Image self-recovery based on authentication feature extraction

Tong Liu; Xiaochen Yuan

doi:10.1109/TrustCom50675.2020.00164

Image self-recovery based on authentication feature extraction

Tong Liu, Xiaochen Yuan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a novel image self-recovery scheme based on authentication feature extraction. The Authentication Feature Extraction method is proposed to calculate the authentication information. The Set Partitioning in Hierarchical Trees encoding algorithm is employed to calculate the recovery information. Moreover, in order to retrieve the damaged information caused by tampering, we propose to map each block into another position and generate the mapped-recovery information accordingly. In this way, a double assurance of recovery information can be provided. Experimental results show the superior performance of the proposed scheme in terms of image self-recovery. Comparison with the state-of-the-art works demonstrate that the proposed scheme shows efficiency in strong capability for image recovery, and effectiveness of attack resistance.

Original language	English
Title of host publication	Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
Editors	Guojun Wang, Ryan Ko, Md Zakirul Alam Bhuiyan, Yi Pan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1222-1227
Number of pages	6
ISBN (Electronic)	9781665403924
DOIs	https://doi.org/10.1109/TrustCom50675.2020.00164
Publication status	Published - Dec 2020
Externally published	Yes
Event	19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 - Guangzhou, China Duration: 29 Dec 2020 → 1 Jan 2021

Publication series

Name	Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

Conference

Conference	19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
Country/Territory	China
City	Guangzhou
Period	29/12/20 → 1/01/21

Keywords

Authentication Feature Extraction
Authentication Information
Image Self-Recovery
Recovery Information
Set Partitioning in Hierarchical Trees

Access to Document

10.1109/TrustCom50675.2020.00164

Cite this

Liu, T., & Yuan, X. (2020). Image self-recovery based on authentication feature extraction. In G. Wang, R. Ko, M. Z. A. Bhuiyan, & Y. Pan (Eds.), Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 (pp. 1222-1227). Article 9343106 (Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TrustCom50675.2020.00164

Liu, Tong ; Yuan, Xiaochen. / Image self-recovery based on authentication feature extraction. Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020. editor / Guojun Wang ; Ryan Ko ; Md Zakirul Alam Bhuiyan ; Yi Pan. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 1222-1227 (Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020).

@inproceedings{839e27af5b984b2a94dfa142c64315aa,

title = "Image self-recovery based on authentication feature extraction",

abstract = "This paper proposes a novel image self-recovery scheme based on authentication feature extraction. The Authentication Feature Extraction method is proposed to calculate the authentication information. The Set Partitioning in Hierarchical Trees encoding algorithm is employed to calculate the recovery information. Moreover, in order to retrieve the damaged information caused by tampering, we propose to map each block into another position and generate the mapped-recovery information accordingly. In this way, a double assurance of recovery information can be provided. Experimental results show the superior performance of the proposed scheme in terms of image self-recovery. Comparison with the state-of-the-art works demonstrate that the proposed scheme shows efficiency in strong capability for image recovery, and effectiveness of attack resistance.",

keywords = "Authentication Feature Extraction, Authentication Information, Image Self-Recovery, Recovery Information, Set Partitioning in Hierarchical Trees",

author = "Tong Liu and Xiaochen Yuan",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 ; Conference date: 29-12-2020 Through 01-01-2021",

year = "2020",

month = dec,

doi = "10.1109/TrustCom50675.2020.00164",

language = "English",

series = "Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1222--1227",

editor = "Guojun Wang and Ryan Ko and Bhuiyan, {Md Zakirul Alam} and Yi Pan",

booktitle = "Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020",

address = "United States",

}

Liu, T & Yuan, X 2020, Image self-recovery based on authentication feature extraction. in G Wang, R Ko, MZA Bhuiyan & Y Pan (eds), Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020., 9343106, Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020, Institute of Electrical and Electronics Engineers Inc., pp. 1222-1227, 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020, Guangzhou, China, 29/12/20. https://doi.org/10.1109/TrustCom50675.2020.00164

Image self-recovery based on authentication feature extraction. / Liu, Tong; Yuan, Xiaochen.
Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020. ed. / Guojun Wang; Ryan Ko; Md Zakirul Alam Bhuiyan; Yi Pan. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1222-1227 9343106 (Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Image self-recovery based on authentication feature extraction

AU - Liu, Tong

AU - Yuan, Xiaochen

PY - 2020/12

Y1 - 2020/12

N2 - This paper proposes a novel image self-recovery scheme based on authentication feature extraction. The Authentication Feature Extraction method is proposed to calculate the authentication information. The Set Partitioning in Hierarchical Trees encoding algorithm is employed to calculate the recovery information. Moreover, in order to retrieve the damaged information caused by tampering, we propose to map each block into another position and generate the mapped-recovery information accordingly. In this way, a double assurance of recovery information can be provided. Experimental results show the superior performance of the proposed scheme in terms of image self-recovery. Comparison with the state-of-the-art works demonstrate that the proposed scheme shows efficiency in strong capability for image recovery, and effectiveness of attack resistance.

AB - This paper proposes a novel image self-recovery scheme based on authentication feature extraction. The Authentication Feature Extraction method is proposed to calculate the authentication information. The Set Partitioning in Hierarchical Trees encoding algorithm is employed to calculate the recovery information. Moreover, in order to retrieve the damaged information caused by tampering, we propose to map each block into another position and generate the mapped-recovery information accordingly. In this way, a double assurance of recovery information can be provided. Experimental results show the superior performance of the proposed scheme in terms of image self-recovery. Comparison with the state-of-the-art works demonstrate that the proposed scheme shows efficiency in strong capability for image recovery, and effectiveness of attack resistance.

KW - Authentication Feature Extraction

KW - Authentication Information

KW - Image Self-Recovery

KW - Recovery Information

KW - Set Partitioning in Hierarchical Trees

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T3 - Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

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BT - Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

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A2 - Ko, Ryan

A2 - Bhuiyan, Md Zakirul Alam

A2 - Pan, Yi

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

Y2 - 29 December 2020 through 1 January 2021

ER -

Liu T, Yuan X. Image self-recovery based on authentication feature extraction. In Wang G, Ko R, Bhuiyan MZA, Pan Y, editors, Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 1222-1227. 9343106. (Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020). doi: 10.1109/TrustCom50675.2020.00164

Image self-recovery based on authentication feature extraction

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Keywords

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