A Honey-imprint enabled Approach for Resisting Social Engineering Attacks

Zhaoxi Zhong, Wenjun Fan

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

Abstract

bstract In the Reconnaissance step of the Cyber Kill Chain (CKC) model, social engineering (SE) techniques are often used to obtain sensitive/private data. This paper proposes a “honey-imprint” enabled approach which takes advantage of Natural Language Processing (NLP) for detecting SE attacks, Generative Adversarial Networks (GAN) for generating decoys from original sensitive information, and steganography for imprinting the honey watermark. The purpose of honey-imprint is to protect the sensitive information in the original file while leaving a covert imprint on the honey file to identify the malicious user. With this, we can further capture malicious interactions (using honey-imprinted data) by the honeypot system. We implement a prototype to verify the design, and the experimental results show that the method is valid and effective.

Original languageEnglish
Title of host publicationAPNOMS 2023 - 24th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationIntelligent Management for Enabling the Digital Transformation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages302-305
Number of pages4
ISBN (Electronic)9788995004395
Publication statusPublished - 2023
Event24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023 - Sejong, Korea, Republic of
Duration: 6 Sept 20238 Sept 2023

Publication series

NameAPNOMS 2023 - 24th Asia-Pacific Network Operations and Management Symposium: Intelligent Management for Enabling the Digital Transformation

Conference

Conference24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023
Country/TerritoryKorea, Republic of
CitySejong
Period6/09/238/09/23

Keywords

  • Deceptive Defense
  • GAN
  • Honeypot
  • NLP
  • Social Engineering
  • Steganography

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