Emerging Applications of Reversible Data Hiding

Reversible data hiding (RDH) is one special type of information hiding, by which the host sequence as well as the embedded data can be both restored from the marked sequence without loss. Beside media annotation and integrity authentication, recently some scholars begin to apply RDH in many other fields innovatively. In this paper, we summarize these emerging applications, including steganography, adversarial example, visual transformation, image processing, and give out the general frameworks to make these operations reversible. As far as we are concerned, this is the first paper to summarize the extended applications of RDH.Comment: ICIGP 201

A Framework to Reversible Data Hiding Using Histogram-Modification

A Novel method of Stegnography to achieve Reversible Data Hiding (RDH) is proposed using Histogram Modification (HM). In this paper the HM technique is revisited and a general framework to construct HM-based RDH is presented by simply designing the shifting and embedding functions on the cover image. The Secret Image is embedded inside the cover image using several steps of specific shifting of pixels with an order. The secret image or logo is retrieved without any loss in data on the cover and as well as in the secrete image. The Experimental results show the better Peak Signal to Noise Ratio (PSNR) with the existing methods

การรวมกันของวิทยาการอำพรางข้อมูลกับวิทยาการเข้ารหัสลับ สำหรับภาพทางการแพทย์

บทคัดย่อ งานวิจัยนี้นำเสนอการรวมกันของสองขั้นตอนวิธีประกอบด้วยการอำพรางข้อมูลแบบที่สามารถกู้คืนกลับได้ (Reversible Data Hiding: RDH) และการเข้ารหัสลับ (Advanced Encryption Standard: AES) เพื่อเพิ่มประสิทธิภาพความปลอดภัยในการเข้าถึงข้อมูล หลายเทคนิคของ RDH ถูกใช้ร่วมกันเพื่อให้ได้รับความบิดเบือนต่ำสุดสำหรับการซ่อนข้อมูล หนึ่งตัวทำนาย Linear Fitting Rhombus Pattern (LFRP) ถูกใช้สำหรับการทำนาย, Local variance ใช้สำหรับการเรียงค่าความผิดพลาดจากการทำนาย, Double Modification Testing (DMT) ใช้เพื่อการตรวจสอบสถานะของพิกเซล และเทคนิค Histogram Shifting ใช้ในการฝัง มากไปกว่านั้น ขั้นตอนวิธี AES ถูกประยุกต์ใช้ร่วมในงานนี้สำหรับการเข้ารหัสลับอีกชั้นหนึ่งสำหรับข้อมูล Header 128 บิต ของขั้นตอนวิธีการเข้ารหัส RDH เพื่อให้แน่ใจสำหรับการป้องกันการเข้าถึงข้อมูลโดยบุคคลที่ไม่ได้รับอนุญาต การทดสอบภาพแบบไบนารีหลายขนาดถูกใช้ฝังลงในภาพทางการแพทย์ซึ่งได้รับมาจากเครื่องมือที่แตกต่างกัน อาทิเช่น Magnetic Resonance Image (MRI) Ultrasound (US) และ X-ray ผลลัพธ์ขั้นตอนวิธีที่นำเสนอแสดงให้เห็นความบิดเบือนของการฝังที่ต่ำ และความปลอดภัยของการเข้าถึงข้อมูลที่สูงขึ้น คำสำคัญ: การอำพรางข้อมูลแบบที่สามารถกู้คืนกลับได้ (RDH) การเข้ารหัสลับ (AES) ABSTRACT This paper presents two algorithms, Reversible Data Hiding (RDH) and Advanced Encryption Standard (AES) to enhance the security of unauthorized data access. Many techniques of RDH can be shared to achieve minimal distortion when hiding information. A Linear Fitting Rhombus Pattern Predictor (LFRPP) was used for prediction, with, local variance to sort prediction error values. Double Modification Testing (DMT) was used to check the status of pixels with Histogram Shifting (HS) employed for data embedding. The AES algorithm was applied for encryption 128 bit RDH encoder algorithm Header to ensure data protection and restrict access by unauthorized persons. Various quantities of binary information embedded into medical imaging and derived from the diverse sources of Magnetic Resonance Image (MRI), Ultrasound (US) and X-ray were tested. Results showed a distortion between embedding low and higher data security.   Keyword: Reversible Data Hiding, Advanced Encryption Standar

REVERSIBLE IMAGE DATA HIDING WITH CONTRAST ENHANCEMENT

Reversible data hiding (RDH) continues to be intensively studied locally of signal processing. To judge the performance of the RDH formula, hiding rate and marked picture quality are essential metrics. There exists a trade-off together because growing the hiding rate frequently causes more distortion in image content. To measure the distortion, the peak signal-to-noise ratio (PSNR) value ofthemarked image is frequently calculated. The greatest two bins within the histogram are selected for data embedding to ensure that histogram equalization could be carried out by repeating the procedure. Alongside it details are to be embedded combined with the message bits into the host image so the original image is totally recoverable. The suggested formula was developed on two teams of images to demonstrate its efficiency. Within this letter, a manuscript reversible data hiding (RDH) algorithmic suggested for digital images. Rather than attempting to keep the PSNR value high, the suggested formula improves the contrast of the image to enhance its visual quality. To the best understanding, it's the first algorithm that accomplishes image contrast enhancement with data hiding. In addition, the evaluation results reveal that the visual quality could be preserved after a great deal of message bits happen to be embedded into the contrast-enhanced images, better still than three specific MATLAB functions employed for image contrast enhancement.

Implementation of Reversible Data Hiding Using Suitable Wavelet Transform For Controlled Contrast Enhancement

Data Hiding is important for secrete communication and it is also essential to keep the data hidden to be received by the intended recipient only. The conventional Reversible Data Hiding (RDH) algorithms pursue high Peak-Signal-to-Noise-Ratio (PSNR) at certain amount of embedding bits. Considering an importance of improvement in image visual quality than keeping high PSNR, a novel RDH scheme utilizing contrast enhancement to replace the PSNR was presented with the help of Integer Wavelet Transform (IWT). In proposed work, the identification of suitable transform from different wavelet families is planned to enhance the security of data by encrypting it and embedding more bits with the original image to generate stego image. The obtained stego image will be transmitted to the other end, where the receiver will extract the transmitted secrete data and original cover image from stego image using required keys. It will use a proper transformation for the purpose of Controlled Contrast Enhancement (CCE) to achieve the intended RDH so that the amount of embedding data bits and visual perception will be enhanced. The difference of the transmitted original image and restored original image is minor, which is almost invisible for human eyes though more bits are embedded with the original image. The performance parameters are also calculated

Design and Analysis of Reversible Data Hiding Using Hybrid Cryptographic and Steganographic approaches for Multiple Images

Data concealing is the process of including some helpful information on images. The majority of sensitive applications, such sending authentication data, benefit from data hiding. Reversible data hiding (RDH), also known as invertible or lossless data hiding in the field of signal processing, has been the subject of a lot of study. A piece of data that may be recovered from an image to disclose the original image is inserted into the image during the RDH process to generate a watermarked image. Lossless data hiding is being investigated as a strong and popular way to protect copyright in many sensitive applications, such as law enforcement, medical diagnostics, and remote sensing. Visible and invisible watermarking are the two types of watermarking algorithms. The watermark must be bold and clearly apparent in order to be visible. To be utilized for invisible watermarking, the watermark must be robust and visibly transparent. Reversible data hiding (RDH) creates a marked signal by encoding a piece of data into the host signal. Once the embedded data has been recovered, the original signal may be accurately retrieved. For photos shot in poor illumination, visual quality is more important than a high PSNR number. The DH method increases the contrast of the host picture while maintaining a high PSNR value. Histogram equalization may also be done concurrently by repeating the embedding process in order to relocate the top two bins in the input image's histogram for data embedding. It's critical to assess the images after data concealment to see how much the contrast has increased. Common picture quality assessments include peak signal to noise ratio (PSNR), relative structural similarity (RSS), relative mean brightness error (RMBE), relative entropy error (REE), relative contrast error (RCE), and global contrast factor (GCF). The main objective of this paper is to investigate the various quantitative metrics for evaluating contrast enhancement. The results show that the visual quality may be preserved by including a sufficient number of message bits in the input photographs