EPPA: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications

By Rongxing Lu, Xiaohui Liang, Xu Li, Xiaodong Lin, Xuemin Shen. 2012

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ju Ren
2. Wenxiu Ding
3. Opeyemi A. Osanaiye
4. Zheng Yan
5. Rongxing Lu
6. Yan Zhang
7. Hong Liu
8. Xuyang Jing

Citations in the corpus

• A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, methodology): “3 - - Y Y N [45] Data injection detection Line power flow K-means or EM IEEE 39 bus - - - - - Y Y [87] False data injection detection Stste estimation Spatiotemporal cyber-state correlation US smart grid Y N - - - N Y [88] Fault Diagnosis Circuit Breakers data and voltage data OWA, ANN, IEEE 14-bus ”
• Role-Dependent Privacy Preservation for Secure V2G Networks in the Smart Grid (2014, methodology): “Additionally, several works have studied the general security issues in the smart grid, including security frameworks [13]–[19], authentication protocols [20]–[23], encryption and key management [24], [25], and privacy-preserving protocols [26], [27].”
• Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering (2017, background): “[9] presented an aggregation scheme with enhanced performance on multidimensional data.”
• Mobile Edge Computing: A Survey (2018, background): “Aggregation schemes, such as homomorphic encryption can enable privacy-preserving aggregation at gateways to secure user information [102].”
• Cloud Computing Applications for Smart Grid: A Survey (2015, background): “Demand response, distributed generation, resource scheduling, and real-time pricing model contribute to the heterogeneity of a smart grid [11]. f) Security: Effective authentication and authorization techniques are required for the preservation of users’ privacy.”
• Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in the Smart Grid (2012, background): “For this reason, cannot obtain the ’s private algorithms (e.g., pseudo-random status generation, and Hamming distance based extension).”
• A Survey of Fog Computing: Concepts, Applications and Issues (2015, methodology): “Techniques such as homomorphic encryption can be utilized to allow privacy-preserving aggregation at the local gateways without decryption [29].”
• Privacy-Enhanced Data Aggregation Scheme Against Internal Attackers in Smart Grid (2014, unknown): “It satisfies semantic security as defined in Definition 1 where the security proof is described in Appendix A.”
• The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, methodology): “For instance a privacy-preserving aggregation scheme, called EPPA, is designed in [319], which permits to perform data aggregation at intermediate proxies without decrypting the data received by individual smart meters.”
• A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms (2019, background): “[92] present a privacy-preserving and efficient aggregation scheme for communication in smart grid.”
• From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, methodology): “Privacy issues in smart grid were presented in [71], and a privacy-preserving aggregation scheme using multidimensional data aggregation approach based on homomorphic Paillier cryptography was proposed.”
• Security and Privacy Issues of Fog Computing: A Survey (2015, methodology): “Techniques such as homomorphic encryption can be utilized to allow privacy-preserving aggregation at the local gateways without decryption [20].”
• An overview of Fog computing and its security issues (2016, methodology): “For data communications from user to smart grid operation centre, data aggregation is performed directly on ciphertext at local gateways without decryption, and the aggregation result of the original data can be obtained at the operation centre [36].”
• Security and Privacy in the Internet of Things (2017, background): “Various schemes have been proposed to secure IoT communication and data exchange, which span over a variety of topics including but not limited to privacy-preserving data collection [102, 111], detection and prevention of false data injection [101, 110, 80, 158], patient monitoring [127, 112], etc.”
• A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing-Enhanced IoT (2017, methodology): “Note that, EPPA [6] may be applied for hybrid IoT data aggregation, but themultiple time-consuming exponential computations make it not as efficient as the proposed LPDA.”
• Fog computing security: a review of current applications and security solutions (2017, methodology): “Other research work provides a similar framework to secure smart grids, regardless of Fog computing, called the Efficient and Privacy Preserving Aggregation (EPPA) scheme [105].”
• Energy-theft detection issues for advanced metering infrastructure in smart grid (2014, background): “Indeed, the traditional power grid, which is surprisingly still grounded on the design more than 100 years ago, can no longer be suitable for today’s society[3].”
• A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications (2017, background): “The original data can only be decrypted at the operation center [151].”