E. Damiani, S. Vimercati, S. Paraboschi, P. Samarati, Andrea Tironi, L. Zaniboni
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We propose a decentralized privacy-preserving approach to spam filtering. Our solution exploits robust digests to identify messages that are a slight variation of one another and a peer-to-peer architecture between mail servers to collaboratively share knowledge about spam.
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