Comparison of the Paillier and ElGamal Cryptosystems for Smart Grid Aggregation Protocols

Many smart grid applications require the collection of fine-grained load data from customers. In order to protect customer privacy, secure aggregation protocols have been proposed that aggregate data spatially without allowing the aggregator to learn individual load data. Many of these protocols build on the Paillier cryptosystem and its additively homomorphic property. Existing works provide little or no justification for the choice of this cryptosystem and there is no direct performance comparison to other schemes that allow for an additively homomorphic property. In this paper, we compare the ElGamal cryptosystem with the established Paillier cryptosystem, both, conceptually and in terms of runtime, specifically for the use in privacy-preserving aggregation protocols. We find that, in the ElGamal cryptosystem, when made additively homomorphic, the runtime for encryption and decryption is distributed more asymmetrically between the smart meter and the aggregator than it is in the Paillier cryptosystem. This better reflects the setup typically found in smart grid environments, where encryption is performed on low-powered smart meters and decryption is usually performed on powerful machines. Thus, the ElGamal cryptosystem is a better, albeit overlooked, choice for secure aggregation

[1]  Ersin Uzun,et al.  Privacy, efficiency & fault tolerance in aggregate computations on massive star networks , 2015, 2015 IEEE International Workshop on Information Forensics and Security (WIFS).

[2]  Peng Liu,et al.  Secure Information Aggregation for Smart Grids Using Homomorphic Encryption , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[3]  Stefan Katzenbeisser,et al.  Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering , 2017, Proc. Priv. Enhancing Technol..

[4]  Stephen B. Wicker,et al.  A Privacy-Aware Architecture for Demand Response Systems , 2011, 2011 44th Hawaii International Conference on System Sciences.

[5]  Caroline Fontaine,et al.  A Survey of Homomorphic Encryption for Nonspecialists , 2007, EURASIP J. Inf. Secur..

[6]  Steven D. Galbraith,et al.  Elliptic Curve Paillier Schemes , 2001, Journal of Cryptology.

[7]  Victor Shoup,et al.  Lower Bounds for Discrete Logarithms and Related Problems , 1997, EUROCRYPT.

[8]  Ivan Damgård,et al.  A generalization of Paillier’s public-key system with applications to electronic voting , 2010, International Journal of Information Security.

[9]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[10]  Munam Ali Shah,et al.  Cryptography: A Comparative Analysis for Modern Techniques , 2017 .

[11]  Zekeriya Erkin,et al.  A fault-tolerant and efficient scheme for data aggregation over groups in the smart grid , 2017, 2017 IEEE Workshop on Information Forensics and Security (WIFS).

[12]  Cornelia Kermel,et al.  Gesetz zur Digitalisierung der Energiewende , 2016 .

[13]  Jacques Stern,et al.  Sharing Decryption in the Context of Voting or Lotteries , 2000, Financial Cryptography.

[14]  Francesc Sebé,et al.  Efficient smart metering based on homomorphic encryption , 2016, Comput. Commun..

[15]  Rosario Gennaro,et al.  Paillier's cryptosystem revisited , 2001, CCS '01.

[16]  Stefan Katzenbeisser,et al.  Group homomorphic encryption: characterizations, impossibility results, and applications , 2013, Des. Codes Cryptogr..

[17]  Zekeriya Erkin,et al.  Private Computation of Spatial and Temporal Power Consumption with Smart Meters , 2012, ACNS.

[18]  Peter Y. A. Ryan,et al.  vVote: A Verifiable Voting System , 2014, TSEC.

[19]  Sanjay Kumar Madria,et al.  Secure Hierarchical Data Aggregation in Wireless Sensor Networks: Performance Evaluation and Analysis , 2009, 2012 IEEE 13th International Conference on Mobile Data Management.

[20]  Dominik Engel,et al.  Error-Resilient Masking Approaches for Privacy Preserving Data Aggregation , 2018, IEEE Transactions on Smart Grid.

[21]  Ben Adida,et al.  Helios: Web-based Open-Audit Voting , 2008, USENIX Security Symposium.

[22]  Zekeriya Erkin,et al.  Private data aggregation with groups for smart grids in a dynamic setting using CRT , 2015, 2015 IEEE International Workshop on Information Forensics and Security (WIFS).

[23]  Markus Jakobsson,et al.  Security of Signed ElGamal Encryption , 2000, ASIACRYPT.

[24]  Ian Richardson,et al.  Smart meter data: Balancing consumer privacy concerns with legitimate applications , 2012 .

[25]  Andreas Unterweger,et al.  Detecting Swimming Pools in 15-Minute Load Data , 2018, 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).

[26]  Ronald Cramer,et al.  A Secure and Optimally Efficient Multi-Authority Election Scheme ( 1 ) , 2000 .

[27]  Ivan Damgård,et al.  A Generalisation, a Simplification and Some Applications of Paillier's Probabilistic Public-Key System , 2001, Public Key Cryptography.

[28]  Taher El Gamal A public key cryptosystem and a signature scheme based on discrete logarithms , 1984, IEEE Trans. Inf. Theory.

[29]  Ronald Cramer,et al.  Design and Analysis of Practical Public-Key Encryption Schemes Secure against Adaptive Chosen Ciphertext Attack , 2003, SIAM J. Comput..

[30]  Jeremy Clark,et al.  Scantegrity II: End-to-End Verifiability for Optical Scan Election Systems using Invisible Ink Confirmation Codes , 2008, EVT.

[31]  Alptekin Küpçü,et al.  Understanding Game-Based Privacy Proofs for Energy Consumption Aggregation Protocols , 2019, IEEE Transactions on Smart Grid.