Spam Detection Using IsMail - An Artificial Immune System For Mail
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1 Spam Detection Using IsMail - An Artificial Immune System For Mail Slavisa Sarafijanovic and Jean-Yves Le Boudec, EPFL MICS, Neuchatel, August 2-3, /6 MICS
2 IsMail An Artificial Immune System For Collaborative Spam Detection An artificial immune system is a system based on the principles of the human immune system One antispam system (Ismail is added per server. Antispam systems collaborate. EPFL ETHZ UNIL 2/6
3 Let first recall what information can be used for automated spam recognition 1. Spammines of words Per user learned database: P( Spam Credit_card = 0.8 P( Spam Cent = 0.95 P( Spam Picture = New spam and mind, said Zeb, we don't and mind, said Zeb, we don't 2. Bulkiness of spam Spam bulk: Detecting bulkiness: User 1 User 2 User N Not used enough! Counter Compute P( Spam Picture, NewYear, Credit_card, Per user! 3. Sender information Sent From: [email protected] Sent From: [email protected] Botnets, Nigerian spam! 3/6
4 How our artificial immune system (AIS detects spam? (1/2 AIS produces and uses detectors - detectors are binary strings able to recognize (using similarity matching spammy portions of s Set of detectors: similarity matching New and mind, said Zeb, we don't similarity hashing spam/normal 4/6
5 How our artificial immune system detects spam? (2/2 How the detectors are produced: Negative Selection Maturation delete as spam feedback from the protected system 1 random candidate detectors 5 new old (memory Maturation (another system randomness adaptation to the user s profile local processing collaboration (discover new bulky spam active detectors Conclusion: AIS approach seems to fit well distributed detection problems Analogy to the human immune system: steps 1-5! 5/6
6 Project Status Initial evaluation (simulation: Patented design: True Positive False Positive Not obfuscated spam Obfuscated spam METHOD TO FILTER ELECTRONIC MESSAGES IN A MESSAGE PROCESSING SYSTEM, US patent No 11/515,063, filed on Sept 5, Built a realistic prototyping and evaluation platform: Preliminary detection results with respect to the number of collaborating antispam systems: modest collaboration (small number of neighboring servers enables promising detection results; the system is resistant to the tested obfuscation by spammer. (Disclaimer: simulation assumptions! AntispamLab A Tool For Realistic Evaluation of Spam Filters, accepted for The Fourth Conference on and Antispam, Mountain View, California, USA, August 2-3, /6
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