Usefulness of Honeypots Towards Data Security: A Systematic Literature Review

Kalpin Erlangga Silaen, Meyliana Meyliana, Harco Leslie Hendric Spits Warnars, Harjanto Prabowo, Achmad Nizar Hidayanto, Maria Susan Anggreainy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The increasing data volume given by the exponential growth of digital devices, cloud platforms, and the Internet of Things (IOT) had become an attractive target for attackers. This makes the search for innovative defense mechanisms intensified leading to a renewed focus on the utilization of honeypots to improve data security. This Systematic Literature Review (SLR) examines the usage and contributions of honeypots in data security field across diverse sectors and environments. Analyzing 38 selected articles from 2018 to 2023, the study highlights the growing adoption of honeypots as tools for detecting and preventing data breaches, exfiltration, and other security incidents. Our finding found that honeypots, with their deceptive capabilities, have proven could be deployed in sectors like healthcare, cloud computing, and industrial control systems and effective in detection and prevention data breaches, exfiltration, and other data breaches, making them as a crucial tool in the data security protection. The future of honeypots lies in their integration with machine learning and AI, to predict and counteract sophisticated. Moreover, evolving honeypots into tools for deterrence and corrective action opens new avenues for cybersecurity strategies. Their ability to act as deterrents by increasing perceived risks for attackers, coupled with their role in aiding recovery from data breaches through detailed forensic analysis, positions honeypots as a cornerstone in the development of resilient data security frameworks. This study paves the way for a more adaptive, proactive, and comprehensive approach to data security, highlighting the indispensable role of honeypots in the ever-evolving landscape of cybersecurity.

Original languageEnglish
Title of host publicationIWAIIP 2023 - Conference Proceeding
Subtitle of host publicationInternational Workshop on Artificial Intelligence and Image Processing
EditorsYessi Jusman
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages422-427
Number of pages6
ISBN (Electronic)9798350382914
DOIs
Publication statusPublished - 2023
Event2023 International Workshop on Artificial Intelligence and Image Processing, IWAIIP 2023 - Hybrid, Yogyakarta, Indonesia
Duration: 1 Dec 20232 Dec 2023

Publication series

NameIWAIIP 2023 - Conference Proceeding: International Workshop on Artificial Intelligence and Image Processing

Conference

Conference2023 International Workshop on Artificial Intelligence and Image Processing, IWAIIP 2023
Country/TerritoryIndonesia
CityHybrid, Yogyakarta
Period1/12/232/12/23

Keywords

  • data security
  • honeypot
  • machine learning
  • systematic literature review

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