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Privacy-preserving metering aggregation is regarded as an important research topic in securing a smart grid. In this paper, we first identify and formalize a new attack, in which the attacker could exploit the information about the presence or absence of a specific person to infer his meter readings. This attack, coined as human-factor-aware differential aggregation (HDA) attack, cannot be addressed in existing privacy-preserving aggregation protocols proposed for smart grids. We give a formal definition on it and propose two novel protocols, including basic scheme and advanced scheme, to achieve privacy-preserving smart metering data aggregation and to resist the HDA attack. Our protocol ensures that smart meters periodically upload encrypted measurements to a (electricity) supplier/aggregator such that the aggregator is able to derive the aggregated statistics of all meter measurements but is unable to learn …