Current Proceedings on Technology

Yazarlar: Ekin Ekinci, Hidayet Takçı

Konular:-

Anahtar Kelimeler:Forensic Science,Authorship identification,Emails,Ensemble classifiers

Özet: As a result of powerful features and ongoing improvements of the Internet, electronic mail has become one of today’s most important communication tools. Electronic mail, which provides conveniences to its user in many cases, is also an attractive medium for criminals. While malicious electronic mail whose actual owner is unknown is taking place in computer crimes, authorship identification has become necessary for determining the actual owner of it. This study describes an application with the aim of authorship identification of electronic mails in terms of forensic science and this application can improve the security and can find the actual owner of these electronic mails based on message body. Bagging and AdaBoostM1 algorithms, which are ensemble classifiers in machine learning and have good generalization performance, processed 49 textual features extracted from a dataset, which contains 250 electronic mails from 5 writers. According to F-measure Bagging provided better generalization performance than AdaBoostM1.

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