A Distributed Representation for Domain Names: An Initial Report

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Smarter Cybersecurity: Domain Names as Vectors

A breakthrough study from Akihiro Satoh and team (Kyushu Institute of Technology) introduces a novel method of representing domain names as vectors using DNS query data. Published in the Journal of Biomedical Research & Environmental Sciences (JBRES), this approach enables AI-powered analysis of domain interactions—revolutionizing network security.

🔐 Key Highlights:

  • Converts DNS logs into vector embeddings using a modified Word2Vec model
  • Captures domain interrelationships with 93% accuracy
  • Boosts capabilities in malware detection, anomaly detection, and security log analysis

This concise and scalable method is perfect for machine learning and large-scale network surveillance.

📚 Why Submit to JBRES?

  • 🕒 Fast Publication – Decision in ~21 days
  • 💸 Flexible APC Discounts – Up to 30% for invited and low-income authors
  • 🌍 Open Access & Indexed Globally – Google Scholar, IndexCopernicus (ICV 88.03)
  • ✅ Plagiarism Checked (iThenticate) and DOI assigned
  • 🔁 Double-blind peer review for fair and quality assessment

📥 Submit your manuscript today:
🔗 Online Submission Form

📧 Contact us:

  • Lisa.a@scireslit.us
  • lisaarya.srl@gmail.com

🔗 Read the full article:
"A Distributed Representation for Domain Names: An Initial Report"
https://www.jelsciences.com/articles/jbres2117.pdf

#Cybersecurity #MachineLearning #DNS #DomainNames #AI #NetworkSecurity #JBRES #DeepLearning #AIResearch #OpenAccess #ResearchPublication #Word2Vec #SecurityAI #DNSAnalytics #SubmitYourManuscript

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