Design and Analysis of a Novel Authorship Verification Framework for Hijacked Social Media Accounts Compromised by a Human
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley-Hindawi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Compromising the online social network account of a genuine user, by imitating the user's writing trait for malicious purposes, is a standard method. Then, when it happens, the fast and accurate detection of intruders is an essential step to control the damage. In other words, an efficient authorship verification model is a binary classification for the investigation of the text, whether it is written by a genuine user or not. Herein, a novel authorship verification framework for hijacked social media accounts, compromised by a human, is proposed. Significant textual features are derived from a Twitter-based dataset. They are composed of 16124 tweets with 280 characters crawled and manually annotated with the authorship information. XGBoost algorithm is then used to highlight the significance of each textual feature in the dataset. Furthermore, the ELECTRE approach is utilized for feature selection, and the rank exponent weight method is applied for feature weighting. The reduced dataset is evaluated with many classifiers, and the achieved result of the F-score is 94.4%.
Açıklama
Anahtar Kelimeler
Kaynak
Security and Communication Networks
WoS Q Değeri
Q3
Scopus Q Değeri
N/A
Cilt
2021
