Multitask Identity-Aware Image Steganography via Minimax Optimization | IEEE Journals & Magazine | IEEE Xplore

Multitask Identity-Aware Image Steganography via Minimax Optimization

Publisher: IEEE

Abstract:

High-capacity image steganography, aimed at concealing a secret image in a cover image, is a technique to preserve sensitive data, e.g., faces and fingerprints. Previous ...View more

Abstract:

High-capacity image steganography, aimed at concealing a secret image in a cover image, is a technique to preserve sensitive data, e.g., faces and fingerprints. Previous methods focus on the security during transmission and subsequently run a risk of privacy leakage after the restoration of secret images at the receiving end. To address this issue, we propose a framework, called Multitask Identity-Aware Image Steganography (MIAIS), to achieve direct recognition on container images without restoring secret images. The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time. Thus, we introduce a simple content loss to preserve the identity information, and design a minimax optimization to deal with the contradictory aspects. We demonstrate that the robustness results can be transferred across different cover datasets. In order to be flexible for the secret image restoration in some cases, we incorporate an optional restoration network into our method, providing a multitask framework. The experiments under the multitask scenario show the effectiveness of our framework compared with other visual information hiding methods and state-of-the-art high-capacity image steganography methods. The code is available at https://github.com/jiabaocui/MIAIS .
Published in: IEEE Transactions on Image Processing ( Volume: 30)
Page(s): 8567 - 8579
Date of Publication: 01 September 2021

ISSN Information:

PubMed ID: 34469298
Publisher: IEEE

Funding Agency:


I. Introduction

Visual security authentication, e.g., face recognition [1]–[3] and fingerprint identification [4], has achieved considerable advances in recent years. Its wide application also poses a challenge that such sensitive data as face and fingerprint need to be protected. High-capacity image steganography, which generates a container image to conceal a secret image in a cover image, is an elegant and widespread technique to address this issue [5]. Previous methods [6], [7] focus on the protection of secret images during transmission. Consequently, they run a risk of visual privacy leakage after restoration: once the receiver is under attack, secret images can be stolen. To this end, we propose a framework, called Multitask Identity-Aware Image Steganography (MIAIS), to perform recognition directly on container images without restoring secret images, as shown in Fig. 1.

Comparison of previous image steganography methods and ours. An image steganography method generates a container image by hiding a secret image in a cover image. The container image would be transferred from a sender to a receiver. Our difference from previous methods lies in the processing of container images. Top: Previous methods restore secret images from container images for recognition, which raises a risk of privacy leakage. Bottom: Our framework performs recognition directly on container images.

References

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