Emerging Trends in Honeypot Research: A Review of Applications and Techniques

Authors

  • Vishal Kumar Department of Computer Science and Informatics, Central University of Himachal Pradesh, India
  • Sawan Bhardwaj Department of Computer Science and Informatics, Central University of Himachal Pradesh, India
  • Pradeep Chouksey Department of Computer Science and Informatics, Central University of Himachal Pradesh, India
  • Praveen Sadotra Department of Computer Science and Informatics, Central University of Himachal Pradesh, India
  • Mayank Chopra Department of Computer Science and Informatics, Central University of Himachal Pradesh, India

DOI:

https://doi.org/10.5281/zenodo.14811718

Keywords:

Attacks, Cyber-security attacks, Data Collection, Honeypots, Threat Detection

Abstract

Honeypots are decoys in cybersecurity, where a system is set up to attract and monitor cyber intruders. These systems appear vulnerable but are isolated and monitored, emulating the entire real world, for example, databases or IOT devices. To gain insight into their tactics, attackers interact with these decoys. Security teams can fortify their defences by learning about these emerging threats. Honeypots are classified on the basis of interaction offered. A low-interaction honeypot will only record the most basic attacks. High-interaction honeypots, in contrast, allow attackers to be interacted with on a higher level, yielding more insight as to how they operate. By adopting this approach early, organizations can better understand how they might be targeted by potential attackers. Besides enabling the early detection of threats, they publish decoys that honeypots distract attackers away from actual systems. But they fail to catch all attacks, particularly those that do not engage the decoy. Honeypots must be kept current to remain effective against rapidly evolving threats.

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Published

2025-02-05

How to Cite

Vishal Kumar, Sawan Bhardwaj, Pradeep Chouksey, Praveen Sadotra, & Mayank Chopra. (2025). Emerging Trends in Honeypot Research: A Review of Applications and Techniques. International Journal of Human Computations & Intelligence, 3(6), 370–377. https://doi.org/10.5281/zenodo.14811718