1. TABLE OF CONTENT Abstract Existing System Disadvantages Proposed System Advantages Modules Screen shorts Conclusion

2. ABSTRACT: Compromised machines are one of the key security threats on the Internet; they are often used to launch various security attacks such as spamming and spreading malware, and identity theft. we focus on the detection of the compromised machines in a network that are involved in the spamming activities, commonly known as spam zombies. We develop an effective spam zombie detection system named SPOT by monitoring outgoing messages of a network. SPOT is designed based on a powerful statistical tool called Sequential Probability Ratio Test, which has bounded false positive and false negative error rates. 3. HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB. Floppy Drive : 1.44 Mb. Monitor : 15 VGA Colour. Mouse : Logitech. Ram : 512 Mb. 4. SOFTWARE REQUIREMENTS: Operating system : Windows XP. Coding Language : JAVA DataBase : MYSQL 5. EXISTING SYSTEM: Major security challenge on the Internet is the existence of the large number of compromised machines. Such machines have been increasingly used to launch various security attacks including spamming and spreading malware, and identity theft. 6. DISADVANTAGES OF EXISTING SYSTEM: They are often used to launch various security attacks such as spamming and spreading malware, and identity theft. A major security challenge on the Internet is the existence of the large number of compromised machines. 7. PROPOSED SYSTEM: In this paper, we focus on the detection of the compromised machines in a network that are used for sending spam messages, which are commonly referred to as spam zombies. In proposed system to develop an effective spam zombie detection system named SPOT. SPOT is used to monitoring outgoing messages of a network. SPOT is designed based on a statistical method called sequential probability ratio test (SPRT). 8. ADVANTAGES OF PROPOSED SYSEM: SPOT is an effective and efficient system in automatically detecting compromised machines in a network. For example, among the 440 internal IP addresses observed in the e-mail trace, SPOT identifies 132 of them as being associated with compromised machines. Out of the 132 IP addresses identified by SPOT, 126 can be either independently confirmed (110) or are highly likely (16) to be compromised. 9. LIST OF MODULES: Account authentication Sending mails SPOT detection capture IP SPOT filter SPOT results CT detection. PT detection 10. Account authentication In this module to check the mail id and password. If these two fields are valid, the account is authenticated. Otherwise is not valid. 11. Sending mails This module a single person to send one or more mails to other person. This mails either spam or non spam. Spam means the more copies of the single message are send. And it contains more than 20 lines. 12. SPOT detection In this module to capture the IP address of the system. That system mails are applied to filtering process. In this process, the mail content is filtered. Finally to produce the result of filter. 13. CT detection In this module to set the threshold value Cs . Cs denotes the fixed length of spam mail. Also to count the number of lines in each mail. If the each mail, counts are greater than equal to threshold value. So, these mails are spam mail. 14. PT detection In this module to set two threshold values. 1) Ca- specifies the minimum number of mail that machine must send. 2) P- specifies the maximum spam mail percentage of a normal machine. This algorithm is used to compute the count of total mails and the count of spam mails of machine. To check this count of total mails are greater than equal to Cs and the count of spam mails are greater than equal to P. If its true these mails are spam mail. 15. Screen Shots : 1.open an account 16. 2. Account authentication : 17. 3. Sending mails 18. To send mail 20 times in different users. 19. 4. SPOT Detection 20. 5. CT Detection 21. 6. PT Detection 22. Conclusion: In this paper, we developed an effective spam zombie detection system named SPOT by monitoring outgoing messages in a network. SPOT was designed based on a simple and powerful statistical tool named Sequential Probability Ratio Test to detect the compromised machines that are involved in the spamming activities. SPOT has bounded false positive and false negative error rates. 23. REFERENCE: Zhenhai Duan, Senior Member, IEEE, Peng Chen, Fernando Sanchez, Yingfei Dong, Member, IEEE, Mary Stephenson, and James Michael Barker, Detecting Spam Zombies by Monitoring Outgoing Messages, 24. Queries ?.... 25. THANK YOU