3,064 research outputs found

    A novel quality assessment for visual secret sharing schemes

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    To evaluate the visual quality in visual secret sharing schemes, most of the existing metrics fail to generate fair and uniform quality scores for tested reconstructed images. We propose a new approach to measure the visual quality of the reconstructed image for visual secret sharing schemes. We developed an object detection method in the context of secret sharing, detecting outstanding local features and global object contour. The quality metric is constructed based on the object detection-weight map. The effectiveness of the proposed quality metric is demonstrated by a series of experiments. The experimental results show that our quality metric based on secret object detection outperforms existing metrics. Furthermore, it is straightforward to implement and can be applied to various applications such as performing the security test of the visual secret sharing process

    Visual secret sharing and related Works -A Review

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    The accelerated development of network technology and internet applications has increased the significance of protecting digital data and images from unauthorized access and manipulation. The secret image-sharing network (SIS) is a crucial technique used to protect private digital photos from illegal editing and copying. SIS can be classified into two types: single-secret sharing (SSS) and multi-secret sharing (MSS). In SSS, a single secret image is divided into multiple shares, while in MSS, multiple secret images are divided into multiple shares. Both SSS and MSS ensure that the original secret images cannot be reconstructed without the correct combination of shares. Therefore, several secret image-sharing methods have been developed depending on these two methods for example visual cryptography, steganography, discrete wavelet transform, watermarking, and threshold. All of these techniques are capable of randomly dividing the secret image into a large number of shares, each of which cannot provide any information to the intrusion team.  This study examined various visual secret-sharing schemes as unique examples of participant secret-sharing methods. Several structures that generalize and enhance VSS were also discussed in this study on covert image-sharing protocols and also this research also gives a comparative analysis of several methods based on various attributes in order to better concentrate on the future directions of the secret image. Generally speaking, the image quality generated employing developed methodologies is preferable to the image quality achieved through using the traditional visual secret-sharing methodology

    Risks and potentials of graphical and gesture-based authentication for touchscreen mobile devices

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    While a few years ago, mobile phones were mainly used for making phone calls and texting short messages, the functionality of mobile devices has massively grown. We are surfing the web, sending emails and we are checking our bank accounts on the go. As a consequence, these internet-enabled devices store a lot of potentially sensitive data and require enhanced protection. We argue that authentication often represents the only countermeasure to protect mobile devices from unwanted access. Knowledge-based concepts (e.g., PIN) are the most used authentication schemes on mobile devices. They serve as the main protection barrier for many users and represent the fallback solution whenever alternative mechanisms fail (e.g., fingerprint recognition). This thesis focuses on the risks and potentials of gesture-based authentication concepts that particularly exploit the touch feature of mobile devices. The contribution of our work is threefold. Firstly, the problem space of mobile authentication is explored. Secondly, the design space is systematically evaluated utilizing interactive prototypes. Finally, we provide generalized insights into the impact of specific design factors and present recommendations for the design and the evaluation of graphical gesture-based authentication mechanisms. The problem space exploration is based on four research projects that reveal important real-world issues of gesture-based authentication on mobile devices. The first part focuses on authentication behavior in the wild and shows that the mobile context makes great demands on the usability of authentication concepts. The second part explores usability features of established concepts and indicates that gesture-based approaches have several benefits in the mobile context. The third part focuses on observability and presents a prediction model for the vulnerability of a given grid-based gesture. Finally, the fourth part investigates the predictability of user-selected gesture-based secrets. The design space exploration is based on a design-oriented research approach and presents several practical solutions to existing real-world problems. The novel authentication mechanisms are implemented into working prototypes and evaluated in the lab and the field. In the first part, we discuss smudge attacks and present alternative authentication concepts that are significantly more secure against such attacks. The second part focuses on observation attacks. We illustrate how relative touch gestures can support eyes-free authentication and how they can be utilized to make traditional PIN-entry secure against observation attacks. The third part addresses the problem of predictable gesture choice and presents two concepts which nudge users to select a more diverse set of gestures. Finally, the results of the basic research and the design-oriented applied research are combined to discuss the interconnection of design space and problem space. We contribute by outlining crucial requirements for mobile authentication mechanisms and present empirically proven objectives for future designs. In addition, we illustrate a systematic goal-oriented development process and provide recommendations for the evaluation of authentication on mobile devices.WĂ€hrend Mobiltelefone vor einigen Jahren noch fast ausschließlich zum Telefonieren und zum SMS schreiben genutzt wurden, sind die Anwendungsmöglichkeiten von MobilgerĂ€ten in den letzten Jahren erheblich gewachsen. Wir surfen unterwegs im Netz, senden E-Mails und ĂŒberprĂŒfen Bankkonten. In der Folge speichern moderne internetfĂ€higen MobilgerĂ€te eine Vielfalt potenziell sensibler Daten und erfordern einen erhöhten Schutz. In diesem Zusammenhang stellen Authentifizierungsmethoden hĂ€ufig die einzige Möglichkeit dar, um MobilgerĂ€te vor ungewolltem Zugriff zu schĂŒtzen. Wissensbasierte Konzepte (bspw. PIN) sind die meistgenutzten Authentifizierungssysteme auf MobilgerĂ€ten. Sie stellen fĂŒr viele Nutzer den einzigen Schutzmechanismus dar und dienen als Ersatzlösung, wenn alternative Systeme (bspw. Fingerabdruckerkennung) versagen. Diese Dissertation befasst sich mit den Risiken und Potenzialen gestenbasierter Konzepte, welche insbesondere die Touch-Funktion moderner MobilgerĂ€te ausschöpfen. Der wissenschaftliche Beitrag dieser Arbeit ist vielschichtig. Zum einen wird der Problemraum mobiler Authentifizierung erforscht. Zum anderen wird der Gestaltungsraum anhand interaktiver Prototypen systematisch evaluiert. Schließlich stellen wir generelle Einsichten bezĂŒglich des Einflusses bestimmter Gestaltungsaspekte dar und geben Empfehlungen fĂŒr die Gestaltung und Bewertung grafischer gestenbasierter Authentifizierungsmechanismen. Die Untersuchung des Problemraums basiert auf vier Forschungsprojekten, welche praktische Probleme gestenbasierter Authentifizierung offenbaren. Der erste Teil befasst sich mit dem Authentifizierungsverhalten im Alltag und zeigt, dass der mobile Kontext hohe AnsprĂŒche an die Benutzerfreundlichkeit eines Authentifizierungssystems stellt. Der zweite Teil beschĂ€ftigt sich mit der Benutzerfreundlichkeit etablierter Methoden und deutet darauf hin, dass gestenbasierte Konzepte vor allem im mobilen Bereich besondere VorzĂŒge bieten. Im dritten Teil untersuchen wir die Beobachtbarkeit gestenbasierter Eingabe und prĂ€sentieren ein Vorhersagemodell, welches die Angreifbarkeit einer gegebenen rasterbasierten Geste abschĂ€tzt. Schließlich beschĂ€ftigen wir uns mit der Erratbarkeit nutzerselektierter Gesten. Die Untersuchung des Gestaltungsraums basiert auf einem gestaltungsorientierten Forschungsansatz, welcher zu mehreren praxisgerechte Lösungen fĂŒhrt. Die neuartigen Authentifizierungskonzepte werden als interaktive Prototypen umgesetzt und in Labor- und Feldversuchen evaluiert. Im ersten Teil diskutieren wir Fettfingerattacken ("smudge attacks") und prĂ€sentieren alternative Authentifizierungskonzepte, welche effektiv vor diesen Angriffen schĂŒtzen. Der zweite Teil beschĂ€ftigt sich mit Angriffen durch Beobachtung und verdeutlicht wie relative Gesten dazu genutzt werden können, um blickfreie Authentifizierung zu gewĂ€hrleisten oder um PIN-Eingaben vor Beobachtung zu schĂŒtzen. Der dritte Teil beschĂ€ftigt sich mit dem Problem der vorhersehbaren Gestenwahl und prĂ€sentiert zwei Konzepte, welche Nutzer dazu bringen verschiedenartige Gesten zu wĂ€hlen. Die Ergebnisse der Grundlagenforschung und der gestaltungsorientierten angewandten Forschung werden schließlich verknĂŒpft, um die Verzahnung von Gestaltungsraum und Problemraum zu diskutieren. Wir prĂ€sentieren wichtige Anforderungen fĂŒr mobile Authentifizierungsmechanismen und erlĂ€utern empirisch nachgewiesene Zielvorgaben fĂŒr zukĂŒnftige Konzepte. ZusĂ€tzlich zeigen wir einen zielgerichteten Entwicklungsprozess auf, welcher bei der Entwicklung neuartiger Konzepte helfen wird und geben Empfehlungen fĂŒr die Evaluation mobiler Authentifizierungsmethoden

    Spread spectrum-based video watermarking algorithms for copyright protection

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    Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

    Information security and assurance : Proceedings international conference, ISA 2012, Shanghai China, April 2012

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    The Pedagogics of Play

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    Teachers should emphasize the importance of play to a student\u27s development, noting their individual talents they need to explore, tryout, take apart and investigate which is fundamental to learning. Design fundamental programs should develop pedagogies that guide student\u27s play into progressive learning experiences in the essentials of form, mathematics, geometry, and creativity

    Towards Scalable, Private and Practical Deep Learning

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    Deep Learning (DL) models have drastically improved the performance of Artificial Intelligence (AI) tasks such as image recognition, word prediction, translation, among many others, on which traditional Machine Learning (ML) models fall short. However, DL models are costly to design, train, and deploy due to their computing and memory demands. Designing DL models usually requires extensive expertise and significant manual tuning efforts. Even with the latest accelerators such as Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU), training DL models can take prohibitively long time, therefore training large DL models in a distributed manner is a norm. Massive amount of data is made available thanks to the prevalence of mobile and internet-of-things (IoT) devices. However, regulations such as HIPAA and GDPR limit the access and transmission of personal data to protect security and privacy. Therefore, enabling DL model training in a decentralized but private fashion is urgent and critical. Deploying trained DL models in a real world environment usually requires meeting Quality of Service (QoS) standards, which makes adaptability of DL models an important yet challenging matter.  In this dissertation, we aim to address the above challenges to make a step towards scalable, private, and practical deep learning. To simplify DL model design, we propose Efficient Progressive Neural-Architecture Search (EPNAS) and FedCust to automatically design model architectures and tune hyperparameters, respectively. To provide efficient and robust distributed training while preserving privacy, we design LEASGD, TiFL, and HDFL. We further conduct a study on the security aspect of distributed learning by focusing on how data heterogeneity affects backdoor attacks and how to mitigate such threats. Finally, we use super resolution (SR) as an example application to explore model adaptability for cross platform deployment and dynamic runtime environment. Specifically, we propose DySR and AdaSR frameworks which enable SR models to meet QoS by dynamically adapting to available resources instantly and seamlessly without excessive memory overheads
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