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Register a new userUsing Chaotic Stream Cipher to Enhance Data Hiding in Digital Images
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Added by
Mohammad AL-Mousa Dr
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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No Arabic abstract
The growing potential of modern communications needs the use of secure means to protect information from unauthorized access and use during transmission. In general, encryption a message using cryptography techniques and then hidden a message with a steganography methods provides an additional layer of protection. Furthermore, using these combination reduces the chance of finding the hidden message. This paper proposed a system which combines schemes of cryptography with steganography for hiding secret messages and to add more complexity for steganography. The proposed system secret message encoded with chaotic stream cipher and afterwards the encoded data is hidden behind an RGB or Gray cover image by modifying the kth least significant bits (k-LSB) of cover image pixels. The resultant stego-image less distorters. After which can be used by the recipient to extract that bit-plane of the image. In fact, the schemes of encryption/decryption and embedding/ extracting in the proposed system depends upon two shred secret keys between the sender and the receiver. An experiment shows that using an unauthorized secret keys between the sender and the receiver have totally different messages from the original ones which improve the confidentiality of the images.
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Reversible data hiding in encrypted images (RDH-EI) has attracted increasing attention, since it can protect the privacy of original images while the embedded data can be exactly extracted. Recently, some RDH-EI schemes with multiple data hiders have been proposed using secret sharing technique. However, these schemes protect the contents of the original images with lightweight security level. In this paper, we propose a high-security RDH-EI scheme with multiple data hiders. First, we introduce a cipher-feedback secret sharing (CFSS) technique. It follows the cryptography standards by introducing the cipher-feedback strategy of AES. Then, using the CFSS technique, we devise a new (r,n)-threshold (r<=n) RDH-EI scheme with multiple data hiders called CFSS-RDHEI. It can encrypt an original image into n encrypted images with reduced size using an encryption key and sends each encrypted image to one data hider. Each data hider can independently embed secret data into the encrypted image to obtain the corresponding marked encrypted image. The original image can be completely recovered from r marked encrypted images and the encryption key. Performance evaluations show that our CFSS-RDHEI scheme has high embedding rate and its generated encrypted images are much smaller, compared to existing secret sharing-based RDH-EI schemes. Security analysis demonstrates that it can achieve high security to defense some commonly used security attacks.
We follow two main objectives in this article. On the one hand, we introduce a security model called LORBACPA$^+$ for self-synchronized stream ciphers which is stronger than the blockwise LOR-IND-CPA, where we show that standard constructions as delayed CBC or similar existing self-synchronized modes of operation are not secure in this stronger model. Then, on the other hand, following contributions of G.~Mill{e}rioux et.al., we introduce a new self-synchronized stream cipher and prove its security in LORBACPA$^+$ model.
Data hiding is referred to as the art of hiding secret data into a digital cover for covert communication. In this letter, we propose a novel method to disguise data hiding tools, including a data embedding tool and a data extraction tool, as a deep neural network (DNN) with an ordinary task. After training a DNN for both style transfer and data hiding, while the DNN can transfer the style of an image to a target one, it can be also used to hide secret data into a cover image or extract secret data from a stego image by inputting the trigger signal. In other words, the tools of data hiding are hidden to avoid arousing suspicion.
This paper presents a new general framework of information hiding, in which the hidden information is embedded into a collection of activities conducted by selected human and computer entities (e.g., a number of online accounts of one or more online social networks) in a selected digital world. Different from other traditional schemes, where the hidden information is embedded into one or more selected or generated cover objects, in the new framework the hidden information is embedded in the fact that some particular digital activities with some particular attributes took place in some particular ways in the receiver-observable digital world. In the new framework the concept of cover almost disappears, or one can say that now the whole digital world selected becomes the cover. The new framework can find applications in both security (e.g., steganography) and non-security domains (e.g., gaming). For security applications we expect that the new framework calls for completely new steganalysis techniques, which are likely more complicated, less effective and less efficient than existing ones due to the need to monitor and analyze the whole digital world constantly and in real time. A proof-of-concept system was developed as a mobile app based on Twitter activities to demonstrate the information hiding framework works. We are developing a more hybrid system involving several online social networks.
Reversible data hiding in encrypted images is an eff ective technique for data hiding and preserving image privacy. In this paper, we propose a novel schema based on polynomial arithmetic, which achieves a high embedding capacity with the perfect recovery of the original image. An effi cient two-layer symmetric en- cryption method is applied to protect the privacy of the original image. One polynomial is generated by the encryption key and a group of the encrypted pixel, and the secret data is mapped into another polynomial. Through the arithmetic of these two polynomials, the purpose of this work is achieved. Fur- thermore, pixel value mapping is designed to reduce the size of auxiliary data, which can further improve embedding capacity. Experimental results demon- strate that our solution has a stable and good performance on various images. Compared with some state-of-the-art methods, the proposed method can get better decrypted image quality with a large embedding capacity.
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