Spam Mitigation Using Spatio-Temporal Reputations From Blacklist History

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Departmental Papers (CIS)
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CPS Internet of Things
Email spam
blacklists
reputation
Computer Sciences
Physical Sciences and Mathematics
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IP blacklists are a spam filtering tool employed by a large number of email providers. Centrally maintained and well regarded, blacklists can filter 80+% of spam without having to perform computationally expensive content-based filtering. However, spammers can vary which hosts send spam (often in intelligent ways), and as a result, some percentage of spamming IPs are not actively listed on any blacklist. Blacklists also provide a previously untapped resource of rich historical information. Leveraging this history in combination with spatial reasoning, this paper presents a novel reputation model (PreSTA), designed to aid in spam classification. In simulation on arriving email at a large university mail system, PreSTA is capable of classifying up to 50% of spam not identified by blacklists alone, and 93% of spam on average (when used in combination with blacklists). Further, the system is consistent in maintaining this blockage-rate even during periods of decreased blacklist performance. PreSTA is scalable and can classify over 500,000 emails an hour. Such a system can be implemented as a complementary blacklist service and used as a first-level filter or prioritization mechanism on an email server.

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2010-12-01
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Departmental Papers (CIS)
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2023-05-17T05:51:27.000
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26th Annual Computer Security Applications Conference, Orlando, Florida, December 5-9, 2010.
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