Evaluating deep learning approaches to characterize and classify the DGAs at scale-Reference-Cited by-同舟云学术

Evaluating deep learning approaches to characterize and classify the DGAs at scale

Published:2018-03-22 Issue:3 Volume:34 Page:1265-1276
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Vinayakumar R.¹,Soman K.P.¹,Poornachandran Prabaharan²,Sachin Kumar S.¹

Affiliation:

1. Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University, India

2. Center for Cyber Security Systems and Networks, Amrita School of Engineering, Amritapuri, Amrita Vishwa Vidyapeetham, Amrita University, India

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference21 articles.

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3. Rossow C. , Andriesse D. , Werner T. , Stone-Gross B. , Plohmann D. , Dietrich C.J. and Bos H. , SoK: P2PWNED – Modeling and Evaluating the Resilience of Peerto-Peer Botnets, In Proceedings of the 34th IEEE Symposium on Security and Privacy (S&P) (San Francisco), CA, 2013.

4. Analysis of a botnet takeover;Stone-Gross;Security Privacy, IEEE,2011

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