{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1692"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1692","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Identifying users on social networking using pattern recognition in messages","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Joshuva, Justin"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kandah, Farah","Tanis, Craig; Gunesakara, Sumith","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:51Z","subjects":["Online social networks -- Security measures","Computer networks -- Security measures"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/539","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kandah, Farah","Tanis, Craig; Gunesakara, Sumith","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Joshuva, Justin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-12-01T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Online social networks -- Security measures","Computer networks -- Security measures"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/539"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","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."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Identifying users on social networking using pattern recognition in messages"]}]}],"canonical_facts":{"dc:contributor":["Kandah, Farah","Tanis, Craig; Gunesakara, Sumith","College of Engineering and Computer Science"],"dc:creator":["Joshuva, Justin"],"dc:date":["2017-12-01T08:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","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."],"dc:description.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."],"dc:identifier":["https://scholar.utc.edu/theses/539"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["https://rightsstatements.org/page/InC/1.0/?language=en"],"dc:subject":["Online social networks -- Security measures","Computer networks -- Security measures"],"dc:title":["Identifying users on social networking using pattern recognition in messages"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:46:51Z"}