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Security evaluation of pattern classifiers

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. 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/

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Security evaluation of pattern classifiers

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  1. Gmail Security of pattern classifier classification with voice recognition technique Based on the IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, NO. 99, may 2014 paper Security evaluation of pattern classifiers under attack

  2. A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional VenkatesanPrabu .J MANAGING DIRECTOR Microsoft Web Developer Advisory Council team member and a well known Microsoft Most Valuable Professional (MVP) for the year 2008, 2009, 2010,2011,2012,2013 ,2014. LakshmiNarayanan.J GENERAL MANAGER BlackBerry Server Admin. Oracle 10g SQL Expert. Arunachalam.J Electronic Architect Human Resourse Manager

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Architecture Diagram

  8. Records Breaks Asia Book Of Records Tamil Nadu Of Records India Of Records MVP Awards World Record

  9. Services: A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional Inplant Training. Internship. Workshop’s. Final Year Project’s. Industrial Visit. Contact Us: +91 98406 78906,+91 90037 18877 kaashiv.info@gmail.com www.kaashivinfotech.com Shivanantha Building (Second building to Ayyappan Temple),X41, 5th Floor, 2nd avenue,Anna Nagar,Chennai-40.

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