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Malicious Domain Name Recognition Based on Deep Neural Networks

  • Xiaodan Yan
  • Baojiang Cui
  • Jianbin Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11342)

Abstract

Malware steals private information by randomly generating a large number of malicious domain names every day using domain generation algorithms (DGAs), which pose a great threat to our daily Internet activity. To improve recognition accuracy for these malicious domain names, this paper proposes a malicious domain name detection algorithm based on deep neural networks to capture the characteristics of malicious domain names. The resulting model is called a Discriminator based on Hierarchical Bidirectional Recurrent Neural Networks (D-HBiRNN).

Keywords

Security Domain name Neural networks BiRNN LSTM 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.North China Electric Power UniversityBeijingChina

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