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Conceptual design of edge adaptive steganography scheme based on advanced lsb algorithm

Feb 11, 2017



  • International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976

    6464(Print), ISSN 0976 6472(Online), Volume 6, Issue 1, January (2015), pp. 39-48 IAEME







    1Department of Computer Science and Engineering,

    SDM Institute of Technology, Ujire, India,

    2Department of Electronics and Communications Engineering,

    SDM Institute of Technology, Ujire, India,


    This research article outlines the efficient algorithm in which secrete data are embedded in

    edge regions of the image. Here region selection totally depending on size of the secrete message. If

    less information to be embedded, then sharp regions in the image are selected for embedding bits. If

    the size of secrete information is large, then the more edge regions are released to accommodate all

    the secrete bits. This means that edge regions are selected adaptively with the size of the secrete

    message. Our work focuses on inserting the bits we used Least Significant Bit Matching Revisited

    (LSBMR) scheme and consider the relationship between characteristics of the region and size of the

    secrete message. And also this paper proposes to preserve higher visual quality of the stego image.

    Keywords: Steganography, Least Significant Bits (LSB), Edge Embedding, Unobtrusiveness,



    Steganography is an efficient and well known technique for secure data transmission over the

    public networks. The secrete information can be communicated to the other authorized user, by

    embedding secrete messages in cover image and it generates stego image. This stego image is

    transmitted over the public network and authorized user can extract the secrete data from the stego

    image by efficient data extraction algorithm. There are many good algorithms are available for




    ISSN 0976 6464(Print)

    ISSN 0976 6472(Online)

    Volume 6, Issue 1, January (2015), pp. 39-48


    Journal Impact Factor (2015): 7.9817 (Calculated by GISI)


    I A E M E

  • International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976

    6464(Print), ISSN 0976 6472(Online), Volume 6, Issue 1, January (2015), pp. 39-48 IAEME


    Steganography is the art and science of writing hidden messages in such a way that no one,

    apart from the sender and intended recipient, suspects the existence of the message. In many new

    applications for military and civilian purpose, the contributions of steganography are immense. The

    word steganography is of Greek origin and means "concealed writing" from the Greek words

    steganos meaning "covered or protected", and graphei meaning writing". The first recorded use of

    the term was in 1499 by Johannes rithemius in his Steganographia, a treatise on cryptography and

    steganography disguised as a book on magic. As people become aware of the internet day-by-day,

    the number of users in the network increases considerably thereby, facing more challenges in terms

    of data storage and transmission over the internet, for example information like account number,

    password etc. Hence, in order to provide a better security mechanism, we propose a data hiding

    technique called steganography along with the technique of encryption-decryption.

    Steganography is the art and science of hiding data into different carrier files such as text, audio,

    images, video, etc. In cryptography, the secret message that we send may be easily detectable by the

    attacker. But in steganography, the secret message is not easily detectable. The persons other than

    the sender and receiver are not able to view the secret message.

    1.1 Characteristics of Steganography

    The steganography should have the following characteristics to function efficiently.

    1.1.1Unobtrusiveness - The steganography should be properly invisible or inaudible, or its presence

    should not interfere with the media content being protected.

    1.1.2 Robustness The covered data should not be accessed or removed by any other user except

    the authorized user. If only a partial knowledge is available, then attempts to remove or destroy a

    hidden data should result in severe degradation of the host data before the hidden data is lost. In

    particular, the steganography should be robust in the following areas:

    1.1.3 Unambiguity - Retrieval of the hidden data should unambiguously identify the owner. Furthermore, the accuracy of owner identification should degrade gracefully in the face of attack.

    1.1.4 Security- The security of steganography techniques can be interpreted in the same way as the security of encryption techniques Kerchoffs assumption state that one should assume that the

    method used to encrypt the data is known to an unauthorized party and that security must lie in the

    choice of a key.

    The applications of steganography spread over many areas. Some of the applications are

    point to point convert communication to convey secrete information between trusted parties with

    host media as camouflage, modern printers, military applications, education, posting secrete

    communications on the web to avoid transmission, embedding corrective audio or image data in case

    corrosion occurs from a poor connection or transmission. Basic idea of steganography is to hide the

    secrete data in master file (carrier file) and communicated to the other user over the networks. Master

    files can be of images, audios, text, video file. Most cases images are used as covered media. In

    digital steganography, electronic communications may include steganographic coding inside of a

    transport layer, such as a document file, image file, program or protocol. Media files are ideal for

    steganographic transmission because of their large size. As a simple example, a sender might start

    with an innocuous image file and adjust the color of every 100th pixel to correspond to a letter in the

    alphabet, a change so subtle that someone not specifically looking for it is unlikely to notice

    it.During transmitting the hidden message in covered media over the public network can be detected

    by using the method called steganalysis.


    Lots of research work is done on steganography and some of the work mentioned here. Many

    of the applications like copy right protection, content annotation, access control and transaction

  • International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976

    6464(Print), ISSN 0976 6472(Online), Volume 6, Issue 1, January (2015), pp. 39-48 IAEME


    tracking, the secrete information can be hidden into compressed video bit stream. For instance, [1]

    used data hiding techniques to assess the quality of compressed video in the absence of the original

    reference. The authors of [2] used data hiding to enable real time scene change detection in

    compressed video.

    Least Significant Bit (LSB) replacement algorithm is one of the popular and age old

    algorithm. In this data hiding scheme, the LSB of master image or covered image is overwritten by

    the bit stream of the secrete message according to the pseudorandom number generator (PRNG) . As

    a result there is a possibility of introducing some structural changes and for unauthorized users over

    public networks become easy to detect the hidden secrete information even though the low

    embedding rate by using some of data hiding algorithms such as Chi-squared attack [3],

    regular/singular groups (RS) analysis [4], sample pair analysis [5], and the general framework for

    structural steganalysis [6], [7]. Most of the LSB replacement algorithms introduces structural

    changes. To avoid this up to maximum extent LSB matching (LSBM) technique can be employed. In

    LSBM if the secrete bit does not match the LSB of the master image, then +1 or -1 is added

    randomly to the corresponding pixel value. Till now several data hiding algorithm [8]-[11] are

    proposed to analyze LSBM scheme.

    In [8], the author introduced detector using centre of mass (COM) of the histogram

    characteristic function (HCF). In [9], the author proved that on a gray scale image, HCF COM does

    not work well, so introduced two ways of applying HCF COM method. Namely utilizing the down

    sample image and adjacent histogram instead of traditional histogram. In a recent work [11], Li et al.

    proposed to calculate calibration-based detectors, such as Calibrated HCF COM, on the difference

    image. It proves that Kers approach [9] outperformed by new detector and acceptable accuracy at an

    embedding rate 50% is achieved. The paper [12] presents an improved data hiding technique based

    on BCH (n,k,t) coding. Wang and Moulin [13] have shown that perfect steganography is possible

    with zero risk of detection as long as the embedder has perfect knowledge of the cover distribution.

    Research papers , Hamming code [14], [15], simplex code [16], binary BCH code [17], Reed

    Solomon code [18], and syndrome-trellis code [19] have been used for se

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