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Artificial Immune Systems (AIS) use the concepts and algorithms inspired by the theory of how the human immune system works. This paper presents the design and initial evaluation of a new artificial immune system for collaborative spam filtering. Collaborative spam filtering allows for the detection of not-previously-seen spam content, by exploiting its bulkiness. Their system uses two novel and possibly advantageous techniques for collaborative spam filtering. The first novelty is local processing of the signatures created from the emails prior to deciding whether and which of the generated signatures will be exchanged with other collaborating antispam systems. This processing exploits both the email-content profiles of the users and implicit or explicit feedback from the users and it uses customized AIS algorithms.
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