Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities, whose exploitation may severely affect their performance, and consequently limit their practical utility. Extending pattern classification theory and design methods to adversarial settings is thus a novel and very relevant research direction, which has not yet been pursued in a systematic way. In this paper, we address one of the main open issues: evaluating at design phase the security of pattern classifiers, namely, the performance degradation under potential attacks they may incur during operation. We propose a framework for empirical evaluation of classifier security that formalizes and generalizes the main ideas proposed in the literature, and give examples of its use in three real applications. Reported results show that security evaluation can provide a more complete understanding of the classifier’s behavior in adversarial environments, and lead to better design choices. http://kaashivinfotech.com/ http://inplanttrainingchennai.com/ http://inplanttraining-in-chennai.com/ http://internshipinchennai.in/ http://inplant-training.org/ http://kernelmind.com/ http://inplanttraining-in-chennai.com/ http://inplanttrainingchennai.com/

1. Based on the IEEE TRANSACTIONS ON KNOWLEDGE AND DATA
ENGINEERING, NO. 99, may 2014 paper
Security evaluation of pattern classifiers under attack

2. Abstract
 Pattern classification systems are commonly used in adversarial
applications, like biometric authentication, network intrusion
detection, and spam filtering, in which data can be purposely
manipulated by humans to undermine their operation. As this
adversarial scenario is not taken into account by classical design
methods, pattern classification systems may exhibit vulnerabilities,
whose exploitation may severely affect their performance, and
consequently limit their practical utility. Extending pattern
classification theory and design methods to adversarial settings is thus
a novel and very relevant research direction, which has not yet been
pursued
 A systematic way. In this paper, we address one of the main open
issues: evaluating at design phase the security of pattern classifiers,
namely, the performance degradation under potential attacks they may
incur during operation. We propose a framework for empirical
evaluation of classifier security that formalizes and generalizes the
main ideas proposed in the literature, and give examples of its use in
three real applications. Reported results show that security evaluation
can provide a more complete understanding of the classifier’s behavior
in adversarial environments, and lead to better design choices

3. Proposed System
 In our proposed system, high effective authentication with the purpose
of log on to the email service securely and efficient spamming are
taken into consideration.
 Authentication in the form of fractal detection and recognition after
contour detection of the face using the image of the user is introduced.
 Since fractal detection and recognition is a unique method to identify
every human being, this concept is more effective in terms of
authenticating into the service.
 Pattern classifiers such as Keywords and URL’s for data check, tag
construction and keyword identity, automatic readings of mails are the
concepts used in this system.
 Administrator of the email service uses the pattern classifiers and
maintains a repository to filter out spam domains and keywords. Hence
this perception spam’s the frequent surplus mails from same domain
with different mail id.
 Automatic reading of mails to examine the spammed keyword is an
intriguing conception introduced in this system to overcome many
flaws in case of spam filtering.

4. Existing System
 Message passing through emails is one the well-known way of today’s
world since it is more effective and fast than any other sources.
 Authentication is the major part often involves verifying the validity of
at least one form of identifications of the users.
 Normally authentications for logging in to the email service by means
of username and password characters are applicable in the existing
system.
 Security type of authentication such as logging in to the email service
using the secret code received to the mobile device of the user is also
applicable.
 This in turn less effectual since anybody who accesses the user’s mobile
can log on to the service or there is no option in case of mobile theft.
 Spam is a typical message passing that floods the Internet with many
copies of the same message, in an attempt to force the message on
people who would not otherwise choose to receive it. Spam keyword
filtering is the way used in existing system to get rid of spam emails.
 Frequent mails from a mail id can be spammed if it is tested against
spam filter but the domain cannot be filtered under the spam filter.
Hence any number of email id can be created by the spammers to send
spam mail under the same domain.

5. System Requirements
 Hardware Requirements:
System : Pentium IV 2.4 GHz.
Hard Disk : 80 GB.
Floppy Drive : 1.44 Mb.
Monitor : 15 VGA Colour.
Mouse : Logitech.
Ram : 1 GB or Above
 Software Requirements:
Operating system : Windows 7
Front End : Dot net 4.0 (VS 2010)
Backend : SQL Server 2008 R2

6. Architecture Diagram