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The context of this chapter is the use of data and advanced data analytics in a commercial setting. Privacy is considered as protection from vulnerability, whereby vulnerability is understood as the state of being exposed to the possibility of being harmed, either physically or emotionally, or in fundamental rights other than privacy. Therefore, privacy's policy instruments, in particular data protection law, could be seen as a means to reduce the risk of harm resulting from data use. Such harm is probabilistic and often uncertain, which, however, does not exclude analyzing costs and benefits of regulatory data protection policies. When balancing privacy protections and opportunities for knowledge gain, regulatory policy could be viewed as superior, when it expands the range of possible trade-offs between vulnerability protection and gaining socially beneficial knowledge.

The purpose of this paper is to solve the problem of information privacy and security of social users. Mobile internet and social network are more and more deeply integrated into people’s daily life, especially under the interaction of the fierce development momentum of the Internet of Things and diversified personalized services, more and more private information of social users is exposed to the network environment actively or unintentionally. In addition, a large amount of social network data not only brings more benefits to network application providers, but also provides motivation for malicious attackers. Therefore, under the social network environment, the research on the privacy protection of user information has great theoretical and practical significance.

In this study, based on the social network analysis, combined with the attribute reduction idea of rough set theory, the generalized reduction concept based on multi-level rough set from the perspectives of positive region, information entropy and knowledge granularity of rough set theory were proposed. Furthermore, it was traversed on the basis of the hierarchical compatible granularity space of the original information system and the corresponding attribute values are coarsened. The selected test data sets were tested, and the experimental results were analyzed.

The results showed that the algorithm can guarantee the anonymity requirement of data publishing and improve the effect of classification modeling on anonymous data in social network environment.

In the test and verification of privacy protection algorithm and privacy protection scheme, the efficiency of algorithm and scheme needs to be tested on a larger data scale. However, the data in this study are not enough. In the following research, more data will be used for testing and verification.

In the context of social network, the hierarchical structure of data is introduced into rough set theory as domain knowledge by referring to human granulation cognitive mechanism, and rough set modeling for complex hierarchical data is studied for hierarchical data of decision table. The theoretical research results are applied to hierarchical decision rule mining and k-anonymous privacy protection data mining research, which enriches the connotation of rough set theory and has important theoretical and practical significance for further promoting the application of this theory. In addition, combined the theory of secure multi-party computing and the theory of attribute reduction in rough set, a privacy protection feature selection algorithm for multi-source decision table is proposed, which solves the privacy protection problem of feature selection in distributed environment. It provides a set of effective rough set feature selection method for privacy protection classification mining in distributed environment, which has practical application value for promoting the development of privacy protection data mining.

In this study, the proposed algorithm and scheme can effectively protect the privacy of social network data, ensure the availability of social network graph structure and realize the need of both protection and sharing of user attributes and relational data.

Despite concerns about digital privacy, little is known about emotional distress about data hacking and surveillance incidents. The purpose of this paper is to examine variables predicting anxiety about data hacking, and the role that such anxiety and other potentially important variables have in explaining the use of digital privacy protection behavior.

In total, 305 participants from an online labor market were sampled who frequently use the internet, surveyed about recent anxiety (using the Generalized Anxiety Disorder-7 scale (GAD-7)), anxiety about data hacking (GAD-7, in reference to data hacking), and issues of digital privacy: news exposure, perceived importance, self-efficacy, protection behavior, and previous hacking victimization.

Profession (information technology-related) moderated the symptom structure for recent anxiety, but not data hacking anxiety. Using structural equation modeling, prior hacking victimization predicted anxiety about hacking. Digital privacy protection behavior was related to hacking anxiety and privacy self-efficacy. Data hacking anxiety mediated relations between hacking victimization and privacy protection. Privacy self-efficacy mediated relations between news exposure to hacking incidents and privacy protection.

Limitations include the self-report nature of the instruments, and use of a selective, non-random sample.

Results highlight knowledge, self-efficacy, and threat appraisal among IT managers in motivating better digital security practices.

This is the first study using a standardized instrument of anxiety to examine distress about hacking and predictors of digital privacy protection behavior.

The purpose of this study is to identify how the privacy policy can be framed for protection of personal data and how the latest judgement of full bench of Supreme Court of India has dealt with right to privacy in India.

The study uses the latest Supreme Court judgement on right to privacy and historical cases on right to privacy in India. This paper uses Indian Constitution as a source of Information for study along with case laws and judgements of different courts in India.

This paper tries to find if personal data privacy is a fundamental right in India. In addition, the paper provides recommendations to different concerned authorities on protecting personal information in online platform.

This study deals with privacy issues so far as Indian citizens are concerns and does not focus on other countries. Moreover, the study tries to understand the issue of fundamental rights from Indian Constitution perspective. In addition, the recommendations provided to the policymakers and other authorities of India have wide implications for formulation of new policy and management of personal data, so that it should not go to wrong hands and the personal data and privacy is protected of the citizens.

Millions of people put their personal information in online platform. In addition, there are few government initiatives in India such as Aadhaar card where the biometric information is taken from the residents of India, and in many cases, the personal data are compromised under various circumstances. As the personal data of the citizens are in question, thus the study has direct practical implication mainly for all the citizens whose personal data are available in online platform.

This study has social implication as it dealt with the “personal data” of the citizens of India. As the paper discusses the issue of protection of personal data in the context of right to privacy, thus this study has a direct social impact so far as online citizen of India is concerned.

This paper is timely, original and discusses the contemporary issue of online data privacy and fundamental right in India. This paper is a useful resource for the researchers, policymakers and online users who deal with personal data-, right to privacy and data privacy policy-related areas.

The move toward e-health care in various countries is envisaged to reduce the cost of provision of health care, improve the quality of care and reduce medical errors. The most significant problem is the protection of patients’ data privacy. If the patients are reluctant or refuse to participate in health care system due to lack of privacy laws and regulations, the benefit of the full-fledged e-health care system cannot be materialized. The purpose of this paper is to investigate the available e-health data privacy protection laws and the perception of the people using the e-health care facilities.

The researchers used content analysis to analyze the availability and comprehensive nature of the laws and regulations. The researchers also used survey method. Participants in the study comprised of health care professionals (n=46) and health care users (n=187) who are based in the Dubai, United Arab Emirates. The researchers applied descriptive statistics mechanisms and correlational analysis to analyze the data in the survey.

The content analysis revealed that the available health data protection laws are limited in scope. The survey results, however, showed that the respondents felt that they could trust the e-health services systems offered in the UAE as the data collected is protected, the rights are not violated. The research also revealed that there was no significance difference between the nationality and the privacy data statements. All the nationality agreed that there is protection in place for the protection of e-health data. There was no significance difference between the demographic data sets and the many data protection principles.

The findings on the users’ perception could help to evaluate the success in realizing current strategies and an action plan of benchmarking could be introduced.

Given the unique cultural-political context of China, this paper aims to investigate two research questions: What has been the development trajectory of policy-making on consumer privacy protection in China, and what factors have shaped its development over the years?

This paper adopts a historical approach and examines the development of Chinese consumer privacy policy during four periods: 1980s, 1990s, 2000s and 2010-present.

Chinese policy-making on consumer privacy protection has made steady advancement in the past few decades due to factors such as technological development, elite advocacy and emulation of other markets; however, the effects of these factors are conditioned by local forces.

To date, most studies of consumer privacy issues have focused on Western countries, especially the European Union and the USA. A better understanding of how consumer privacy policy has developed in China provides important lessons on the promotion of consumer privacy protection in other developing countries.

First, the authors analyze the key problems faced by the protection of digital library readers' data privacy and behavior privacy. Second, the authors introduce the characteristics of all kinds of existing approaches to privacy protection and their application limitations in the protection of readers' data privacy and behavior privacy. Lastly, the authors compare the advantages and disadvantages of each kind of existing approaches in terms of security, efficiency, accuracy and practicality and analyze the challenges faced by the protection of digital library reader privacy.

In this paper, the authors review a number of research achievements relevant to privacy protection and analyze and evaluate the application limitations of them in the reader privacy protection of a digital library, consequently, establishing the constraints that an ideal approach to library reader privacy protection should meet, so as to provide references for the follow-up research of the problem.

As a result, the authors conclude that an ideal approach to reader privacy protection should be able to comprehensively improve the security of all kinds of readers' privacy information on the untrusted server-side as a whole, under the premise of not changing the architecture, efficiency, accuracy and practicality of a digital library system.

Along with the rapid development of new network technologies, such as cloud computing, the server-side of a digital library is becoming more and more untrustworthy, thereby, posing a serious threat to the privacy of library readers. In fact, the problem of reader privacy has become one of the important obstacles to the further development and application of digital libraries.

This study aims to identify the roles that privacy experiences and social media use play in influencing privacy-protection behaviors. As social media use expands in terms of the number of users and functionality; it is important to understand social media user privacy-protection behaviors and the users’ psychological underpinnings driving those behaviors. Among these, perceptions are the users’ evaluation of their privacy concerns and data sharing benefits inherent in social media use which influence the users’ behaviors to protect their privacy.

To research these issues, a theoretical model and hypotheses were developed, based on self-efficacy theory. The theoretical model was empirically tested using 193 questionnaire responses collected from students enrolled in business courses at a medium-sized university in the western USA. All the respondents reported that they routinely use social media. The empirical analysis was performed using structural equations modeling in PC SAS version 9.4, procedure Calis.

The estimation of the paths in the structural model indicates that privacy concerns positively influence social media users’ protection behaviors while the perceived benefits of data sharing negatively influence protection behaviors. Privacy experience positively influences privacy concerns. Alternatively, social media use positively influences social media self-efficacy and perceived usefulness, which, in turn, have meaningful influences on data sharing benefits.

Previous findings about the effect of self-efficacy on protection behaviors has been inconclusive. This study adds some clarity. Specifically, the findings suggest that the effect depends upon the foci of self-efficacy. While higher self-efficacy with respect to using privacy-related features of a specific technology tends to lead to greater privacy concerns, higher self-efficacy with respect to the more general technology (e.g. social media, computer) seems to affect protection behaviors through perceived benefits. Further, the results of this study offer conclusions about the roles that privacy experiences, social media use and perceived social media benefits play in affecting protection behaviors.

Privacy concerns and data security are changing the risks for businesses and organisations. This indicates that the accountability of all governance participants changes. This paper aims to investigate the role of external auditors within data protection practices and how their role is evolving due to the current digital ecosystem.

By surveying the literature, the authors embrace a practice-oriented perspective to explain how data protection practices emerge, exist and occur and examine the auditors’ position within data protection.

Auditors need to align their tasks to the purpose of data protection practices. Accordingly, in accessing and using data, auditors are required to engage moral judgements and follow ethical principles that go beyond their legal responsibility. Simultaneously, their accountability extends to data protection ends for instilling confidence that security risks are properly managed. Due to the changing technological conditions under, which auditors operate, the traditional auditors’ task of hearing and verifying extend to new phenomena that create risks for businesses. Thus, within data protection practices, auditors have the accountability to keep interested parties informed about data security and privacy risks, continue to transmit signals to users and instill confidence in businesses.

The normative level of the study is a research limitation, which calls for future empirical research on how Big Data and data protection is reshaping accounting and auditing practices.

This paper provides auditing standard setters and practitioners with insights into the redefinitions of auditing practices in the era of Big Data.

Recent privacy concerns at Facebook have sent warning signals across the world about the risks posed by in Big Data systems in terms of privacy, to those charged with governance of organisations. Auditors need to understand these privacy issues to better serve their clients.

This paper contributes to triggering discussions and future research on data protection and privacy in accounting and auditing research, which is an emerging, yet unresearched topic.