A Novel Privacy-Preserving Set Aggregation Scheme for Smart Grid Communications

Lu, Rongxing; Alharbi, Khalid; Lin, Xiaodong; Huang, Cheng

doi:10.1109/glocom.2015.7417029

Cited by 29 publications

(50 citation statements)

References 10 publications

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“…There has been extensive research concerning privacy and security on the smart grid. Much literature have proposed schemes to address confidentiality, data integrity and authenticity in uplink transmissions [8,10,22,52,53,82,83]. However, only few security schemes have been proposed to secure downlink communications in smart grid.…”

Section: Discussionmentioning

confidence: 99%

A framework for privacy-preserving data sharing in the Smart Grid

Alharbi

Lin

Shao

2014

2014 IEEE/CIC International Conference on Communications in China (ICCC)

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Section: Discussionmentioning

confidence: 99%

A framework for privacy-preserving data sharing in the Smart Grid

Alharbi

Lin

Shao

2014

2014 IEEE/CIC International Conference on Communications in China (ICCC)

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“…In this section, an overview of existing fog-enabled privacy preserving-data aggregation (e.g., [9], [10], [12]- [14] and traditional privacy-preserving data aggregation (e.g., [17][18][19][20][21][22][23][24][25][26][27][28]) schemes in SG is provided in detail. Existing fog-enabled data aggregation schemes in SG, such as those presented in [9], [10], have a number of limitations.…”

Section: A Related Workmentioning

confidence: 99%

“…Authors in [24], [25] have proposed fault-tolerant privacy-preserving data aggregation schemes which perform the aggregation of users' consumption data even if some of the SMs are malfunctioning. Many researchers have worked on privacy preservation in an aggregated data by collecting the data in multiple subsets [26]- [28].…”

Section: A Related Workmentioning

confidence: 99%

FESDA: Fog-Enabled Secure Data Aggregation in Smart Grid IoT Network

Saleem

Khan

Malik

et al. 2020

IEEE Internet Things J.

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With advances in Fog and edge computing, various problems such as data processing for large Internet of things (IoT) systems can be solved in an efficient manner. One such problem for the next generation smart grid IoT system comprising of millions of smart devices is the data aggregation problem. Traditional data aggregation schemes for smart grids incur high computation and communication costs, and in recent years there have been efforts to leverage fog computing with smart grids to overcome these limitations. In this paper, a new fog-enabled privacy-preserving data aggregation scheme (FESDA) is proposed. Unlike existing schemes, the proposed scheme is resilient to false data injection attacks by filtering out the inserted values from external attackers. To achieve privacy, a modified version of Paillier crypto-system is used to encrypt consumption data of the smart meter users. In addition, FESDA is fault-tolerant, which means, the collection of data from other devices will not be affected even if some of the smart meters malfunction. We evaluate its performance along with three other competing schemes in terms of aggregation, decryption and communication costs. The findings demonstrate that FESDA reduces the communication cost by 50%, when compared with the PPFA aggregation scheme.

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“…In order to solve the mentioned problem above, Lu et al proposed a novel privacy‐preserving set aggregation scheme in smart grid to satisfy the need of more fine‐grained aggregation results at the control center. In this scheme, the whole residential users are divided into two subsets according a threshold, and then the total consumption of each subset and subset size can be obtained by using a group of composite order.…”

Section: Related Workmentioning

confidence: 99%

“…Meanwhile, the data privacy of individual user is protected against the honest‐but‐curious gateway and control center. Extending the work of Lu et al to support data integrity authentication, Tahir et al studied a set aggregation‐based data integrity scheme in smart grids; the integrity of the aggregated data is authenticated based on a novel hash chain construction mechanism. Enhanced with the work of Lu et al, the PPMA scheme provides support for the aggregation of multiple (more than two) subsets separately, while the data integrity authentication and fault tolerance are not supported.…”

Section: Related Workmentioning

confidence: 99%

Layered data aggregation with efficient privacy preservation for fog‐assisted IIoT

Chen

Zhao

et al. 2020

Int J Communication

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The emergence of fog computing facilitates industrial Internet of Things (IIoT) to be more real-time and efficient; in order to achieve secure and efficient data collection and applications in fog-assisted IIoT, it usually sacrifices great computation and bandwidth resources. From the low computation and communication overheads perspective, this paper proposes a layered data aggregation scheme with efficient privacy preservation (LDA-EPP) for fog-assisted IIoT by integrating the Chinese remainder theorem (CRT), modified Paillier encryption, and hash chain technology. In LDA-EPP scheme, the entire network is divided into several subareas; the fog node and cloud are responsible for local and global aggregations, respectively. Specially, the cloud is able to obtain not only the global aggregation result but also the fine-grained aggregation results of subareas, which enables that can provide fine-grained data services. Meanwhile, the LDA-EPP realizes data confidentiality by the modified Paillier encryption, ensures that both outside attackers and internal semi-trusted nodes (such as, fog node and cloud) are unable to know the privacy data of individual device, and guarantees data integrity by utilizing simply hash chain to resist tempering and polluting attacks. Moreover, the fault tolerance is also supported in our scheme; ie, even though some IIoT devices or channel links are failure, the cloud still can decrypt incomplete aggregation ciphertexts and derive expected aggregation results. Finally, the performance evaluation indicates that our proposed LDA-EPP has less computation and communication costs.

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A Novel Privacy-Preserving Set Aggregation Scheme for Smart Grid Communications

Cited by 29 publications

References 10 publications

A framework for privacy-preserving data sharing in the Smart Grid

A framework for privacy-preserving data sharing in the Smart Grid

FESDA: Fog-Enabled Secure Data Aggregation in Smart Grid IoT Network

Layered data aggregation with efficient privacy preservation for fog‐assisted IIoT

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