Big Data Ethics in Research

The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (Data Protection Directive - General Data Protection Regulation, "GDPR"). The Ethics Issues section details the specific aspects of Big Data. After a brief section of Big Data Research, I finalize my work with the presentation of Conclusions on research ethics in working with Big Data. CONTENTS: Abstract 1. Introduction - 1.1 Definitions - 1.2 Big Data dimensions 2. Technology - 2.1 Applications - - 2.1.1 In research 3. Philosophical aspects 4. Legal aspects - 4.1 GDPR - - Stages of processing of personal data - - Principles of data processing - - Privacy policy and transparency - - Purposes of data processing - - Design and implicit confidentiality - - The (legal) paradox of Big Data 5. Ethical issues - Ethics in research - Awareness - Consent - Control - Transparency - Trust - Ownership - Surveillance and security - Digital identity - Tailored reality - De-identification - Digital inequality - Privacy 6. Big Data research Conclusions Bibliography DOI: 10.13140/RG.2.2.11054.4640

A REVIEW ON INTERNET OF THINGS ARCHITECTURE FOR BIG DATA PROCESSING

The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper

Challenges for MapReduce in Big Data

In the Big Data community, MapReduce has been seen as one of the key enabling approaches for meeting continuously increasing demands on computing resources imposed by massive data sets. The reason for this is the high scalability of the MapReduce paradigm which allows for massively parallel and distributed execution over a large number of computing nodes. This paper identifies MapReduce issues and challenges in handling Big Data with the objective of providing an overview of the field, facilitating better planning and management of Big Data projects, and identifying opportunities for future research in this field. The identified challenges are grouped into four main categories corresponding to Big Data tasks types: data storage (relational databases and NoSQL stores), Big Data analytics (machine learning and interactive analytics), online processing, and security and privacy. Moreover, current efforts aimed at improving and extending MapReduce to address identified challenges are presented. Consequently, by identifying issues and challenges MapReduce faces when handling Big Data, this study encourages future Big Data research

RESEARCH ON SECURE VIRUS TROJAN IN CYBERSECURITY PLATFORM

Security is main issue of this generation of computing because many types of attacks are increasing day by day. Establishing a network is not a big issue for network administrators but protecting the entire network is a big issue. There are various methods and tools are available today for destroying the existing network. In this paper we mainly emphasize on the network security also we present some major issues that can affect our network, Trojan horse virus can give rise to the leakage of internal data. Keywords:Security, Trojan Horse, System, Network

Applied business analytics approach to IT projects – Methodological framework

The design and implementation of a big data project differs from a typical business intelligence project that might be presented concurrently within the same organization. A big data initiative typically triggers a large scale IT project that is expected to deliver the desired outcomes. The industry has identified two major methodologies for running a data centric project, in particular SEMMA (Sample, Explore, Modify, Model and Assess) and CRISP-DM (Cross Industry Standard Process for Data Mining). More general, the professional organizations PMI (Project Management Institute) and IIBA (International Institute of Business Analysis) have defined their methods for project management and business analysis based on the best current industry practices. However, big data projects place new challenges that are not considered by the existing methodologies. The building of end-to-end big data analytical solution for optimization of the supply chain, pricing and promotion, product launch, shop potential and customer value is facing both business and technical challenges. The most common business challenges are unclear and/or poorly defined business cases; irrelevant data; poor data quality; overlooked data granularity; improper contextualization of data; unprepared or bad prepared data; non-meaningful results; lack of skill set. Some of the technical challenges are related to lag of resources and technology limitations; availability of data sources; storage difficulties; security issues; performance problems; little flexibility; and ineffective DevOps. This paper discusses an applied business analytics approach to IT projects and addresses the above-described aspects. The authors present their work on research and development of new methodological framework and analytical instruments applicable in both business endeavors, and educational initiatives, targeting big data. The proposed framework is based on proprietary methodology and advanced analytics tools. It is focused on the development and the implementation of practical solutions for project managers, business analysts, IT practitioners and Business/Data Analytics students. Under discussion are also the necessary skills and knowledge for the successful big data business analyst, and some of the main organizational and operational aspects of the big data projects, including the continuous model deployment

Analysis of Privacy Issues in Cloud Computing

Recent evolutions in information technology have led to a more distributed computing environment, while also reviving the utility of centralized storage. The growth in high-speed data lines, the falling cost of storage, the advent of wireless high-speed networks, the proliferation of handheld devices that can access the web – together, these factors mean that users now can store data on a server that likely resides in a remote data center. Cloud computing premise is very similar in that it provides a virtual computing environment that’s dynamically allocated to meet user needs. But How much secure is cloud computing environment is a big challenge. This paper, focused on the security issues in cloud computing and its main objectives to describe cloud computing and all major security risks and issues related with it

State sovereignty and capitalism's relationship in the digital age. A critical analysis of platform capitalism, collaborative governance, and big data.

openThe aim of the research is to analyse the relationship between state sovereignty and market capitalism starting from the ‘80s in the western countries, after the advent of the new Information and Communication Technologies (ICTs). In order to do so, the thesis will display a schematic critique of the new forms of platform capitalism, platform urbanism, and big data analysis. The chapters will follow the three power relations between state, market, and citizens, assessing the various problems concerning the use of big data, such as security issues, exploitation, extraction of value, and democratic accountability. Apart from an organic critique, the following research’s main thesis is that the collaborative governance is a new conjunction ring between capitalism and state power, that brought into existence a new market of public service delivery and a sell-out of state political legitimacy. In the first chapter I will outline the historical framework that brought the diffusion of the ICTs, marking out the economical and political changes following the ‘80s. The second chapter will analyse the power relation between State and citizens. Following the two cases of Cambridge Analytica and Edward Snowden, I will discuss the evolution of state security and the riskiness related to big data for the democratic accountability. The third chapter will discuss the platform urbanism and the critiques concerning the Smart cities. With a critical perspective about collaborative governance, I will assert that in the last decades a new market based on the public service delivery has expanded, creating accountability and legitimacy issues for the western democracies. In the fourth and last chapter I will examine the power relation between citizens and the market, discussing the platform capitalism, the gig economy and the new forms of extraction of value related to the use of big data.The aim of the research is to analyse the relationship between state sovereignty and market capitalism starting from the ‘80s in the western countries, after the advent of the new Information and Communication Technologies (ICTs). In order to do so, the thesis will display a schematic critique of the new forms of platform capitalism, platform urbanism, and big data analysis. The chapters will follow the three power relations between state, market, and citizens, assessing the various problems concerning the use of big data, such as security issues, exploitation, extraction of value, and democratic accountability. Apart from an organic critique, the following research’s main thesis is that the collaborative governance is a new conjunction ring between capitalism and state power, that brought into existence a new market of public service delivery and a sell-out of state political legitimacy. In the first chapter I will outline the historical framework that brought the diffusion of the ICTs, marking out the economical and political changes following the ‘80s. The second chapter will analyse the power relation between State and citizens. Following the two cases of Cambridge Analytica and Edward Snowden, I will discuss the evolution of state security and the riskiness related to big data for the democratic accountability. The third chapter will discuss the platform urbanism and the critiques concerning the Smart cities. With a critical perspective about collaborative governance, I will assert that in the last decades a new market based on the public service delivery has expanded, creating accountability and legitimacy issues for the western democracies. In the fourth and last chapter I will examine the power relation between citizens and the market, discussing the platform capitalism, the gig economy and the new forms of extraction of value related to the use of big data

Secure Development of Big Data Ecosystems

A Big Data environment is a powerful and complex ecosystem that helps companies extract important information from data to make the best business and strategic decisions. In this context, due to the quantity, variety, and sensitivity of the data managed by these systems, as well as the heterogeneity of the technologies involved, privacy and security especially become crucial issues. However, ensuring these concerns in Big Data environments is not a trivial issue, and it cannot be treated from a partial or isolated perspective. It must be carried out through a holistic approach, starting from the definition of requirements and policies, and being present in any relevant activity of its development and deployment. Therefore, in this paper, we propose a methodological approach for integrating security and privacy in Big Data development based on main standards and common practices. In this way, we have defined a development process for this kind of ecosystems that considers not only security in all the phases of the process but also the inherent characteristics of Big Data. We describe this process through a set of phases that covers all the relevant stages of the development of Big Data environments, which are supported by a customized security reference architecture (SRA) that defines the main components of this kind of systems along with the key concepts of security

Big Data Regulatory Legislation: Security, Privacy and Smart City Governance

Dubai is a smart city: this cannot be contested. The city has labelled itself as a globally recognized successful smart city and it has set in place a vision and a strategy to achieve the goal to become a smart city and to keep this status. Therefore, to sustain its competiveness, the Government of Dubai is considering the massive, fast and diverse data moving quickly everywhere creating what is known as “Big Data” era. This data is becoming the most important source of valuable insights and ultimately helping to make more informed decisions. Despite the growing demand and hopes with the big data, legal and ethical issues related to accessing data remains the main challenge. Therefore, in 2017, Dubai has announced its new Big Data Regulations Act aiming at regulating the big data usage and access to improve policies for better quality of life. This comes as part of the Smart Dubai roadmap to prepare Dubai to embrace the future and emerge as a world-leading city by 2021. The new regulations aim at ensuring privacy, security and governance of the data. The paper will explore the new regulatory act, and evaluate how it sustains and develop comprehensive infrastructure for the big data era in Dubai to maintain the city’s vision. Keywords: Big Data, Smart City, Dubai Data Law, Governance DOI: 10.7176/JLPG/95-03 Publication date:March 31st 202

RESEARCH ON SECURE VIRUS TROJAN IN CYBERSECURITY PLATFORM

Security is main issue of this generation of computing because many types of attacks are increasing day by day. Establishing a network is not a big issue for network administrators but protecting the entire network is a big issue. There are various methods and tools are available today for destroying the existing network. In this paper we mainly emphasize on the network security also we present some major issues that can affect our network, Trojan horse virus can give rise to the leakage of internal data. Keywords:Security, Trojan Horse, System, Network