Open AccessLSTM Network Based Malicious Domain Name Detection
Author(s) -
Gurpreet Singh Josan,
Jagroop Kaur
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f8809.088619
Subject(s) - computer science , task (project management) , domain (mathematical analysis) , domain name , artificial intelligence , class (philosophy) , artificial neural network , machine learning , data mining , world wide web , the internet , mathematical analysis , mathematics , management , economics
Detecting malicious domain names attract lot of research in recent years. Researchers tried various text based, network traffic based and combination of these methods to detect malicious names. In this paper, we analyze the possibility of detection malicious names using deep neural network based models. Bidirectional LSTM network has been developed and trained on the dataset. Two tasks were experimented. First task was to identify malicious domain name and second task was to identify the class of domain name. Proposed method is able to perform well on task 1 producing 98.9% accuracy whereas on task 2 it is able to achieve accuracy of 69.7% only.