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International Conference on Data Privacy and Big Data Systems

📅 15–16 May 2027 📍 Antalya, Turkey 👤 Standard / Listener

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$165

virtual · $165 in person

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Official invitation letterIssued automatically after registration

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Certificate & digital materialsCertificate, slides and resource materials

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Supporting global researchConnect with researchers across 30+ countries

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Conference session tracks

Key research areas covered across the sessions — tap a track to read more.

This track focuses on the latest innovations in technologies aimed at enhancing data privacy. It will explore encryption methods, secure data sharing techniques, and privacy-preserving algorithms.

This session will delve into frameworks and strategies for effective data governance in the context of big data. Discussions will include compliance with privacy regulations and the role of governance in risk management.

This track examines the intersection of artificial intelligence and data privacy, highlighting AI-driven solutions for privacy compliance. It will cover machine learning techniques that enhance data protection and user privacy.

This session will explore the role of predictive analytics in enhancing data security measures. It will discuss how predictive models can identify vulnerabilities and mitigate risks in big data systems.

This track focuses on the development of intelligent systems that facilitate seamless data integration while ensuring privacy. It will highlight techniques that balance data accessibility with security concerns.

This session will discuss the design and implementation of privacy frameworks tailored for big data environments. It will address challenges and best practices in maintaining data privacy across diverse systems.

This track will explore architectural approaches to building secure systems that handle big data. It will emphasize the importance of security design principles in safeguarding sensitive information.

This session will focus on effective risk management strategies that address data privacy concerns in big data systems. It will cover methodologies for assessing and mitigating privacy risks.

This track will investigate the application of machine learning techniques in enhancing data privacy. It will cover topics such as anomaly detection and privacy-preserving data mining.

This session will address the unique challenges of ensuring data security and privacy in cloud computing environments. It will explore strategies for protecting data in transit and at rest.

This track will examine the ethical implications of big data practices on privacy. It will encourage discussions on responsible data usage and the societal impact of data-driven decisions.