International Conference on Blockchain-Driven Anomaly Detection in Big Data Security
(ICBDAD - 27)

5th - 6th April 2027 London, UK (Hybrid Event)

Call for Paper

The ICBDAD is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Blockchain, Cybersecurity, Big Data, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Anomaly detection techniques using blockchain
  • Blockchain for enhancing security analytics
  • Real-time anomaly detection in big data
  • Machine learning and blockchain for security
  • Challenges in blockchain-driven anomaly detection
  • Decentralized anomaly detection systems
  • Blockchain's role in threat detection
  • Case studies on anomaly detection applications
  • Integrating blockchain with existing security tools
  • Blockchain for data integrity verification
  • Automating anomaly detection with smart contracts
  • Impact of blockchain on security monitoring
  • Blockchain for insider threat detection
  • Future directions in anomaly detection research
  • Collaborative anomaly detection using blockchain
  • Blockchain and predictive security analytics
  • Best practices for blockchain anomaly detection
  • Blockchain's role in incident prediction
  • Scalability of blockchain anomaly detection systems
  • Blockchain for enhancing data visibility
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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