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E-DPNCT: An Enhanced Attack Resilient Differential Privacy Model For Smart Grids Using Split Noise Cancellation. (arXiv:2110.11091v3 [cs.CR] UPDATED)
cs.CR updates on arXiv.org arxiv.org
High frequency reporting of energy consumption data in smart grids can be
used to infer sensitive information regarding the consumers life style and
poses serious security and privacy threats. Differential privacy (DP) based
privacy models for smart grids ensure privacy when analysing energy consumption
data for billing and load monitoring. However, DP models for smart grids are
vulnerable to collusion attack where an adversary colludes with malicious smart
meters and un-trusted aggregator in order to get private information from other …
attack billing consumers data differential privacy energy high information life monitoring noise privacy reporting security sensitive information serious smart threats vulnerable