IH-SESD: Modeling Information Hiding With Super-Resolution Enhancement and Significant Region Detection for UAV Networks

Mianjie Li, Haozheng Cui, Chun Shan, Xiaojiang Du, Mohsen Guizani

Research output: Contribution to journalArticlepeer-review

Abstract

The advent of unmanned aerial vehicle (UAV) networks, renowned for their expansive coverage capabilities and heightened adaptability, presents a promising landscape for bolstering the efficacy of Internet of Things (IoT) data transmissions. Nevertheless, the integration of UAVs into IoT ecosystems introduces a spectrum of security challenges, notably data tampering, man-in-the-middle (MitM) attacks, and eavesdropping, which threaten the integrity and confidentiality of transmitted information. Since covert transmission has the characteristics of strong concealment and difficult detection, UAV networks based on information hiding become a new paradigm for solving these security problems. This article proposes an information hiding algorithm based on super-resolution enhancement and significant region detection (IH-SESD). This algorithm incorporates the super-resolution enhanced SRCNN and the U2Net salient region detection technologies. Comprehensive performance analysis and comparisons with existing methods demonstrate the superiority of the proposed IH-SESD algorithm.

Original languageEnglish
Pages (from-to)9383-9390
Number of pages8
JournalIEEE Internet of Things Journal
Volume12
Issue number8
DOIs
StatePublished - 2025

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • Information hiding
  • Internet of Things (IoT)
  • significant area detection
  • super-resolution enhancement
  • unmanned aerial vehicle (UAV) networks

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