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Aim and Scope

Data intelligence and data security are two closely related views. In the era of big data, both data intelligence and data security are very important, and present constant challenges for both academia and industry. Those challenges bring with great opportunities for innovative ideas, tools and technologies.


The 6th International Conference on Data Intelligence and Security (ICDIS 2024) is oriented to:


  • provide a unique forum where data intelligence and data security are all involved;

  • provide a forum for researchers, experts, professionals and stakeholders in related fields to disseminate their recent advances and share their visions.


The topics of ICDIS-2024 include two aspects. First, contributions on data intelligence in security and privacy are welcome, including works on how to learn from data and how to intelligently process data for security and privacy applications. Second, contributions on security and privacy in data intelligence are always within the scope of the conference, including works on making data intelligence models secure and trusted.

Particularly, the topics of interest include but are not limited to:

Topic 1: Data Intelligence in Security and Privacy

  • Security

    • Data Analysis and –Mining​

    • Intrusion-, Anomaly-, and Fraud Detection ​

    • Deterministic & Probabilistic Security​

    • Educational Data Mining​

    • Visualization: Analysis and Perception ​

  • Machine Learning​

    • Deep-, Supervised- & Unsupervised-, Reinforcement-, and Distributed Learning​

    • Generative AI, Natural Language Processing, Large Language Models ​

  • Network & Computer Security ​

    • Network & Protocol Security​

    • Host Security | Processor Security​

    • Wireless Security, Security in Beyond 5G & 6G​

    • Control-Flow integrity and Memory Security

Topic 2 – Security & Privacy in Data Intelligence​

  • Privacy ​

    • Data Privacy​

    • Sensitive Data Collection​

    • Privacy Preserving Data Mining​

    • Attacks on Data Intelligence​

    • Biometrics​

  • Trustworthy AI & Trusted AI ​

    • Privacy Preserving Machine Learning​

    • Federated Learning, Swarm Learning​

    • Attacks on Privacy Preserving Data Intelligence​

    • AI Fairness​

    • Digital Watermarking for AI & AI backdoors ​

  • Cyber Security ​

    • Secure Cloud Environments​

    • Physical Security Convergences​

    • Critical Infrastructures

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