  As smart grids are getting popular and being widely implemented, preserving
the privacy of consumers is becoming more substantial. Power generation and
pricing in smart grids depends on the continuously gathered information from
the consumers. However, having access to the data relevant to the electricity
consumption of each individual consumer is in conflict with its privacy. One
common approach for preserving privacy is to aggregate data of different
consumers and to use their smart-meters for calculating the bills. But in this
approach, malicious consumers who send erroneous data to take advantage or
disrupt smart grid cannot be identified. In this paper, we propose a new
statistical-based scheme for data gathering and billing in which the privacy of
consumers is preserved, and at the same time, if any consumer with erroneous
data can be detected. Our simulation results verify these matters.
