A Meta-analysis of Big Data Security: How the Government Formulates a Model of Public Information and Security Assurance into Big Data

2021 ◽  
pp. 472-479
Author(s):  
Achmad Nurmandi ◽  
Danang Kurniawan ◽  
Misran ◽  
Salahudin
Keyword(s):  
Big Data ◽  
Data Security ◽  
Meta Analysis ◽  
Public Information ◽  
Security Assurance ◽  
The Government

Breaching intellectual capital: critical reflections on Big Data security

2018 ◽  
Vol 26 (3) ◽  
pp. 463-482 ◽  
Author(s):  
Matteo La Torre ◽  
John Dumay ◽  
Michele Antonio Rea
Keyword(s):  
Big Data ◽  
Intellectual Capital ◽  
Data Security ◽  
Economic Value ◽  
Public Information ◽  
Dark Side ◽  
Content Type ◽  
Security Breaches ◽  
Managerial Implications ◽  
New Research

PurposeReflecting on Big Data’s assumed benefits, this study aims to identify the risks and challenges of data security underpinning Big Data’s socio-economic value and intellectual capital (IC).Design/methodology/approachThe study reviews academic literature, professional documents and public information to provide insights, critique and projections for IC and Big Data research and practice.FindingsThe “voracity” for data represents a further “V” of Big Data, which results in a continuous hunt for data beyond legal and ethical boundaries. Cybercrimes, data security breaches and privacy violations reflect voracity and represent the dark side of the Big Data ecosystem. Losing the confidentiality, integrity or availability of data because of a data security breach poses threat to IC and value creation. Thus, cyberthreats compromise the social value of Big Data, impacting on stakeholders’ and society’s interests.Research limitations/implicationsBecause of the interpretative nature of this study, other researchers may not draw the same conclusions from the evidence provided. It leaves some open questions for a wide research agenda about the societal, ethical and managerial implications of Big Data.Originality/valueThis paper introduces the risks of data security and the challenges of Big Data to stimulate new research paths for IC and accounting research.

KUALITAS LAYANAN KETERBUKAAN INFORMASI PUBLIK BERBASIS WEBPORTAL PADA PEJABAT PENGELOLA INFORMASI DAN DOKUMENTASI (PPID) KABUPATEN SLEMAN TAHUN 2019

2020 ◽  
Vol 3 (1) ◽  
pp. 55-66
Author(s):  
Coni Wanprala ◽  
Isnaini Muallidin ◽  
Dewi Sekar Kencono
Keyword(s):  
Information Disclosure ◽  
Central Government ◽  
Public Information ◽  
Descriptive Study ◽  
Field Observations ◽  
Public Agencies ◽  
The Public ◽  
Qualitative Descriptive ◽  
The Government ◽  
Data Collection Technique

At present the development of technology and information has reached a very rapid level. Technology and information are used as a service media in the government environment which is also known as e-Government, one of which is the service of public information disclosure. The central government through Law No. 14 of 2008 concerning Openness of Public Information, encourages all Public Agencies including the Sleman Regency Government to make transparency in the administration of the state by utilizing information technology. This research is a qualitative descriptive study which aims to describe the reality that occurs. The object of research in this study is the official website of the Information and Documentation Management Officer (PPID) of Sleman Regency with the domain https://ppid.slemankab.go.id then the Sleman Regency Communication and Informatics Office as the organizer of the public information disclosure program. The data collection technique itself is carried out by means of interviews, documentation studies, and field observations (observations). After collecting and presenting data, then the data will be reduced first then analyzed and concluded. From the results of the study, in general the researchers concluded that the Sleman Regency PPID website had reached the level of qualification to become a quality website, however there were still some improvements and evaluations that had to be done by the relevant agencies in order to be better, namely (i) the website was still being assessed as a one-way service (ii) There are still many OPDs that are not ready to implement PPID (iii) data and information are still not updated (iv) lack of responsiveness of services in requests for information.

Big Data Security Challenges and Solution of Distributed Computing in Hadoop Environment: A Security Framework

2020 ◽  
Vol 13 (4) ◽  
pp. 790-797
Author(s):  
Gurjit Singh Bhathal ◽  
Amardeep Singh Dhiman
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Sets ◽  
Security Framework ◽  
Hadoop Distributed File System ◽  
Current Scenario ◽  
Hadoop Cluster ◽  
Ciphertext Policy ◽  
In Transit ◽  
Hadoop Framework

Background: In current scenario of internet, large amounts of data are generated and processed. Hadoop framework is widely used to store and process big data in a highly distributed manner. It is argued that Hadoop Framework is not mature enough to deal with the current cyberattacks on the data. Objective: The main objective of the proposed work is to provide a complete security approach comprising of authorisation and authentication for the user and the Hadoop cluster nodes and to secure the data at rest as well as in transit. Methods: The proposed algorithm uses Kerberos network authentication protocol for authorisation and authentication and to validate the users and the cluster nodes. The Ciphertext-Policy Attribute- Based Encryption (CP-ABE) is used for data at rest and data in transit. User encrypts the file with their own set of attributes and stores on Hadoop Distributed File System. Only intended users can decrypt that file with matching parameters. Results: The proposed algorithm was implemented with data sets of different sizes. The data was processed with and without encryption. The results show little difference in processing time. The performance was affected in range of 0.8% to 3.1%, which includes impact of other factors also, like system configuration, the number of parallel jobs running and virtual environment. Conclusion: The solutions available for handling the big data security problems faced in Hadoop framework are inefficient or incomplete. A complete security framework is proposed for Hadoop Environment. The solution is experimentally proven to have little effect on the performance of the system for datasets of different sizes.

Telemedicine (or Teleconsultation?) Practice Guidelines of India: A Game changer or a half-hearted attempt amid COVID-19? (Preprint)

2020 ◽  
Author(s):  
Venkatesh U ◽  
Aravind Gandhi P
Keyword(s):  
Health Care ◽  
Practice Guidelines ◽  
Health Care Workers ◽  
Data Security ◽  
Patient Relationship ◽  
Medical Practitioners ◽  
Care Workers ◽  
The Government ◽  
First Time ◽  
Game Changer

UNSTRUCTURED Telemedicine is where health care intersects with Information Technology. In India, there has been no statutory regulations or official guidelines, specific for Telemedicine practice and allied matters, so far. For the first time, Government of India has released Telemedicine Practice Guidelines for Registered Medical Practitioners on March 25, 2020, amid the COVID-19 outbreak. Through this paper, we would like to initiate the discussion on the features of the guidelines, limitations, and its significance in times of COVID-19 pandemic. The guidelines are with a restricted scope for providing medical consultation to patients, excluding other aspects of Telemedicine such as research and evaluation, and the continuing education of health-care workers. The guidelines have elaborated on the eligibility for practicing Telemedicine in India, the modes and types of Teleconsultation, delved into doctor-patient relationship, consent, & management protocols, touched upon the data security & privacy aspects of the Teleconsultation. After releasing the guidelines, Telescreening of public for COVID-19 symptoms is being advocated by the Government of India. COVID-19 National Teleconsultation Centre (CoNTeC) has been initiated, which connects the doctors across the India to AIIMS in real-time for accessing expert guidance on treatment of the COVID-19 patients.

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

scholarly journals DaLiF: a data lifecycle framework for data-driven governments

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Syed Iftikhar Hussain Shah ◽  
Vassilios Peristeras ◽  
Ioannis Magnisalis
Keyword(s):  
Big Data ◽  
Data Management ◽  
Good Governance ◽  
Business Community ◽  
Data Driven ◽  
Governmental Organizations ◽  
Data Lifecycle ◽  
The Government ◽  
Data Ecosystem ◽  
Governance Transparency

AbstractThe public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

Mapping the United Nations Fundamental Principles of Official Statistics against new and big data sources

2021 ◽  
Vol 37 (1) ◽  
pp. 161-169
Author(s):  
Dominik Rozkrut ◽  
Olga Świerkot-Strużewska ◽  
Gemma Van Halderen
Keyword(s):  
Big Data ◽  
Public Information ◽  
Fundamental Principle ◽  
Data Sources ◽  
Official Statistics ◽  
Development Agenda ◽  
Data Gaps ◽  
Data Source ◽  
Exciting Time ◽  
Statistical Systems

Never has there been a more exciting time to be an official statistician. The data revolution is responding to the demands of the CoVID-19 pandemic and a complex sustainable development agenda to improve how data is produced and used, to close data gaps to prevent discrimination, to build capacity and data literacy, to modernize data collection systems and to liberate data to promote transparency and accountability. But can all data be liberated in the production and communication of official statistics? This paper explores the UN Fundamental Principles of Official Statistics in the context of eight new and big data sources. The paper concludes each data source can be used for the production of official statistics in adherence with the Fundamental Principles and argues these data sources should be used if National Statistical Systems are to adhere to the first Fundamental Principle of compiling and making available official statistics that honor citizen’s entitlement to public information.

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