Developing a GUI Application: GPU-Accelerated Malicious Domain Detection
Author:
Affiliation:
1. eLink Design, Lexington, Kentucky, USA
2. Computer Science, Governors State University, University Park, Illinois, USA
3. Computer Science and Information Technology, Eastern Kentucky University, Richmond, Kentucky, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3564746.3587105
Reference15 articles.
1. Searching Structural Neighborhood of Malicious URLs to Improve Blacklisting
2. Zhe Fan , Feng Qiu , Arie Kaufman , and Suzanne Yoakum-Stover . 2004 . GPU Cluster for High Performance Computing. In SC'04: Proceedings of the 2004 ACM/IEEE conference on Supercomputing. IEEE , Pittsburgh, USA, 47--47. Zhe Fan, Feng Qiu, Arie Kaufman, and Suzanne Yoakum-Stover. 2004. GPU Cluster for High Performance Computing. In SC'04: Proceedings of the 2004 ACM/IEEE conference on Supercomputing. IEEE, Pittsburgh, USA, 47--47.
3. PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation
4. String Matching on a Multicore GPU Using CUDA
5. PsyBoG: A scalable botnet detection method for large-scale DNS traffic
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