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Spam filter optimality based on signal detection theory

Published: 06 October 2009 Publication History

Abstract

Unsolicited bulk email, commonly known as spam, represents a significant problem on the Internet. The seriousness of the situation is reflected by the fact that approximately 97% of the total e-mail traffic currently (2009) is spam. To fight this problem, various anti-spam methods have been proposed and are implemented to filter out spam before it gets delivered to recipients, but none of these methods are entirely satisfactory. In this paper we analyze the properties of spam filters from the viewpoint of Signal Detection Theory (SDT). The Bayesian approach of Signal Detection Theory provides a basis for determining the optimality of spam filters, i.e. whether they provide positive utility to users. In the process of decision making by a spam filter various tradeoff's are considered as a function of the costs of incorrect decisions and the benefits of correct decisions.

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    cover image ACM Conferences
    SIN '09: Proceedings of the 2nd international conference on Security of information and networks
    October 2009
    322 pages
    ISBN:9781605584126
    DOI:10.1145/1626195
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 06 October 2009

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    Author Tags

    1. e-mail
    2. filters
    3. optimality
    4. signal detection theory (sdt).
    5. spam
    6. tradeoffs

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