Design and Implementation of Visual Cryptography System for Transmission of Secure Data

In recent period of time security of the transmitted data is most critical problem, as network technology is greatly advanced and heaps of information is transmitted via net. Visual cryptography strategy is one of the most secure technique for privacy auspices, that allow the encryption of secret image or data by transferring it into the secure percentage and such a strategy is able to recover the secret image or data. This behavior makes visual cryptography especially useful for the low computation load requirement. In this paper, we are providing the information regarding information security by using Visual Cryptography scheme by making use of exclusive new technique of splitting of images along with their pixels rotation with the help of generated random number. We also have made an attempt to overcome some of the disadvantages of preexisting techniques of encryption and decryption. Finally, successful transmission of the message from transmitting end to receiving end without any interception was done. Most importantly, it is very difficult to hack by use of any professional hacking techniques as the message is encrypted twice. Hence the data is highly secured under transmission pat

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Defining, Measuring, and Enabling Transparency for Electronic Medical Systems

Transparency is a novel concept in the context of Information and Communication Technology (ICT). It has arisen from regulations as a data protection principle, and it is now being studied to encompass the peculiarities of digital information. Transparency, however, is not the first security concept to be borrowed from regulations; privacy once emerged from discussions on individual’s rights. Privacy began to be vigorously debated in 1890, when Warren and Brandeis analysed legal cases for which penalties were applied on the basis of defamation, infringement of copyrights, and violation of confidence. The authors defended that those cases were, in fact, built upon a broader principle called privacy. But privacy was only given a structured definition almost one century later, in 1960, when Prosser examined cases produced after Warren and Brandeis’ work, classifying violation of privacy into four different torts; it took twenty years more before the concept was thoroughly studied for its functions in ICT. Guidelines by the OECD outlined principles to support the discussion of privacy as a technical requirement. Proceeded by international standards for a privacy framework (ISO/IEC 29100), which translated the former legal concepts into information security terms, such as data minimisation, accuracy, and accountability. Transparency has a younger, but comparable history; the current General Data Protection Regulation (GDPR) defines it as a principle which requires “that any information and communication relating to the processing of those personal data be easily accessible and easy to understand [..]". However, other related and more abstract concepts preceded it. In the Health Insurance Portability and Accountability Act (HIPAA) of 1996, the Privacy Rule demands to document privacy policies and procedures and to notify individuals of uses of their health information. Former European Directives, i.e., 95/46/EC and 2011/24/EU, establish “the right for individuals to have access to their personal data concerning their health [..] also in the context of cross-border healthcare”. The same did the Freedom of Information Act (FOIA) of 1966, instituting that any person has a right to obtain from agencies information regarding their records. These and other similar requests refer to the transversal quality called transparency. Similarly to what happened with privacy, transparency was also the subject of guidelines that clarify its interpretation in ICT. However, no framework or standard has been defined yet that translates transparency into a technical property. This translation is the goal of our work. This thesis is dedicated to debate existing interpretations for transparency, to establish requirements and measurement procedures for it, and to study solutions that can help systems adhere to the transparency principle from a technical perspective. Our work constitutes an initial step towards the definition of a framework that helps accomplish meaningful transparency in the context of Electronic Medical Systems

Harnessing Simulated Data with Graphs

Physically accurate simulations allow for unlimited exploration of arbitrarily crafted environments. From a scientific perspective, digital representations of the real world are useful because they make it easy validate ideas. Virtual sandboxes allow observations to be collected at-will, without intricate setting up for measurements or needing to wait on the manufacturing, shipping, and assembly of physical resources. Simulation techniques can also be utilized over and over again to test the problem without expending costly materials or producing any waste. Remarkably, this freedom to both experiment and generate data becomes even more powerful when considering the rising adoption of data-driven techniques across engineering disciplines. These are systems that aggregate over available samples to model behavior, and thus are better informed when exposed to more data. Naturally, the ability to synthesize limitless data promises to make approaches that benefit from datasets all the more robust and desirable. However, the ability to readily and endlessly produce synthetic examples also introduces several new challenges. Data must be collected in an adaptive format that can capture the complete diversity of states achievable in arbitrary simulated configurations while too remaining amenable to downstream applications. The quantity and zoology of observations must also straddle a range which prevents overfitting but is descriptive enough to produce a robust approach. Pipelines that naively measure virtual scenarios can easily be overwhelmed by trying to sample an infinite set of available configurations. Variations observed across multiple dimensions can quickly lead to a daunting expansion of states, all of which must be processed and solved. These and several other concerns must first be addressed in order to safely leverage the potential of boundless simulated data. In response to these challenges, this thesis proposes to wield graphs in order to instill structure over digitally captured data, and curb the growth of variables. The paradigm of pairing data with graphs introduced in this dissertation serves to enforce consistency, localize operators, and crucially factor out any combinatorial explosion of states. Results demonstrate the effectiveness of this methodology in three distinct areas, each individually offering unique challenges and practical constraints, and together showcasing the generality of the approach. Namely, studies observing state-of-the-art contributions in design for additive manufacturing, side-channel security threats, and large-scale physics based contact simulations are collectively achieved by harnessing simulated datasets with graph algorithms

Central Washington University 2018-2019 Undergraduate Catalog

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