A Review of Image Steganography Techniques

اخفاء الصور هو أحد تقنيات تأمين البيانات كصورة غلاف. من ناحية أخرى ، نظرًا لأن الاتصالات السرية وتطوير محتويات الوسائط المتعددة ، يعكس الاختزال للتقنيات أدوارًا مهمة. تعد جودة صورة الغلاف  "stego "وقدرة صورة الغلاف جانبًا مهمًا في نظامstegnography ، ويعتمد تقييم الأداء ومقارنة التقنيات على هذه المعلمات في نظام إخفاء المعلومات. هناك تقنيات تضمين موجودة تهدف إلى حماية المعلومات ، ومعدل تضمين البت الأعلى يمثل تحديًا مهمًا في تصميم نظام إخفاء المعلومات. تسلط هذه الورقة الضوء على مراجعة الأدبيات لنهج المجال المكاني للتصنيف (الاعتماد على قيمة البكسل) لإخفاء الصور ؛ و شمل ، (1) إخفاء العلومات باستخدام طريقة  LSB ، (2) إخفاء المعلومات باستخدام طريقة PVD ، (3) إخفاء المعلومات باستخدام طريقة GLM ، (4) إخفاء المعلومات باستخدام طريقة PPM الهدف من هذه الورقة هو توفير ملخص شامل للأعمال الموجودة من حيث الهدف ، وتسليط الضوء على نقاط القوة والضعف في التقنيات الحالية.Image steganography is one in  techniques of securing data as a cover image. In the other hand, since secret communications and development of multimedia contents, stenography of the techniques  reflect important roles. In based are reflected stegnography system, the quality of stego image and the capacity of the cover image are important side of the image, evaluate performance and comparison of  techniques are depending on these parameters in steganography system. There are existing embedding techniques that aim to protect information, and a higher bit embedding rate is an important challenge in designing a steganographic system.  This paper highlights a literature review of the classification spatial domain (beads on pixel value) approach  of image steganography; include, (i) LSB steganography, (ii) PVD based steganography, (iii)GLM based steganography, (iv) PPM based steganography. The goal of this paper is to supply a comprehensive summary of  existing works in terms of ideals, and to highlight the strong and weak points of current  techniques

An Effective Data Embedding Technique Based on APPM in Transform Domain

This paper proposes an efficient data embedding technique based on adaptive pixel pair matching in transform domain. The basic principle of a Pixel Pair Matching (PPM) based data embedding technique is to use the values of a pixel pair as a reference coordinate and search a coordinate in the neighborhood set of that pixel pair according to given message digit. In order to conceal secret data the pixel pair is then replaced by the searched coordinate. In transform domain data embedding techniques, the image pixels are converted into transform domain by using a particular transform and then the secret data is embedded by using an efficient data embedding algorithm. In this paper the Haar transform is used. The proposed method not only offers lower embedding distortion but also more robust against various noise attacks. The experimental results shows that this method performs better when compared to the spatial domain technique

Effective Data Hiding Method Through Pixel Pair Matching

This work proposes a new data-hiding method based on pixel pair matching , which is to use the values of pixel pair as a reference coordinate, and find a coordinate in the neighborhood set of this pixel pair based on the given message. Further the pixel pair is replaced by the searched coordinate to cover the digit. Two methods has been proposed to overcome this problem one is Exploiting modification direction (EMD) and another is diamond encoding (DE). The proposed methods offer lower distortion as compared to the existing methods by providing more compact neighborhood sets and allowing embedded digits in any notational system

A Brief Review of RIDH

The Reversible image data hiding (RIDH) is one of the novel approaches in the security field. In the highly sensitive domains like Medical, Military, Research labs, it is important to recover the cover image successfully, Hence, without applying the normal steganography, we can use RIDH to get the better result. Reversible data hiding has a advantage over image data hiding that it can give you double security surely

Reversible difference expansion multi-layer data hiding technique for medical images

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads

Paperless Transfer of Medical Images: Storing Patient Data in Medical Images

Medical images have become an integral part ofpatient diagnosis in recent years. With the introduction of HealthInformation Management Systems (HIMS) used for the storageand sharing of patient data, as well as the use of the PictureArchiving and Communication Systems (PACS) formanipulating and storage of CT Scans, X-rays, MRIs and othermedical images, the security of patient data has become a seriousconcern for medical professionals. The secure transfer of theseimages along with patient data is necessary for maintainingconfidentiality as required by the Data Protection Act, 2011 inTrinidad and Tobago and similar legislation worldwide. Tofacilitate this secure transfer, different digital watermarking andsteganography techniques have been proposed to safely hideinformation in these digital images. This paper focuses on theamount of data that can be embedded into typical medical imageswithout compromising visual quality. In addition, ExploitingModification Direction (EMD) is selected as the method of choicefor hiding information in medical images and it is compared tothe commonly used Least Significant Bit (LSB) method.Preliminary results show that by using EMD there little to nodistortion even at the highest embedding capacity

An Efficient Light-weight LSB steganography with Deep learning Steganalysis

Active research is going on to securely transmit a secret message or so-called steganography by using data-hiding techniques in digital images. After assessing the state-of-the-art research work, we found, most of the existing solutions are not promising and are ineffective against machine learning-based steganalysis. In this paper, a lightweight steganography scheme is presented through graphical key embedding and obfuscation of data through encryption. By keeping a mindset of industrial applicability, to show the effectiveness of the proposed scheme, we emphasized mainly deep learning-based steganalysis. The proposed steganography algorithm containing two schemes withstands not only statistical pattern recognizers but also machine learning steganalysis through feature extraction using a well-known pre-trained deep learning network Xception. We provided a detailed protocol of the algorithm for different scenarios and implementation details. Furthermore, different performance metrics are also evaluated with statistical and machine learning performance analysis. The results were quite impressive with respect to the state of the arts. We received 2.55% accuracy through statistical steganalysis and machine learning steganalysis gave maximum of 49.93~50% correctly classified instances in good condition.Comment: Accepted pape

Introducing a New Evaluation Criteria for EMD-Base Steganography Method

Steganography is a technique to hide the presence of secret communication. When one of the communication elements is under the influence of the enemy, it can be used. The main measure to evaluate steganography methods in a certain capacity is security. Therefore, in a certain capacity, reducing the amount of changes in the cover media, creates a higher embedding efficiency and thus more security of an steganography method. Mostly, security and capacity are in conflict with each other, the increase of one lead to the decrease of the other. The presence of a single criterion that represents security and capacity at the same time be useful in comparing steganography methods. EMD and the relevant methods are a group of steganography techniques, which optimize the amount of changes resulting from embedding (security). The present paper is aimed to provide an evaluation criterion for this group of steganography methods. In this study, after a general review and comparison of EMD-based steganography techniques, we present a method to compare them exactly, from the perspective of embedding efficiency. First, a formula is presented to determine the value of embedding efficiency, which indicates the effect of one or more changes on one or more pixels. The results demonstrate that the proposed embedding efficiency formula shows the performance of the methods better when several changes are made on a pixel compared to the existing criteria. In the second step, we have obtained an upper bound, which determines the best efficiency for each certain capacity. Finally, based on the introduced bound, another evaluation criterion for a better comparison of the methods is presented

Dual-image-based reversible data hiding scheme with integrity verification using exploiting modification direction

Abstract(#br)In this paper, a novel dual-image-based reversible data hiding scheme using exploiting modification direction (EMD) is proposed. This scheme embeds two 5-base secret digits into each pixel pair of the cover image simultaneously according to the EMD matrix to generate two stego-pixel pairs. By shifting these stego-pixel pairs to the appropriate locations in some cases, two meaningful shadows are produced. The secret data can be extracted accurately, and the cover image can be reconstructed completely in the data extraction and the image reconstruction procedure, respectively. Experimental results show that our scheme outperforms the comparative methods in terms of image quality and embedding ratio. Pixel-value differencing (PVD) histogram analysis reveals that our scheme..