Hybrid Conferencee

International Conference on Data Privacy and Big Data Systems (ICDPBDS - 26)

10th - 11th October 2026 | Los Angeles, USA

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Call for Papers Extended:
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Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
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Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Los Angeles conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Los Angeles, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Los Angeles."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 9
SDG 9 Industry, Innovation and Infrastructure
SDG 16
SDG 16 Peace, Justice and Strong Institutions
Track 01

Advancements in Data Privacy Technologies

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.

Track 02

Big Data Governance and Compliance

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.

Track 03

AI-Driven Privacy Solutions

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.

Track 04

Predictive Analytics and Data Security

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.

Track 05

Intelligent Systems for Data Integration

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.

Track 06

Privacy Frameworks in Big Data Environments

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.

Track 07

Secure Systems Architecture for Big Data

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.

Track 08

Risk Management Strategies in Data Privacy

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.

Track 09

Machine Learning for Enhanced Data Privacy

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.

Track 10

Data Security in Cloud Computing Environments

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.

Track 11

Ethical Considerations in Big Data and Privacy

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.