scholarly journals Methodology for Measuring the Impact of the Privacy Protection Law on the Use of Big Data

2021 ◽  
Vol 15 ◽  
pp. 62-66
Author(s):  
Oh Ky U-Cheol
Keyword(s):  
Big Data ◽  
Stock Prices ◽  
Privacy Protection ◽  
Turning Point ◽  
Personal Information ◽  
Legal Regulation ◽  
Technical Innovation ◽  
Smart Devices ◽  
Ict Revolution ◽  
The Impact

The ICT revolution triggered by the emergence of smart devices, typically represented by the iPhone and the iPad, is migrating into the new domain of ‘big data’ after passing the turning point of ‘SNS Life,’ which is represented by Twitter and FaceBook among others. These developments have brought significant changes in all areas of politics, economy and culture. The stock prices of Apple, Samsung Electronics, FaceBook and Google fluctuate depending on who takes the hegemony in the changes. Meanwhile, such a reform of the ICT sector has generated some new undesirable sideeffects, including online disclosure of personal information, malicious comments, Smishing or other forms of financial scams. As we cannot abandon either big data or privacy protection, it is critical to find a compromise. It seems both evident and selfexplanatory that the use of big data, which is attributable to technical innovation, conflicts with privacy protection based on the idea that individuals should be allowed to determine the disclosure or not of their personal information. Yet, the problem here is that the discussion of countermeasures remains at the level of catching the wind with a net. Therefore, this paper intends to present a framework that can objectively verify what impact the enhanced legal regulation concerning privacy protection has on the use of big data as the first step in exploring a compromise between the use of big data and privacy protection.

View analysis of personal information leakage and privacy protection in big data era—based on Q method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lei Huang ◽  
Jingyi Zhou ◽  
Jiecong Lin ◽  
Shengli Deng
Keyword(s):  
Big Data ◽  
Privacy Protection ◽  
Personal Information ◽  
Information Leakage ◽  
Q Method ◽  
Information Protection ◽  
Content Type ◽  
Trade Offs ◽  
Big Data Technology ◽  
Personal Information Protection

PurposeIn the era of big data, people are more likely to pay attention to privacy protection with facing the risk of personal information leakage while enjoying the convenience brought by big data technology. Furthermore, people’s views on personal information leakage and privacy protection are varied, playing an important role in the legal process of personal information protection. Therefore, this paper aims to propose a semi-qualitative method based framework to reveal the subjective patterns about information leakage and privacy protection and further provide  practical implications for interested party.Design/methodology/approachQ method is a semi-qualitative methodology which is designed for identifying typologies of perspectives. In order to have a comprehensive understanding of users’ viewpoints, this study incorporates LDA & TextRank method and other information extraction technologies to capture the statements from large-scale literature, app reviews, typical cases and survey interviews, which could be regarded as the resource of the viewpoints.FindingsBy adopting the Q method that aims for studying subjective thought patterns to identify users’ potential views, the authors have identified three categories of stakeholders’ subjectivities: macro-policy sensitive, trade-offs and personal information sensitive, each of which perceives different risk and affordance of information leakage and importance and urgency of privacy protection. All of the subjectivities of the respondents reflect the awareness of the issue of information leakage, that is, the interested parties like social network sites are unable to protect their full personal information, while reflecting varied resistance and susceptibility of disclosing personal information for big data technology applications.Originality/valueThe findings of this study provide an overview of the subjective patterns on the information leakage issue. Being the first to incorporate the Q method to study the views of personal information leakage and privacy protection, the research not only broadens the application field of the Q method but also enriches the research methods for personal information protection. Besides, the proposed LDA & TextRank method in this paper alleviates the limitation of statements resource in the Q method.

Data Mining, Big Data, Data Analytics

Web Services ◽  
2019 ◽  
pp. 89-104
Author(s):  
Priya P. Panigrahi ◽  
Tiratha Raj Singh
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Biological Data ◽  
Smart Devices ◽  
Data Life Cycle ◽  
The Impact ◽  
Special Relevance ◽  
Generation Sequencing

In this digital and computing world, data formation and collection rate are growing very rapidly. With these improved proficiencies of data storage and fast computation along with the real-time distribution of data through the internet, the usual everyday ingestion of data is mounting exponentially. With the continuous advancement in data storage and accessibility of smart devices, the impact of big data will continue to develop. This chapter provides the fundamental concepts of big data, its benefits, probable pitfalls, big data analytics and its impact in Bioinformatics. With the generation of the deluge of biological data through next generation sequencing projects, there is a need to handle this data trough big data techniques. The chapter also presents a discussion of the tools for analytics, development of a novel data life cycle on big data, details of the problems and challenges connected with big data with special relevance to bioinformatics.

Data Mining, Big Data, Data Analytics

2017 ◽  
pp. 91-111
Author(s):  
Priya P. Panigrahi ◽  
Tiratha Raj Singh
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Biological Data ◽  
Smart Devices ◽  
Data Life Cycle ◽  
The Impact ◽  
Special Relevance ◽  
Generation Sequencing

In this digital and computing world, data formation and collection rate are growing very rapidly. With these improved proficiencies of data storage and fast computation along with the real-time distribution of data through the internet, the usual everyday ingestion of data is mounting exponentially. With the continuous advancement in data storage and accessibility of smart devices, the impact of big data will continue to develop. This chapter provides the fundamental concepts of big data, its benefits, probable pitfalls, big data analytics and its impact in Bioinformatics. With the generation of the deluge of biological data through next generation sequencing projects, there is a need to handle this data trough big data techniques. The chapter also presents a discussion of the tools for analytics, development of a novel data life cycle on big data, details of the problems and challenges connected with big data with special relevance to bioinformatics.

The issues of implementing legislation on personal data in the era of big data

2020 ◽  
pp. 319-326
Author(s):  
Ekaterina Shebunova
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Nonprofit Organizations ◽  
Personal Data ◽  
Legal Regulation ◽  
Financial Control ◽  
Large Databases ◽  
The Impact ◽  
The Given ◽  
Improved Methods

We consider the impact of automation processes on the implementation of external financial control. We study the practical application features of new sources of data analysis – state information systems. In particular, the legal regulation of the functioning of such systems and their use for financial control purposes. We present methods for collecting and analyzing big data in order to improve the legal regulation of the budgetary process, as well as the law enforcement practice of using big data arising in the process of digitalization of the control and supervisory activities of external financial control bodies. We focus on the fact that big data analysis methods (for ex-ample, spatial analysis, social network analysis, machine learning, etc.) can be used to implement state financial control over the activities of nonprofit organizations. We find that improved methods of collecting and analyzing data helps not only to respond flexibly to sudden changes and make faster and more accurate decisions, but also to use large databases, which, in turn, allows us to move from monitoring the legality of spending to analyzing the effectiveness of use financial resources of the state. Based on the given ex-amples, we conclude that automation contributes to improving the methods of state financial control.

Group Privacy in Times of Big Data. A Literature Review

2016 ◽  
Vol 2 (2) ◽  
pp. 137-152 ◽  
Author(s):  
Paula Helm
Keyword(s):  
Big Data ◽  
New Technologies ◽  
Personal Information ◽  
Legal Regulation ◽  
The Other ◽  
Future Challenges ◽  
New Challenges ◽  
The One ◽  
Personal Law ◽  
Formation Of Groups

Abstract New technologies pose new challenges on the protection of privacy and they stimulate new debates on the scope of privacy. Such debates usually concern the individuals’ right to control the flow of his or her personal information. The article however discusses new challenges posed by new technologies in terms of their impact on groups and their privacy. Two main challenges are being identified in this regard, both having to do with the formation of groups through the involvement of algorithms and the lack of civil awareness regarding the consequences of this involvement. On the one hand, there is the phenomenon of groups being created on the basis of big data without the members of such groups being aware of having been assigned and being treated as part of a certain group. Here, the challenge concerns the limits of personal law, manifesting with the disability of individuals to address possible violations of their right to privacy since they are not aware of them. On the other hand, commercially driven Websites influence the way in which groups form, grow and communicate when doing this online and they do this in such subtle way, that members oftentimes do not take into account this influence. This is why one could speak of a kind of domination here, which calls for legal regulation. The article presents different approaches addressing and dealing with those two challenges, discussing their strengths and weaknesses. Finally, a conclusion gathers the insights reached by the different approaches discussed and reflects on future challenges for further research on group privacy in times of big data.

scholarly journals LIP-PA: A Logistics Information Privacy Protection Scheme with Position and Attribute-Based Access Control on Mobile Devices

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Qi Gao ◽  
Junwei Zhang ◽  
Jianfeng Ma ◽  
Chao Yang ◽  
Jingjing Guo ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Mobile Devices ◽  
Privacy Protection ◽  
Personal Information ◽  
Information Privacy ◽  
Smart Devices ◽  
Protection Scheme ◽  
Logistics Information ◽  
Attribute Based Access Control

With the fast development of Logistics Internet of Things and smart devices, the security of express information processed by mobile devices in Logistics Internet of Things has attracted much attention. However, the existing secure express schemes only focus on privacy protection of personal information but do not consider the security of the logistics information against couriers with malicious mobile devices. For example, a privacy-preserving delivery path should be required in order to prevent the privacy leakage in the express delivery procedure. Therefore, besides the security of personal information, the privacy protection of logistics information and authentication of mobile devices used in express company are important to security in Logistics Internet of Things. In this paper, we propose a secure logistics information scheme LIP-PA to provide privacy protection of both personal information and logistics information. First, we define the basic requirements of Logistics Internet of Things. Then, using attribute-based encryption and position-based key exchange, we propose a logistics information privacy protection scheme with position and attribute-based access control for mobile devices. The analysis results show that our scheme satisfies the defined requirements. Finally, the performance of our scheme is evaluated and the experiment results show that our scheme is efficient and feasible for mobile devices in real parcel delivery scenario.

Redefining Humanity in the Era of AI – Technical Civilization

Paragrana ◽  
2020 ◽  
Vol 29 (1) ◽  
pp. 83-93
Author(s):  
Shoko Suzuki
Keyword(s):  
Artificial Intelligence ◽  
Turning Point ◽  
Information And Communications Technology ◽  
Technical Innovation ◽  
Communications Technology ◽  
Human Capabilities ◽  
Human Environment ◽  
Massive Change ◽  
The Impact

AbstractThe human environment is currently undergoing massive change amid the rapid adoption of information and communications technology (ICT). ICT can be characterized as offering an opportunity to consider the nature of humanity, create new values, and foster new cultures. As humans, the question that technical innovation relating to Artificial Intelligence (AI) and Robots thrusts before us is, “What is a human?” What exactly are the things that AI will never be able to do, no matter how close it gets to human capabilities? What makes us humans, and what is it that only humans can do? This essay discusses the impact of AI technology on humans and society from the perspective of a turning point in how people perceive themselves and humanity.

scholarly journals The impact of transparency on mobile privacy decision making

2019 ◽  
Vol 30 (3) ◽  
pp. 607-625 ◽  
Author(s):  
Jan Hendrik Betzing ◽  
Matthias Tietz ◽  
Jan vom Brocke ◽  
Jörg Becker
Keyword(s):  
Data Processing ◽  
Service Providers ◽  
Personal Information ◽  
Mobile Apps ◽  
Personal Data ◽  
Smart Devices ◽  
General Data Protection Regulation ◽  
Personalized Services ◽  
Acceptance Rates ◽  
The Impact

Abstract Smart devices provide unprecedented access to users’ personal information, on which businesses capitalize to offer personalized services. Although users must grant permission before their personal information is shared, they often do so without knowing the consequences of their decision. Based on the EU General Data Protection Regulation, which mandates service providers to comprehensively inform users about the purpose and terms of personal data processing, this article examines how increased transparency regarding personal data processing practices in mobile permission requests impact users in making informed decisions. We conducted an online experiment with 307 participants to test the effect of transparency on users’ decisions about and comprehension of the requested permission. The results indicate increased comprehension of data processing practices when privacy policies are transparently disclosed, whereas acceptance rates do not vary significantly. We condense our findings into principles that service providers can apply to design privacy-transparent mobile apps.

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