Big data privacy concerns require a comprehensive review of existing mechanisms and recent techniques, with a focus on healthcare applications.

Big data privacy: a technological perspective and review

This study provides a four-dimensional framework for analyzing and designing privacy-preserving big data analytics approaches, identifying opportunities and challenges for businesses to effectively leverage big data for sustainable innovation and growth.

Privacy preserving big data analytics: A critical analysis of state‐of‐the‐art

This paper reviews various privacy preservation techniques in Big Data applications, highlighting the need for efficient solutions and models to minimize privacy violations and improve efficiency in Big Data projects.

Privacy Prevention of Big Data Applications: A Systematic Literature Review

Big data analytics limits privacy self-management, and acknowledging the collective dimension of privacy could provide more meaningful alternatives for protection.

Big data analytics and the limits of privacy self-management

Big data-driven privacy and security face new challenges and require new policies, technologies, and tools for protecting privacy in the modern age.

Privacy and security in the big data paradigm

Big data privacy preservation mechanisms need improvement, as they face challenges in data generation, storage, and processing, and require future research directions.

Protection of Big Data Privacy

Big data privacy requires a shift from definitions to models, considering the datafication model, where new personal information is deduced from predictive analytics on already-gathered data without consent.

Big data privacy: The datafication of personal information

Big data and privacy goals conflict, posing potential privacy concerns in areas like unevenness in data, reputation monitoring systems, and social media inferrability.

Big Data and Privacy: Emerging Issues

Big data systems pose serious privacy concerns, and implementing measures to strengthen user privacy can improve the effectiveness of business intelligence and predictive analysis.

Understanding Privacy Violations in Big Data Systems

Big data life cycle presents security and privacy challenges, requiring a security taxonomy to address threats and issues in each phase.

Security and Privacy in Big Data Life Cycle: A Survey and Open Challenges

Privacy-preserving data mining and analytics in Big Data aims to extract useful insights while safeguarding personal data, balancing data value and privacy concerns.

Privacy-Preserving Data Mining and Analytics in Big Data

Big Data presents various privacy challenges, including data collection, storage, and processing, but its use can benefit various applications and organizations.

Privacy issues in big data

Recent advances in data encryption, privacy preservation, and trust management show promise for securing big data platforms and addressing diverse challenges.

Security and Privacy for Big Data

Big data security and privacy challenges are increasing, but this paper presents methods and techniques to ensure their protection.

Big Data Security and Privacy Issues

The proposed privacy preservation model, based on aggregate query answers, effectively balances data utility and privacy in big data analytics, making it more efficient and effective.

Privacy-Enhancing Data Aggregation for Big Data Analytics

Big Data Analytics offers immense benefits but also presents security and privacy risks, requiring strong protection techniques to enable benefits without risking privacy.

Big Data Analytics: Security and privacy challenges

Privacy by design in big data analytics can be achieved by integrating privacy and data protection safeguards into the analytics value chain, addressing privacy concerns and promoting user empowerment and control.

Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics

Big data privacy and security research is gaining momentum, with various models, techniques, and algorithms proposed to address current challenges and future research directions.

Privacy and Security of Big Data: Current Challenges and Future Research Perspectives

Big data management has enhanced customer insights and growth, but security and privacy concerns remain a challenge, requiring ongoing research to address these issues.

Big data management: Security and privacy concerns

Big data analytics can help identify and neutralize cyber attacks by analyzing large amounts of data from various sources, but companies must ensure privacy and security before implementing it.

Big data analytics for security and privacy challenges

What is the Privacy issues in big data analytics?

These studies suggest that big data analytics presents significant privacy issues, including the need for improved privacy preservation mechanisms, new policies and technologies, and a comprehensive review of existing techniques, particularly in healthcare and business applications.