A novel conservative chaos driven dynamic DNA coding for image encryption

In this paper, we propose a novel conservative chaotic standard map-driven dynamic DNA coding (encoding, addition, subtraction and decoding) for the image encryption. The proposed image encryption algorithm is a dynamic DNA coding algorithm i.e., for the encryption of each pixel different rules for encoding, addition/subtraction, decoding etc. are randomly selected based on the pseudorandom sequences generated with the help of the conservative chaotic standard map. We propose a novel way to generate pseudo-random sequences through the conservative chaotic standard map and also test them rigorously through the most stringent test suite of pseudo-randomness, the NIST test suite, before using them in the proposed image encryption algorithm. Our image encryption algorithm incorporates a unique feed-forward and feedback mechanisms to generate and modify the dynamic one-time pixels that are further used for the encryption of each pixel of the plain image, therefore, bringing in the desired sensitivity on plaintext as well as ciphertext. All the controlling pseudorandom sequences used in the algorithm are generated for a different value of the parameter (part of the secret key) with inter-dependency through the iterates of the chaotic map (in the generation process) and therefore possess extreme key sensitivity too. The performance and security analysis has been executed extensively through histogram analysis, correlation analysis, information entropy analysis, DNA sequence-based analysis, perceptual quality analysis, key sensitivity analysis, plaintext sensitivity analysis, etc., The results are promising and prove the robustness of the algorithm against various common cryptanalytic attacks.Comment: 29 pages, 5 figures, 15 table

Analysis and review of the possibility of using the generative model as a compression technique in DNA data storage: review and future research agenda

The amount of data in this world is getting higher, and overwriting technology also has severe challenges. Data growth is expected to grow to 175 ZB by 2025. Data storage technology in DNA is an alternative technology with potential in information storage, mainly digital data. One of the stages of storing information on DNA is synthesis. This synthesis process costs very high, so it is necessary to integrate compression techniques for digital data to minimize the costs incurred. One of the models used in compression techniques is the generative model. This paper aims to see if compression using this generative model allows it to be integrated into data storage methods on DNA. To this end, we have conducted a Systematic Literature Review using the PRISMA method in selecting papers. We took the source of the papers from four leading databases and other additional databases. Out of 2440 papers, we finally decided on 34 primary papers for detailed analysis. This systematic literature review (SLR) presents and categorizes based on research questions, namely discussing machine learning methods applied in DNA storage, identifying compression techniques for DNA storage, knowing the role of deep learning in the compression process for DNA storage, knowing how generative models are associated with deep learning, knowing how generative models are applied in the compression process, and knowing latent space can be formed. The study highlights open problems that need to be solved and provides an identified research direction

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Electronic Evidence and Electronic Signatures

In this updated edition of the well-established practitioner text, Stephen Mason and Daniel Seng have brought together a team of experts in the field to provide an exhaustive treatment of electronic evidence and electronic signatures. This fifth edition continues to follow the tradition in English evidence text books by basing the text on the law of England and Wales, with appropriate citations of relevant case law and legislation from other jurisdictions. Stephen Mason (of the Middle Temple, Barrister) is a leading authority on electronic evidence and electronic signatures, having advised global corporations and governments on these topics. He is also the editor of International Electronic Evidence (British Institute of International and Comparative Law 2008), and he founded the innovative international open access journal Digital Evidence and Electronic Signatures Law Review in 2004. Daniel Seng (Associate Professor, National University of Singapore) is the Director of the Centre for Technology, Robotics, AI and the Law (TRAIL). He teaches and researches information technology law and evidence law. Daniel was previously a partner and head of the technology practice at Messrs Rajah & Tann. He is also an active consultant to the World Intellectual Property Organization, where he has researched, delivered papers and published monographs on copyright exceptions for academic institutions, music copyright in the Asia Pacific and the liability of Internet intermediaries

Electronic Evidence and Electronic Signatures

In this updated edition of the well-established practitioner text, Stephen Mason and Daniel Seng have brought together a team of experts in the field to provide an exhaustive treatment of electronic evidence and electronic signatures. This fifth edition continues to follow the tradition in English evidence text books by basing the text on the law of England and Wales, with appropriate citations of relevant case law and legislation from other jurisdictions. Stephen Mason (of the Middle Temple, Barrister) is a leading authority on electronic evidence and electronic signatures, having advised global corporations and governments on these topics. He is also the editor of International Electronic Evidence, and he founded the innovative international open access journal Digital Evidence and Electronic Signatures Law Review in 2004. Daniel Seng (Associate Professor, National University of Singapore) is the Director of the Centre for Technology, Robotics, AI and the Law (TRAIL). He teaches and researches information technology law and evidence law. Daniel was previously a partner and head of the technology practice at Messrs Rajah & Tann. He is also an active consultant to the World Intellectual Property Organization, where he has researched, delivered papers and published monographs on copyright exceptions for academic institutions, music copyright in the Asia Pacific and the liability of Internet intermediaries

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

The HBP1 tumor suppressor is a negative epigenetic regulator of MYCN driven neuroblastoma through interaction with the PRC2 complex

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Anuário Científico – 2009 & 2010 Resumos de Artigos, Comunicações, Teses, Patentes, Livros e Monografias de Mestrado

O Conselho Técnico-Científico do Instituto Superior de Engenharia de Lisboa (ISEL), na senda da consolidação da divulgação do conhecimento e da ciência desenvolvidos pelo nosso corpo docente, propõe-se publicar mais uma edição do Anuário Científico, relativa à produção científica de 2009 e 2010. A investigação, enquanto vertente estratégica do Instituto Superior de Engenharia de Lisboa (ISEL), tem concorrido para o seu reconhecimento nacional e internacional como instituição de referência e de qualidade na área do ensino das engenharias. É também nesta vertente que o ISEL consubstancia a sua ligação à sociedade portuguesa e internacional através da transferência de tecnologia e de conhecimento, resultantes da sua atividade científica e pedagógica, contribuindo para o seu desenvolvimento e crescimento de forma sustentada. São parte integrante do Anuário Científico todos os conteúdos com afiliação ISEL resultantes de resumos de artigos publicados em livros, revistas e atas de congressos que os docentes do ISEL apresentaram em fóruns e congressos nacionais e internacionais, bem como teses e patentes. Desde 2002, ano da publicação da primeira edição, temos assistido a uma evolução crescente do número de publicações de conteúdos científicos, fruto do trabalho desenvolvido pelos docentes que se têm empenhado com afinco e perseverança. Contudo, nestes dois anos (2009 e 2010) constatou-se um decréscimo no número de publicações, principalmente em 2010. Uma das causas poderá estar diretamente relacionada com a redução do financiamento ao ensino superior uma vez que limita toda a investigação no âmbito da atividade de I&D e da produção científica. Na sequência da implementação do Processo de Bolonha em 2006, o ISEL promoveu a criação de cursos de Mestrado disponibilizando uma oferta educativa mais completa e diversificada aos seus alunos, mas também de outras instituições, dotando-os de competências inovadoras apropriadas ao mercado de trabalho que hoje se carateriza mais competitivo e dinâmico. Terminados os períodos escolar e de execução das monografias dos alunos, os resumos destas são igualmente parte integrante deste Anuário, no que concerne à conclusão dos Mestrados em 2009 e 2010.A fim de permitir uma maior acessibilidade à comunidade científica e à sociedade civil, o Anuário Científico será editado de ora avante em formato eletrónico. Excecionalmente esta edição contempla publicações referentes a dois anos – 2009 e 2010