Immunity from Spam: An Analysis of an Artificial Immune System for Junk Email Detection

Lecture notes in computer sciencePublished 1 January 2005

Terri Oda, Tony White

DOI10.1007/11536444_21

Source URL

Citations59

SJR quartileQ2

SJR score0.35

SNIP0.55

TL;DR

An extended examination of the spam-detecting artificial immune system proposed in [1,2], focusing on comparison of scoring schemes, the effect of population size, and the libraries used to create the detectors is undertaken.

Abstract

Despite attempts to legislate them out of existence, spam messages (junk email) continue to fill electronic mailboxes around the world. With spam senders adapting to each technical solution put on the market, adaptive solutions are being incorporated into new products. This paper undertakes an extended examination of the spam-detecting artificial immune system proposed in [1,2], focusing on comparison of scoring schemes, the effect of population size, and the libraries used to create the detectors.

Keywords

Computer ScienceEngineeringSocial Sciences

A Bayesian Approach to Filtering Junk E-Mail

1,153 Citations1998Mehran Sahami, Susan Dumais +2 more

This work examines methods for the automated construction of filters to eliminate such unwanted messages from a user’s mail stream, and shows the efficacy of such filters in a real world usage scenario, arguing that this technology is mature enough for deployment.

Lecture notes in computer scienceGenetic and Evolutionary Computation — GECCO 2003

374 Citations2003CantÃº-Paz, Erick, Miller, Julian +16 more

This work extends the application of CPSO to the dynamic problem by considering a bi-modal parabolic environment of high spatial and temporal severity, and suggests that charged swarms perform best in the extreme cases, but neutral swarms are better optimizers in milder environments.

AISEC: an artificial immune system for e-mail classification

87 Citations2003Andrew Secker, Alex A. Freitas +1 more

An immune-inspired algorithm called AISEC is presented that is capable of continuously classifying electronic mail as interesting and non-interesting without the need for re-training and has a great potential for augmentation.

National Conference on Artificial IntelligenceSpamCop: A Spam Classification & Organisation Program

85 Citations1998Patrick Pantel, Dekang Lin

This work presents a simple, yet highly accurate, spam filtering program, called SpamCop, which is able to identify about 92% of the spams while misclassifying only about 1.16%" of the nonspam e-mails.

Lecture notes in computer scienceDeveloping an Immunity to Spam

64 Citations2003Terri Oda, Tony White

The use of an artificial immune system for another kind of protection: protection from unsolicited email, or spam.

Increasing the accuracy of a spam-detecting artificial immune system

45 Citations2003Terri Oda, Tony White

This paper tests the spam immune system against the publicly available spam assassin corpus of spam and non-spam, and extends the original system by looking at several methods of classifying email messages with the detectors produced by the immune system.

Hackers & Painters

13 Citations2004Paul Graham

Hackers & Painters: Big Ideas from the Computer Age, by Paul Graham takes readers on an unflinching exploration into what he calls "an intellectual Wild West."