A Lossless Data-Hiding based IoT Data Authenticity Model in Edge-AI for Connected Living

Edge computing is an emerging technology for the acquisition of Internet-of-Things (IoT) data and provisioning different services in connected living. Artificial Intelligence (AI) powered edge devices (edge-AI) facilitate intelligent IoT data acquisition and services through data analytics. However, data in edge networks are prone to several security threats such as external and internal attacks and transmission errors. Attackers can inject false data during data acquisition or modify stored data in the edge data storage to hamper data analytics. Therefore, an edge-AI device must verify the authenticity of IoT data before using them in data analytics. This article presents an IoT data authenticity model in edge-AI for a connected living using data hiding techniques. Our proposed data authenticity model securely hides the data source’s identification number within IoT data before sending it to edge devices. Edge-AI devices extract hidden information for verifying data authenticity. Existing data hiding approaches for biosignal cannot reconstruct original IoT data after extracting the hidden message from it (i.e., lossy) and are not usable for IoT data authenticity. We propose the first lossless IoT data hiding technique in this article based on error-correcting codes (ECCs). We conduct several experiments to demonstrate the performance of our proposed method. Experimental results establish the lossless property of the proposed approach while maintaining other data hiding properties.

Design and development of learning model for compression and processing of deoxyribonucleic acid genome sequence

Owing to the substantial volume of human genome sequence data files (from 30-200 GB exposed) Genomic data compression has received considerable traction and storage costs are one of the major problems faced by genomics laboratories. This involves a modern technology of data compression that reduces not only the storage but also the reliability of the operation. There were few attempts to solve this problem independently of both hardware and software. A systematic analysis of associations between genes provides techniques for the recognition of operative connections among genes and their respective yields, as well as understandings into essential biological events that are most important for knowing health and disease phenotypes. This research proposes a reliable and efficient deep learning system for learning embedded projections to combine gene interactions and gene expression in prediction comparison of deep embeddings to strong baselines. In this paper we preform data processing operations and predict gene function, along with gene ontology reconstruction and predict the gene interaction. The three major steps of genomic data compression are extraction of data, storage of data, and retrieval of the data. Hence, we propose a deep learning based on computational optimization techniques which will be efficient in all the three stages of data compression.

Formal Modelling and Automated Trade-off Analysis of Enforcement Architectures for Cryptographic Access Control in the Cloud

To facilitate the adoption of cloud by organizations, Cryptographic Access Control (CAC) is the obvious solution to control data sharing among users while preventing partially trusted Cloud Service Providers (CSP) from accessing sensitive data. Indeed, several CAC schemes have been proposed in the literature. Despite their differences, available solutions are based on a common set of entities—e.g., a data storage service or a proxy mediating the access of users to encrypted data—that operate in different (security) domains—e.g., on-premise or the CSP. However, the majority of these CAC schemes assumes a fixed assignment of entities to domains; this has security and usability implications that are not made explicit and can make inappropriate the use of a CAC scheme in certain scenarios with specific trust assumptions and requirements. For instance, assuming that the proxy runs at the premises of the organization avoids the vendor lock-in effect but may give rise to other security concerns (e.g., malicious insiders attackers). To the best of our knowledge, no previous work considers how to select the best possible architecture (i.e., the assignment of entities to domains) to deploy a CAC scheme for the trust assumptions and requirements of a given scenario. In this article, we propose a methodology to assist administrators in exploring different architectures for the enforcement of CAC schemes in a given scenario. We do this by identifying the possible architectures underlying the CAC schemes available in the literature and formalizing them in simple set theory. This allows us to reduce the problem of selecting the most suitable architectures satisfying a heterogeneous set of trust assumptions and requirements arising from the considered scenario to a decidable Multi-objective Combinatorial Optimization Problem (MOCOP) for which state-of-the-art solvers can be invoked. Finally, we show how we use the capability of solving the MOCOP to build a prototype tool assisting administrators to preliminarily perform a “What-if” analysis to explore the trade-offs among the various architectures and then use available standards and tools (such as TOSCA and Cloudify) for automated deployment in multiple CSPs.

Cloud Computing Models for Business

The idea of cloud computing is not a new one, it has been developed and discussed for many years. Cloud computing is a model which allows to get access to the network upon request from the set of adjustable computing services, such as infrastructure, applications and storages. Cloud services and data storage products allow their users to store and share any type of document and file from any device connected to Internet. There are several types of cloud services, which can be subdivided into: SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service). Besides, there are several deployment models, such as public, residential, hybrid or community cloud. Cloud computing models are based on modern process paradigm, which offers new alternatives to the companies of various ranges for implementation of innovative business models. With the help of these new business models small companies will be able to use cloud computing platforms and to increase gradually their computation capacities and data storage capacities depending on the requirements in real time mode, which creates a unique opportunity for market competition. Keywords— cloud computing, IaaS, OpenStack, PaaS, SaaS.

PEMBINAAN TEKNOLOGI INFORMASI DAN SISTEM OPERASIONAL BANK SYARIAH

Information technology is a knowledge that is always evolving from tools or communication which is a delivery of information through rapid communications, which relates to information problems in terms of all aspects ranging from data collection, data storage, data processing from information to the process of delivering information to people who need it. The purpose of fostering information technology and healthy internet use is an educational process by providing sufficient understanding of the current latest technology and being educated with the Islamic bank operating system, the owner of the fund invests his money so he can earn interest from the bank. If the profit sharing from the customer's funds is then distributed to those in need (eg venture capital), with a profit sharing agreement according to the agreement. Guidance on the Development of Information Technology and Bank Sariah Operational Systems at the Vocational High School Nang Nadim Batam to find out how to use good information technology and know the operating system of the Sariah bank. With this coaching, it is hoped that students will be helped in understanding the service that was carried out on January 15 and 16, 2019 at SMK Hang Nadim Batu Aji, Batam City.

Key Issues for Realizing Open Ecoacoustic Monitoring in Australia

Many organizations are attempting to scale ecoacoustic monitoring for conservation but are hampered at the stages of data management and analysis. We reviewed current ecoacoustic hardware, software, and standards, and conducted workshops with 23 participants across 10 organizations in Australia to learn about their current practices, and to identify key trends and challenges in their use of ecoacoustics data. We found no existing metadata schemas that contain enough ecoacoustics terms for current practice, and no standard approaches to annotation. There was a strong need for free acoustics data storage, discoverable learning resources, and interoperability with other ecological modeling tools. In parallel, there were tensions regarding intellectual property management, and siloed approaches to studying species within organizations across different regions and between organizations doing similar work. This research contributes directly to the development of an open ecoacoustics platform to enable the sharing of data, analyses, and tools for environmental conservation.

Adoption of cloud computing tools for sustainable construction: a structural equation modelling approach

Purpose The purpose of this paper is to assess the cloud computing (CC) methods and tools towards the achievement of construction project sustainability in Nigeria. Design/methodology/approach Data were obtained from the literature, complemented by a quantitative method using a questionnaire distributed among 104 respondents comprising mainly construction professionals in Nigeria. Subsequently, data were analysed using the exploratory factor analysis (EFA) method. In addition, the partial least square structural modelling was used to generate a model for the adoption of CC tools for sustainable construction. Findings EFA results indicated that the CC implementation tools could be categorised into four significant constructs: platform, communication, software and data storage. Results obtained from the model showed that platform tools were the most crucial tools for implementing CC in the construction industry. Practical implications The findings from this study are essential to the pursuit of perception of methods and tools connected to the vagueness of CC for future employees. In addition, the identified CC tools are expected to enhance the success of construction projects. Originality/value The novelty of this research work will be a benchmark or board for decision-makers to quality by adopting CC methods and tools in Nigeria’s construction projects to achieve their sustainable projects.

Application of Heterogeneous Network Oriented to NoSQL Database in Optimal Postevaluation Indexes of Construction Projects

With the advent of the Internet Web 2.0 era, storage devices used to store website data are developing at an ever-increasing high-growth rate and a diversified trend. The focus on the structured data storage model has reduced the responsiveness of traditional relational databases to data changes. NoSQL database is scalable, has a powerful and flexible data model and a large amount of data, and has an increasing application potential in the memory field. Heterogeneous networks are composed of third-party computers, network equipment, and systems. Network types are usually used for other protocols to support other functions and applications. The research on heterogeneous networks can be traced back to the BARWAN project that started in 1995 at the University of California, Berkeley. The project leader RHKatz merged multiple types of nested networks for the first time to form heterogeneous network requirements for various future terminal services. Construction engineering refers to an engineering entity formed by installing pipelines and equipment that support the construction of various houses and ancillary facilities. “House construction” refers to projects with roofs, beams, columns, walls, and foundations that can form internal spaces to meet people’s needs in production, living, learning, and public activities. Among them, the engineering evaluation index is a statistical index used to evaluate and compare the quality and effects of social and economic activities through the use of equipment, such as capital turnover rate and employee labor efficiency. It is the exchange of corporate performance evaluation content and the expression of corporate performance evaluation content.