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1.
PLoS One ; 15(4): e0230997, 2020.
Article in English | MEDLINE | ID: mdl-32298280

ABSTRACT

The existing tamper detection schemes for absolute moment block truncation coding (AMBTC) compressed images are able to detect the tampering. However, the marked image qualities of these schemes can be enhanced, and their authentication methods may fail to detect some special tampering. We propose a secure AMBTC tamper detection scheme that preserves high image fidelity with excellent detectability. In the proposed approach, a bit in bitmaps of AMBTC codes is sequentially toggled to generate a set of authentication codes. The one that causes the least distortion is embedded into the quantization levels with the guidance of a key-generated reference table (RT). Without the correct key, the same reference table cannot be constructed. Therefore, the proposed method is able to detect various kinds of malicious tampering, including those special tampering techniques designed for RT-based authentication schemes. The proposed method not only offers better image quality, but also provides an excellent and satisfactory detectability as compared with previous works.


Subject(s)
Image Processing, Computer-Assisted , Security Measures , Algorithms , Computer Security/standards , Computer Security/statistics & numerical data , Data Compression/standards , Data Compression/statistics & numerical data , Humans , Image Processing, Computer-Assisted/standards , Image Processing, Computer-Assisted/statistics & numerical data , Internet/standards , Internet/statistics & numerical data , Security Measures/standards , Security Measures/statistics & numerical data
2.
PLoS One ; 14(2): e0212802, 2019.
Article in English | MEDLINE | ID: mdl-30811472

ABSTRACT

In this paper, we propose an efficient method for authenticating the absolute moment block truncation coding (AMBTC) compressed images with the capability to recover tampered blocks. The existing methods may not be able to detect some types of intentional tampering. Meanwhile, the tampered blocks are only recovered by their means, causing an unpleasant mosaic-like appearance. The proposed method classifies image blocks into groups according to their similarities, and the group information is recorded for the recovery purpose. The multiple copies of the group information are scrambled and embedded into the bitmap of smooth blocks. The dominant portions of quantization levels are adjusted to generate a set of authentication code candidates. The codes with the minimal distortion are embedded into the least significant bits (LSBs) of the quantization levels. The tampered blocks can be recovered by averaging those untampered ones with the same index. The experimental results show that the proposed method not only achieves an excellent marked image quality and detectability, but also offers a satisfactory recovered result.


Subject(s)
Computer Security , Data Compression/methods , Algorithms
3.
ScientificWorldJournal ; 2014: 604876, 2014.
Article in English | MEDLINE | ID: mdl-24977214

ABSTRACT

This paper proposes a separable reversible data-hiding scheme in encrypted image which offers high payload and error-free data extraction. The cover image is partitioned into nonoverlapping blocks and multigranularity encryption is applied to obtain the encrypted image. The data hider preprocesses the encrypted image and randomly selects two basic pixels in each block to estimate the block smoothness and indicate peak points. Additional data are embedded into blocks in the sorted order of block smoothness by using local histogram shifting under the guidance of the peak points. At the receiver side, image decryption and data extraction are separable and can be free to choose. Compared to previous approaches, the proposed method is simpler in calculation while offering better performance: larger payload, better embedding quality, and error-free data extraction, as well as image recovery.


Subject(s)
Algorithms , Computer Security , Image Interpretation, Computer-Assisted/methods , Signal Processing, Computer-Assisted
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