A Collaborative Approach to Anti-Spam
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1 A Collaborative Approach to Anti-Spam Chia-Mei Chen National Sun Yat-Sen University TWCERT/CC, Taiwan Agenda Introduction Proposed Approach System Demonstration Experiments Conclusion 1
2 Problems of Spam Mail Commercial Spam Reduce productivity waste network bandwidth and increase processing load of mail servers Spam mail may include pornography messages Problems of Spam Mail (2) Malicious Spam Virus Spam Worm Spam Rootkit Spam Backdoor Spam Botnet Phishing 2
3 Spam Filter Most Spam filter is standalone Filtering out spam mails based on mail header and keywords The most important problem of standalone spam filter is the content of unsolicited messages evolve and may change time by time a standalone mail filter might not be able to fast enough to catch up all new types of spam mails Collaborative Anti-spam Framework 3
4 Proposed System Spam rule generation Spam rule exchange Spam rule evolution System Architecture 4
5 Spam Rule Generation Using machine learning or statistic approach to generate exchangeable spam rules Decision tree Rough set Bayesian a Using header information, keyword frequency and format information as feature Selected Attributes Attributes Description From The sender'ss name and address. Reply to If this mail specifies an address for replies to go to CC If this mail has carbon copy Received It means where the message originated and what route it took to get to you. Subject The subject of this mail. Body The content of this mail. Length The length (byte) of this mail Domain The domain name of sender s mail server Multi part Does this mail be multi part? Text/Html The format of the content of mail. Hasform Does this mail have form? Table Does the content of mail have tables Rec_number The number of keyword in the mail Encoding The encoding of this mail 5
6 Rule Exchange Spam Rule Evolution R ii :the reward S i :the strength of rule i S i can be viewed as rule quality Si + Rii Si = β Si, 0 < β < 1 R ii Rii = R ii if rule i is used if rule i is not used if classify correctly if classify incorrectly 6
7 System Demonstration User Interface (mail client) Open web mail Rule Generate Rosetta Mail Pre-Process and Filter Procmail Rule Exchange XML Files Mail and Rule Repository MySQL Database User Interface (Inbox) Legitimate mail Feedback 7
8 User Interface (Spam folder ) Feedback Spam mail Rule Generation (Rosetta) 8
9 Mail Repository Performance Evaluation Performance Metrics Training and testing data source Experiment results 9
10 Performance Metrics Spam precision spam recall accuracy Miss rate Data Source TWCERT/CC MIS Department NSYSU University Spam mails 3,483 3,115 17,948 Legitimate mails Totals 4,294 3,646 18,939 Data are gathered from 2006/5/10 to 2006/5/30 10
11 Experiment Result- Spam Precision 100.0% 99.5% 99.0% 98.5% 98.0% 97.5% 10 May 20 May 30 May Rule A Rule A Rule B Rule A Rule B Rule C 10-May 20-May 30-May Rule A % % % Rule A Rule B % % % Rule A Rule B Rule C % % % Experiment Result- Spam Recall 100.0% 99.5% 99.0% 98.5% 98.0% 97.5% 97.0% 96.5% 96.0% 10 May 20 May 30 May Rule A Rule A Rule B Rule A Rule B Rule C 10-May 20-May 30-May Rule A % % % Rule A Rule B % % % Rule A Rule B Rule C % % % 11
12 Experiment Result- Miss Rate 16.00% 14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% 10 May 20 May 30 May Rule A Rule A Rule B Rule A Rule B Rule C 10-May 20-May 30-May Rule A % % % Rule A Rule B % % % Rule A Rule B Rule C % % % Experiment Result- Accuracy 99.5% 99.0% 98.5% 98.0% 97.5% 97.0% 96.5% 96.0% 95.5% 95.0% 10 May 20 May 30 May Rule A Rule A Rule B Rule A Rule B Rule C 10-May 20-May 30-May Rule A % % % Rule A Rule B % % % Rule A Rule B Rule C % % % 12
13 Conclusion Due to rule exchange and evolution, collaborative approach is better than standalone server Collaborative approach can extend to hierarchical architecture Some powerful server generate and exchange spam rules and spam rules can be transmitted to other powerless server In future study, spam rules can be generated by different rule-based approach and an integrated scheme will be developed Q&A Thank You!! 13
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