhead and no more extra communication and storage costs.
Journal ArticleDOI

Human-Factor-Aware Privacy-Preserving Aggregation in Smart Grid

TL;DR: This paper identifies and formalizes a new attack, in which the attacker could exploit the information about the presence or absence of a specific person to infer his meter readings, and proposes two novel protocols to achieve privacy-preserving smart metering data aggregation and to resist the HDA attack.
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