Stylometric fingerprints and privacy behavior in textual data

مرکز و کتابخانه مطالعات اسلامی به زبان های اروپایی

منو

" Stylometric fingerprints and privacy behavior in textual data "
Aylin Caliskan-Islam Greenstadt, Rachel

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	803460
Doc. No	:	TL48249
Call number	:	‭1691134975;‮ ‬3705471‬
Main Entry	:	Farah, Warrick
Title & Author	:	Stylometric fingerprints and privacy behavior in textual data\ Aylin Caliskan-IslamGreenstadt, Rachel
College	:	Drexel University
Date	:	2015
Degree	:	Ph.D.
field of study	:	Computer Science
student score	:	2015
Page No	:	171
Note	:	Committee members: Greenstadt, Rachel; Mancoridis, Spiros; McCoy, Damon; Narayanan, Arvind; Salvucci, Dario
Note	:	Place of publication: United States, Ann Arbor; ISBN=978-1-321-78589-0
Abstract	:	Machine learning and natural language processing can be used to characterize and quantify aspects of human behavior expressed in language. Linguistic features exhibited in any kind of text can be used to study individuals' behavior as well as to identify an author among thousands of authors. Studying aspects of human behavior can be automated by incorporating machine learning techniques and well-engineered features that represent behavior of interest. Human behavior analysis can be used to enhance security by detecting malware programmers, malicious users, or abusive multiple account holders in online networks. At the same time, such an automated analysis is a serious threat to privacy, especially to the privacy of persons that would like to remain anonymous. Nevertheless, privacy enhancing technologies can be built by first and foremost understanding privacy infringing methods in-depth to create countermeasures.
Subject	:	Computer science
Descriptor	:	Applied sciences;De-anonymization;Forensics;Privacy;Privacy behavior;Security;Stylometry
Added Entry	:	Greenstadt, Rachel
Added Entry	:	Computer ScienceDrexel University