Committee Chair

Kandah, Farah

Committee Member

Tanis, Craig; Gunesakara, Sumith

Department

Dept. of Computer Science and Engineering

College

College of Engineering and Computer Science

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Online social networks, such as Facebook and Twitter, have become a huge part of many people's lives, often as their main means of communication with other people. Because of frequency of use and the apparent security measures of these sites, users often falsely believe the proffered identity of the person they are talking to. This blind belief sometimes results in security threats due to the passing of private or confidential information to the wrong user. This may lead to malicious readers getting a user's private information and using it illegally. This work proposes a mathematical model for identifying security threats using pattern recognition with the aid of an extension of the Naive Bayes method called the Friendship Naive Bayes. Since specific patterns could be observed by examining the communication history between users, the proposed scheme uses these patterns to authenticate that the new message was written by the same person from the history. The scheme then calculates the probability of identifying the person as either the correct or incorrect user.

Acknowledgments

Dr. Farah Kandah, Dr. Craig Tanis and Dr. Sumit Gunesakara

Degree

M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.

Date

12-2017

Subject

Online social networks -- Security measures; Computer networks -- Security measures

Keyword

Social network; Pattern recognition; Facebook; Naive; Bayes; Messages

Document Type

Masters theses

Extent

xii, 34 leaves

Language

English

Rights

Under copyright.

License

http://creativecommons.org/licenses/by-nc-nd/3.0/

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