302 research outputs found

    Vector-based Efficient Data Hiding in Encrypted Images via Multi-MSB Replacement

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    As an essential technique for data privacy protection, reversible data hiding in encrypted images (RDHEI) methods have drawn intensive research interest in recent years. In response to the increasing demand for protecting data privacy, novel methods that perform RDHEI are continually being developed. We propose two effective multi-MSB (most significant bit) replacement-based approaches that yield comparably high data embedding capacity, improve overall processing speed, and enhance reconstructed images' quality. Our first method, Efficient Multi-MSB Replacement-RDHEI (EMR-RDHEI), obtains higher data embedding rates (DERs, also known as payloads) and better visual quality in reconstructed images when compared with many other state-of-the-art methods. Our second method, Lossless Multi-MSB Replacement-RDHEI (LMR-RDHEI), can losslessly recover original images after an information embedding process is performed. To verify the accuracy of our methods, we compared them with other recent RDHEI techniques and performed extensive experiments using the widely accepted BOWS-2 dataset. Our experimental results showed that the DER of our EMR-RDHEI method ranged from 1.2087 bit per pixel (bpp) to 6.2682 bpp with an average of 3.2457 bpp. For the LMR-RDHEI method, the average DER was 2.5325 bpp, with a range between 0.2129 bpp and 6.0168 bpp. Our results demonstrate that these methods outperform many other state-of-the-art RDHEI algorithms. Additionally, the multi-MSB replacement-based approach provides a clean design and efficient vectorized implementation.Comment: 14 pages; journa

    Privacy-preserving information hiding and its applications

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    The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality

    Data Security using Reversible Data Hiding with Optimal Value Transfer

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    In this paper a novel reversible data hiding algorithm is used which can recover image without any distortion. This algorithm uses zero or minimum points of an image and modifies the pixel. It is proved experimentally that the peak signal to noise ratio of the marked image generated by this method and the original image is guaranteed to be above 48 dB this lower bound of peak signal to noise ratio is much higher than all reversible data hiding technique present in the literature. Execution time of proposed system is short. The algorithm has been successfully applied to all types of images

    Privacy-aware reversible watermarking in cloud computing environments

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    As an interdisciplinary research between watermarking and cryptography, privacy-aware reversible watermarking permits a party to entrust the task of embedding watermarks to a cloud service provider without compromising information privacy. The early development of schemes were primarily based upon traditional symmetric-key cryptosystems, which involve an extra implementation cost of key exchange. Although recent research attentions were drawn to schemes compatible with asymmetric-key cryptosystems, there were notable limitations in the practical aspects. In particular, the host signal must either be enciphered in a redundant way or be pre-processed prior to encryption, which would largely limit the storage efficiency and scheme universality. To relax the restrictions, we propose a novel research paradigm and devise different schemes compatible with different homomorphic cryptosystems. In the proposed schemes, the encoding function is recognised as an operation of adding noise, whereas the decoding function is perceived as a corresponding denoising process. Both online and offline contentadaptive predictors are developed to assist watermark decoding for various operational requirements. A three-way trade-off between the capacity, fidelity and reversibility is analysed mathematically and empirically. It is shown that the proposed schemes achieve the state-the-art performance

    Zero watermarking scheme for privacy protection in e-Health care

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    E-health care is an emerging field where health services and information are delivered and offered over the Internet. So the health information of the patients communicated over the Internet has to protect the privacy of the patients. The patient information is embedded into the health record and communicated online which also induces degradation to the original information. So, in this article, a zero watermarking scheme for privacy protection is proposed which protects the privacy and also eliminates the degradation done during embedding of patient information into the health record. This method is based on simple linear iterative clustering (SLIC) superpixels and partial pivoting lower triangular upper triangular (PPLU) factorization. The novelty of this article is that the use of SLIC superpixels and PPLU decomposition for the privacy protection of medical images (MI). The original image is subjected to SLIC segmentation and non-overlapping high entropy blocks are selected. On the selected blocks discrete wavelet transform (DWT) is applied and those blocks undergo PPLU factorization to get three matrices, L, U and P, which are lower triangular, upper triangular and permutation matrix respectively. The product matrix L×U is used to construct a zero-watermark. The technique has been experimented on the UCID, BOWS and SIPI databases. The test results demonstrate that this work shows high robustness which is measured using normalized correlation (NC) and bit error rate (BER) against the listed attacks

    WAVELET BASED DATA HIDING OF DEM IN THE CONTEXT OF REALTIME 3D VISUALIZATION (Visualisation 3D Temps-Réel à Distance de MNT par Insertion de Données Cachées Basée Ondelettes)

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    The use of aerial photographs, satellite images, scanned maps and digital elevation models necessitates the setting up of strategies for the storage and visualization of these data. In order to obtain a three dimensional visualization it is necessary to drape the images, called textures, onto the terrain geometry, called Digital Elevation Model (DEM). Practically, all these information are stored in three different files: DEM, texture and position/projection of the data in a geo-referential system. In this paper we propose to stock all these information in a single file for the purpose of synchronization. For this we have developed a wavelet-based embedding method for hiding the data in a colored image. The texture images containing hidden DEM data can then be sent from the server to a client in order to effect 3D visualization of terrains. The embedding method is integrable with the JPEG2000 coder to accommodate compression and multi-resolution visualization. Résumé L'utilisation de photographies aériennes, d'images satellites, de cartes scannées et de modèles numériques de terrains amène à mettre en place des stratégies de stockage et de visualisation de ces données. Afin d'obtenir une visualisation en trois dimensions, il est nécessaire de lier ces images appelées textures avec la géométrie du terrain nommée Modèle Numérique de Terrain (MNT). Ces informations sont en pratiques stockées dans trois fichiers différents : MNT, texture, position et projection des données dans un système géo-référencé. Dans cet article, nous proposons de stocker toutes ces informations dans un seul fichier afin de les synchroniser. Nous avons développé pour cela une méthode d'insertion de données cachées basée ondelettes dans une image couleur. Les images de texture contenant les données MNT cachées peuvent ensuite être envoyées du serveur au client afin d'effectuer une visualisation 3D de terrains. Afin de combiner une visualisation en multirésolution et une compression, l'insertion des données cachées est intégrable dans le codeur JPEG 2000

    Information Hiding Based on DNA Sequences

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    يعد أمن المعلومات مصدر قلق رئيسي، خاصة في ضوء التوسع السريع في استخدام الإنترنت في السنوات الأخيرة. نتيجة لهذا التوسع، كانت هناك حالات وصول غير قانوني، والتي تم تخفيفها من خلال اعتماد مجموعة متنوعة من بروتوكولات الاتصال الآمن، بما في ذلك التشفير وإخفاء البيانات. في السنوات الأخيرة، كانت هناك زيادة في استخدام الحمض النووي للتشفير وإخفاء البيانات كناقل، مع الاستفادة من قدراته الجزيئية الحيوية. في إخفاء البيانات. نتيجة لذلك، في نهج إخفاء البيانات، يتم استخدام قواعد الحمض النووي كناقل للمعلومات لتعزيز الأمن. يندمج علم إخفاء المعلومات والتشفير المستند إلى الحمض النووي بين السمات البيولوجية والتقنيات التقليدية من أجل تحقيق خوارزمية مؤمنة جيدًا تستغلها. لذلك، توفر تسلسلات الحمض النووي قدرة عالية على البيانات بما في ذلك الحفاظ على الخصائص الكيميائية والبيولوجية لتسلسل الحمض النووي.Information security is a major source of worry, especially in light of the rapid expansion of internet use in recent years. As a result of this expansion, there have been incidences of illegal access, which have been mitigated by the adoption of a variety of secure communication protocols, including encryption and data concealment. DNA's bio-molecular properties have seen an uptick in popularity as a carrier for cryptography and data hiding in recent years. when information needs to be hidden. Therefore, DNA bases are utilized as information carriers in the data concealing strategy to increase safety. DNA-based steganography and cryptography combine a biological property with conventional methods to provide an algorithm with increased security. Because of their ability to maintain their chemical and biological characteristics, DNA sequences also have a high data capacity

    A review and open issues of multifarious image steganography techniques in spatial domain

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    Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method
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