Security and Privacy Data Protection Methods for Online Social Networks in the Era of Big Data

2020 ◽  
pp. 53-66
Author(s):  
Lei Ma ◽  
Ying-jian Kang
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Data Protection ◽  
Online Social Networks ◽  
Security And Privacy

scholarly journals Privacy and Security Issues in Online Social Networks

2018 ◽  
Vol 10 (12) ◽  
pp. 114 ◽  
Author(s):  
Shaukat Ali ◽  
Naveed Islam ◽  
Azhar Rauf ◽  
Ikram Din ◽  
Mohsen Guizani ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Service Providers ◽  
Security And Privacy ◽  
Security Issue ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Security Issues ◽  
Social Sphere

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

Access Control Models for Online Social Networks

2014 ◽  
pp. 451-484
Author(s):  
Rula Sayaf ◽  
Dave Clarke
Keyword(s):  
Social Networks ◽  
Access Control ◽  
Online Social Networks ◽  
Personal Data ◽  
Security And Privacy ◽  
Open Problems ◽  
Access Control Models ◽  
Control Models ◽  
Underlying Mechanisms ◽  
High Level

Access control is one of the crucial aspects in information systems security. Authorizing access to resources is a fundamental process to limit potential privacy violations and protect users. The nature of personal data in online social networks (OSNs) requires a high-level of security and privacy protection. Recently, OSN-specific access control models (ACMs) have been proposed to address the particular structure, functionality and the underlying privacy issues of OSNs. In this survey chapter, the essential aspects of access control and review the fundamental classical ACMs are introduced. The specific OSNs features and review the main categories of OSN-specific ACMs are highlighted. Within each category, the most prominent ACMs and their underlying mechanisms that contribute enhancing privacy of OSNs are surveyed. Toward the end, more advanced issues of access control in OSNs are discussed. Throughout the discussion, different models and highlight open problems are contrasted. Based on these problems, the chapter is concluded by proposing requirements for future ACMs.

Security and Privacy Challenges in Big Data

2020 ◽  
pp. 97-124
Author(s):  
Dharmpal Singh ◽  
Ira Nath ◽  
Pawan Kumar Singh
Keyword(s):  
Big Data ◽  
Data Protection ◽  
High Performance ◽  
Digital Transformation ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Data Safety ◽  
Amount Of Information ◽  
Enormous Amount ◽  
Software Skills

Big data refers to enormous amount of information which may be in planned and unplanned form. The huge capacity of data creates impracticable situation to handle with conventional database and traditional software skills. Thousands of servers are needed for its processing purpose. Big data gathers and examines huge capacity of data from various resources to determine exceptional novel awareness and recognizing the technical and commercial circumstances. However, big data discloses the endeavor to several data safety threats. Various challenges are there to maintain the privacy and security in big data. Protection of confidential and susceptible data from attackers is a vital issue. Therefore, the goal of this chapter is to discuss how to maintain security in big data to keep your organization robust, operational, flexible, and high performance, preserving its digital transformation and obtaining the complete benefit of big data, which is safe and secure.

Intranet Exploitation of Social Network Knowledge Intelligence

2017 ◽  
pp. 273-298
Author(s):  
Mark Alan Underwood
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Social Network ◽  
Life Cycle ◽  
Online Social Networks ◽  
Intelligent Agents ◽  
Process Mining ◽  
Just In Time ◽  
Domain Specific ◽  
Social Graphs

Intranets are almost as old as the concept of a web site. More than twenty-five years ago the text Business Data Communications closed with a discussion of intranets (Stallings, 1990). Underlying technology improvements in intranets have been incremental; intranets were never seen as killer developments. Yet the popularity of Online Social Networks (OSNs) has led to increased interest in the part OSNs play – or could play – in using intranets to foster knowledge management. This chapter reviews research into how social graphs for an enterprise, team or other collaboration group interacts with the ways intranets have been used to display, collect, curate and disseminate information over the knowledge life cycle. Future roles that OSN-aware intranets could play in emerging technologies, such as process mining, elicitation methods, domain-specific intelligent agents, big data, and just-in-time learning are examined.

scholarly journals Handling big data of online social networks on a small machine

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Ming Jia ◽  
Hualiang Xu ◽  
Jingwen Wang ◽  
Yiqi Bai ◽  
Benyuan Liu ◽  
...  
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Online Social Networks ◽  
Small Machine

scholarly journals Security and Privacy Issues of Big Data

2019 ◽  
pp. 375-407
Author(s):  
José Moura ◽  
Carlos Serrão
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Personal Data ◽  
Security And Privacy ◽  
Data Systems ◽  
Computing Systems ◽  
Big Data Applications ◽  
Big Data Systems ◽  
Privacy Issues

This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.

Protecting a new Achilles heel: the role of auditors within the practice of data protection

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matteo La Torre ◽  
Vida Lucia Botes ◽  
John Dumay ◽  
Elza Odendaal
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Data Security ◽  
Security And Privacy ◽  
Legal Responsibility ◽  
Future Research ◽  
Content Type ◽  
Privacy Concerns ◽  
Digital Ecosystem

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications This paper provides auditing standard setters and practitioners with insights into the redefinitions of auditing practices in the era of Big Data. Social implications 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. Originality/value 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.

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