J3: High payload histogram neutral JPEG steganography

Abstract

Steganography is the art of secret communication between two parties that not only conceals the contents of a message but also its existence. Steganalysis attempts to detect the existence of embedded data in a steganographically altered cover file. Many algorithms have been proposed, but so far each has some weakness that has allowed its effects to be detected, usually through statistical analysis of the image. In this paper, we propose a different approach to JPEG steganography that provides high embedding capacity with zero-deviant histogram restoration. Our algorithm, named J3, uses stop points in its header structure that allows it to restore the histogram completely, making its detection impossible by any first order steganalysis. It gives better results with higher order steganalysis when compared to F5, Outguess and Steghide. As far as we know, there is no existing algorithm that can provide as high an embedding payload with complete histogram restoration.

A Review on Stegnography Data Hiding using Color Images

“…Notwithstanding the three key ideas of security, two other security objectives are basic with respect to cryptography: confirmation and non-revocation [10]. 1.…”

“…No Detection: Steganography fizzles in the event that somebody can without much of a stretch distinguish where you conceal your data and discover your message. In this way, regardless of whether somebody knows how the steganography strategy installs the mystery data, he or she can't without much of a stretch discover that you have implanted information in a given record [10]. 4.…”

“…J3 can be utilized to install a lot of information with protection from visual and first request factual assaults. To the extent we know, there is no current calculation that can furnish as high an inserting payload with finish histogram restoration [10]. Shashikala Channalli, Ajay Jadhav [2009] in this day and age the craft of sending and showing the shrouded data particularly out in the open spots, has gotten more consideration and confronted numerous difficulties.…”

Asymptotically Optimum Perfect Universal Steganography of Finite Memoryless Sources

“…, n, where b i ∈ {0, 1} is the message bit embedded in the i-th element of the host. The histogram-preserving methods in [11], [12] and [13] can be seen as using LSB steganography plus some kind of histogram compensation to remediate the lack of histogram preservation in the baseline technique. These beginnings limit their possibilities.…”

“…Using (41) and (42), the figures of merit for the embedding distortion (13) and (14) can be put as a function of ω(x) (1/n)ω(x) = p 2 as follows:…”