MuDA: Multifunctional data aggregation in privacy-preserving smart grid communications
Privacy-preserving data aggregation has been widely studied to meet the requirement of timely monitoring electricity consumption of users while protecting individual users data privacy in smart grid communications. In this paper, we propose a new multifunctional data aggregation scheme, named MuDA, for privacy-preserving smart grid communications. With MuDA, the smart grid control center can compute multiple statistical functions of users data in a privacy-preserving way to provide diversiform services. Moreover, MuDA is also designed to resist differential attacks that most secure data aggregation schemes may suffer. Through detailed security and utility analyses, we demonstrate that MuDA preserves users data privacy with acceptable noise rate. In addition, extensive performance evaluations are conducted to illustrate that our MuDA scheme is more efficient than a popular aggregation scheme in terms of communication overhead.
privacy-preserving smart grid multifunctional aggregation differential privacy