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User identification via neural network based language models
Author(s) -
Phan Tien D.,
ZincirHeywood Nur
Publication year - 2018
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.2049
Subject(s) - computer science , identification (biology) , phishing , artificial neural network , language model , artificial intelligence , machine learning , alarm , natural language processing , computer security , world wide web , the internet , botany , materials science , composite material , biology
Summary Identifying compromised accounts on online social networks that are used for phishing attacks or sending spam messages is still one of the most challenging problems of cyber security. In this research, the authors explore an artificial neural network‐based language model to differentiate the writing styles of different users on short text messages. In doing so, the aim is to be able to identify compromised user accounts. The results obtained indicate that one can learn the language model on one dataset and can generalize it to different datasets to identify users with high accuracy and low false alarm rates without any modification to the language model.