Paper Title

Optimizing Honeypot Deployment in Ultra-Dense Beyond 5G Networks Using Deep Q-Networks: A Novel Reinforcement Learning Strategy

Article Identifiers

Registration ID: IJNRD_214526

Published ID: IJNRD2404060

DOI: Click Here to Get

Authors

Vijaya S Rao , Kumaraswamy S

Keywords

Honeypot, Intrusion Detection, Deep Q-Network, Reinforcement Learning, Beyond 5G Networks, Cybersecurity.

Abstract

In the landscape of Beyond 5G networks, the fusion of Software Defined Networking (SDN) and virtualization heralds a new phase of digital connectivity, albeit with heightened security vulnerabilities. This research introduces an innovative security strategy utilizing Deep Q-Networks (DQN) for the deployment of honeypots, sophisticated decoy systems designed to entrap cyberattackers, thereby safeguarding genuine network assets. Diverging from traditional reinforcement learning techniques, our approach harnesses the advanced capabilities of DQN to navigate the complex, dynamic environment of ultra-dense networks more efficiently. We propose a DQN-based framework that not only overcomes the limitations of data dependency inherent in machine and deep learning models but also dynamically adapts to evolving cyber threats, ensuring robust network security. Through extensive simulations, we demonstrate the enhanced performance of our method in optimizing honeypot deployment, marking a significant step forward in the proactive defense mechanisms for next-generation networks.

How To Cite (APA)

Vijaya S Rao & Kumaraswamy S (April-2024). Optimizing Honeypot Deployment in Ultra-Dense Beyond 5G Networks Using Deep Q-Networks: A Novel Reinforcement Learning Strategy. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), a463-a472. https://ijnrd.org/papers/IJNRD2404060.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : a463-a472

Other Publication Details

Paper Reg. ID: IJNRD_214526

Published Paper Id: IJNRD2404060

Downloads: 000121994

Research Area: Engineering

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404060.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404060

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

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Subject Category: Research Area

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