In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching stra...In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching strategy. However, these big energy data in terms of volume, velocity and variety raise concern over consumers＇ privacy. For instance, in order to optimize energy utilization and support demand response, numerous smart meters are installed at a consumer＇s home to collect energy consumption data at a fine granularity, but these fine-grained data may contain information on the appliances and thus the consumer＇s behaviors at home. In this paper, we propose a privacy-preserving data aggregation scheme based on secret sharing with fault tolerance in a smart grid, which ensures that the control center obtains the integrated data without compromising privacy. Meanwhile, we also consider fault tolerance and resistance to differential attack during the data aggregation. Finally, we perform a security analysis and performance evaluation of our scheme in comparison with the other similar schemes. The analysis shows that our scheme can meet the security requirement, and it also shows better performance than other popular methods.展开更多
Technological advancement has made a significant contribution to the change of the economy and the advancement of humanity.Because it is changing how economic transactions are carried out,the blockchain is one of the t...Technological advancement has made a significant contribution to the change of the economy and the advancement of humanity.Because it is changing how economic transactions are carried out,the blockchain is one of the technical developments that has a lot of promise for this progress.The public record of the Bitcoin blockchain provides dispersed users with evidence of transaction owner-ship by publishing all transaction data from block reward transactions to unspent transaction outputs.Attacks on the public ledger,on the other hand,are a result of the fact that all transaction information are exposed.De-anonymization attacks allow users to link transaction entities and acquire user privacy through specified transaction amounts.As a result,in light of the Bitcoin blockchain system’s priv-acy issues,this scheme combines the concept of coin mixing with encrypted trans-action technology to create a truly anonymous blockchain system that preserves the payer identity and transaction amount privacy.The one-way aggregated sig-nature technique of Boneh,Gentry,and Lynn systematically embeds the notion of mixing into the whole block.The homomorphic encryption approach of Boneh,Goh,and Nissim allows miners to check the legality of encrypted transactions.Miners will validate transactions,conceal transactions,and package transactions as entities in the scheme.Finally,this technique was chosen after a comparison of several privacy-preserving blockchain schemes.It not only ensures complete anonymity,but also keeps transaction storage overhead to a minimum.展开更多
As an emergent-architecture, mobile edge computing shifts cloud service to the edge of networks. It can satisfy several desirable characteristics for Io T systems. To reduce communication pressure from Io T devices, d...As an emergent-architecture, mobile edge computing shifts cloud service to the edge of networks. It can satisfy several desirable characteristics for Io T systems. To reduce communication pressure from Io T devices, data aggregation is a good candidate. However, data processing in MEC may suffer from many challenges, such as unverifiability of aggregated data, privacy-violation and fault-tolerance. To address these challenges, we propose PVF-DA: privacy-preserving, verifiable and fault-tolerant data aggregation in MEC based on aggregator-oblivious encryption and zero-knowledge-proof. The proposed scheme can not only provide privacy protection of the reported data, but also resist the collusion between MEC server and corrupted Io T devices. Furthermore, the proposed scheme has two outstanding features: verifiability and strong fault-tolerance. Verifiability can make Io T device to verify whether the reported sensing data is correctly aggregated. Strong fault-tolerance makes the aggregator to compute an aggregate even if one or several Io Ts fail to report their data. Finally, the detailed security proofs are shown that the proposed scheme can achieve security and privacy-preservation properties in MEC.展开更多
文摘In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching strategy. However, these big energy data in terms of volume, velocity and variety raise concern over consumers＇ privacy. For instance, in order to optimize energy utilization and support demand response, numerous smart meters are installed at a consumer＇s home to collect energy consumption data at a fine granularity, but these fine-grained data may contain information on the appliances and thus the consumer＇s behaviors at home. In this paper, we propose a privacy-preserving data aggregation scheme based on secret sharing with fault tolerance in a smart grid, which ensures that the control center obtains the integrated data without compromising privacy. Meanwhile, we also consider fault tolerance and resistance to differential attack during the data aggregation. Finally, we perform a security analysis and performance evaluation of our scheme in comparison with the other similar schemes. The analysis shows that our scheme can meet the security requirement, and it also shows better performance than other popular methods.
基金supported by the Researchers Supporting Project(No.RSP-2021/395),King Saud University,Riyadh,Saudi Arabia.
文摘Technological advancement has made a significant contribution to the change of the economy and the advancement of humanity.Because it is changing how economic transactions are carried out,the blockchain is one of the technical developments that has a lot of promise for this progress.The public record of the Bitcoin blockchain provides dispersed users with evidence of transaction owner-ship by publishing all transaction data from block reward transactions to unspent transaction outputs.Attacks on the public ledger,on the other hand,are a result of the fact that all transaction information are exposed.De-anonymization attacks allow users to link transaction entities and acquire user privacy through specified transaction amounts.As a result,in light of the Bitcoin blockchain system’s priv-acy issues,this scheme combines the concept of coin mixing with encrypted trans-action technology to create a truly anonymous blockchain system that preserves the payer identity and transaction amount privacy.The one-way aggregated sig-nature technique of Boneh,Gentry,and Lynn systematically embeds the notion of mixing into the whole block.The homomorphic encryption approach of Boneh,Goh,and Nissim allows miners to check the legality of encrypted transactions.Miners will validate transactions,conceal transactions,and package transactions as entities in the scheme.Finally,this technique was chosen after a comparison of several privacy-preserving blockchain schemes.It not only ensures complete anonymity,but also keeps transaction storage overhead to a minimum.
基金supported by Beijing Natural Science Foundation—Haidian Original Innovation Joint Fund Project Task Book(Key Research Topic)(Nos.L182039)Open Fund of National Engineering Laboratory for Big Data Collaborative Security Technology and the Foundation of Guizhou Provincial Key Laboratory of Public Big Data(No.2019BDKFJJ012)。
文摘As an emergent-architecture, mobile edge computing shifts cloud service to the edge of networks. It can satisfy several desirable characteristics for Io T systems. To reduce communication pressure from Io T devices, data aggregation is a good candidate. However, data processing in MEC may suffer from many challenges, such as unverifiability of aggregated data, privacy-violation and fault-tolerance. To address these challenges, we propose PVF-DA: privacy-preserving, verifiable and fault-tolerant data aggregation in MEC based on aggregator-oblivious encryption and zero-knowledge-proof. The proposed scheme can not only provide privacy protection of the reported data, but also resist the collusion between MEC server and corrupted Io T devices. Furthermore, the proposed scheme has two outstanding features: verifiability and strong fault-tolerance. Verifiability can make Io T device to verify whether the reported sensing data is correctly aggregated. Strong fault-tolerance makes the aggregator to compute an aggregate even if one or several Io Ts fail to report their data. Finally, the detailed security proofs are shown that the proposed scheme can achieve security and privacy-preservation properties in MEC.
