Covid-19 Research

Research Article

OCLC Number/Unique Identifier:

A Distributed Representation for Domain Names: An Initial Report

General Science    Start Submission

Akihiro Satoh*, Gen Kitagata, Yutaka Fukuda and Yutaka Nakamura

Volume6-Issue6
Dates: Received: 2025-05-19 | Accepted: 2025-06-08 | Published: 2025-06-09
Pages: 642-645

Abstract

We propose a distributed representation approach for domain names based on DNS queries. This distributed representation enables domains to be embedded into vector spaces with reflecting data exchange in networks. Since the ground truth of the distributed representation is unknown, we indirectly evaluate our distributed representation based on the premise that the accuracy of the distributed representation is strongly related to the validity of similarity between domains in the distributed representation. The results suggest the feasibility of the concise and versatile representation for numerous domain names with accurately capturing their interrelations.

FullText HTML FullText PDF DOI: 10.37871/jbres2117


Certificate of Publication




Copyright

© 2025 Satoh A, et al., Distributed under Creative Commons CC-BY 4.0

How to cite this article

Satoh A, Kitagata G, Fukuda Y, Nakamura Y. A Distributed Representation for Domain Names: An Initial Report. J Biomed Res Environ Sci. 2025 Jun 09; 6(6): 642-645. doi: 10.37871/jbres2117, Article ID: JBRES2117, Available at: https:// www.jelsciences.com/articles/jbres2117.pdf


Subject area(s)

References


  1. Lawson C, Watts J. Quick answer: How can organizations use dns to improve their security posture? Gartner Research. 2021.
  2. Ma Z, Li Q, Meng X. Discovering suspicious APT families through a large-scale domain graph in information-centric IoT. IEEE. 2019;7:13917-13926.
  3. Xu H, Zhang Z, Yan J, Ma X. Evaluating the impact of name resolution dependence on the DNS. Security and Communication Networks. 2019;1-12. doi: 10.1155/2019/8565397.
  4. López W, Merlino J, Rodríguez-Bocca P. Learning semantic information from internet domain names using word embeddings. Engineering Applications of Artificial Intelligence. 2020;94:1-13. doi: 10.1016/j.engappai.2020.103823.
  5. Pang G, Shen C, Cao L, Hengel AVD. Deep learning for anomaly detection: A review. ACM Computing Surveys. 2022;54(2):1-38. doi: 10.1145/3439950.
  6. Di Gennaro G, Buonanno A, Palmieri FAN. Considerations about learning Word2Vec. The Journal of Supercomputing. 2021;77(11):12320-12335. doi: 10.1007/s11227-021-03743-2.


Comments


Swift, Reliable, and studious. We aim to cherish the world by publishing precise knowledge.

  • Brown University Library
  • University of Glasgow Library
  • University of Pennsylvania, Penn Library
  • University of Amsterdam Library
  • The University of British Columbia Library
  • UC Berkeley’s Library
  • MIT Libraries
  • Kings College London University
  • University of Texas Libraries
  • UNSW Sidney Library
  • The University of Hong Kong Libraries
  • UC Santa Barbara Library
  • University of Toronto Libraries
  • University of Oxford Library
  • Australian National University
  • ScienceOpen
  • UIC Library
  • KAUST University Library
  • Cardiff University Library
  • Ball State University Library
  • Duke University Library
  • Rutgers University Library
  • Air University Library
  • UNT University of North Texas
  • Washington Research Library Consortium
  • Penn State University Library
  • Georgetown Library
  • Princeton University Library
  • Science Gate
  • Internet Archive
  • WashingTon State University Library
  • Dimensions
  • Zenodo
  • OpenAire
  • Index Copernicus International
  • icmje
  •  International Scientific Indexing (ISI)
  • Sherpa Romeo
  • ResearchGate
  • Universidad De Lima
  • WorldCat
  • JCU Discovery
  • McGill
  • National University of Singepore Libraries
  • SearchIT
  • Scilit
  • SemantiScholar
  • Base Search
  • VU
  • KB
  • Publons
  • oaji
  • Harvard University
  • sjsu-library
  • UWLSearch
  • Florida Institute of Technology
  • CrossRef
  • LUBsearch
  • Universitat de Paris
  • Technical University of Denmark
  • ResearchBIB
  • Google Scholar
  • Microsoft Academic Search