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In this paper, we propose two efficient and privacy-preservingdata aggregation protocols for WSNs: PASKOS (Privacy preserving basedon Anonymously Shared Keys and Omniscient Sink) and PASKIS (Pri-vacy preserving based on Anonymously Shared Keys and Ignorant Sink)—requiring low overhead. Both protocols guarantee privacy preservationand a high data-loss resilience. In particular, PASKOS effectively pro-tects the privacy of any node against other nodes, by requiring O(log N )communication cost in the worst case and O(1) on average, and O(1) asfor memory and computation. PASKIS can even protect a node’s privacyagainst a compromised sink, requiring only O(1) overhead as for compu-tation, communication, and memory; however, these gains in efficiencyare traded-off with a (slightly) decrease in the assured level of privacy.A thorough analysis and extensive simulations demonstrate the supe-rior performance of our protocols against existing solutions in terms ofprivacy-preserving effectiveness, efficiency, and accuracy of computed ag-gregation

Preserving privacy against external and internal threats in WSN data aggregation