ICDIS-2022: The 4th International Conference on Data Intelligence and Security Sheraton Shenzhen Nanshan Shenzhen, China, July 25-27, 2022 |
Conference website | http://www.icdis.org |
Submission link | https://easychair.org/conferences/?conf=icdis2022 |
Important: The conference date of ICDIS 2022 has been changed to August 24-26, 2022.
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 4th International Conference on Data Intelligence and Security (ICDIS-2022) aims to: (1) provide a unique forum where data intelligence and data security are all involved; (2) provide a forum for researchers, experts, professionals and stakeholders in related fields to disseminate their recent advances and share their views on future perspectives.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
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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.
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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.
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Important Dates
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====== The first round ======
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Paper Submission Deadline: Feburary 28, 2022
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Notification to Authors (Accept/Reject): April 15, 2022
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Deadline for camera-ready copies: May 15, 2022
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====== The second round ======
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Paper Submission Deadline: April 15, 2022
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Notification to Authors (Accept/Reject): June 1, 2022
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Deadline for camera-ready copies: July 1, 2022
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Deadline for Special Session Proposals: March 15, 2022
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Conference date: August 24- 26, 2022
List of Topics
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1. Data intelligence in security and privacy- Intrusion detection- Anomaly detection- Fraud detection- Defense against Malicious codes- Defense against denial of service attacks- Network security- System security- Biometrics- Deep learning- Unsupervised learning and clustering- Supervised learning and classification- Reinforcement learning- Data mining- Robust and dyanmic optimtization- Visualization and analysis- Immune computation
2. Security and privacy in data intelligence- Federated learning- Swarm learning- Poisoning attack and defense - Evasion attacks and defense - Adversarial examples- Model inversion- AI backdoors- Membership inference attacks - Digital watermarking for AI models- Privacy-preserving machine learning- Privacy-preserving data mining- Privacy-preserving data publishing- Secure model processing platforms- Security and privacy in social networks- Interpretability of machine learning models for secure machine learning- Secure machine learning- Secure cloud computing- Secure multi-party computation- Data privacy- Sensitive data collection- AI fariness- AI trust- AI ethics- Blockchain
Contact
Yang Liu, Harbin Institute of Technology, Shenzhen, ChinaEmail: liu.yang@hit.edu.cn, Tel: 0086-0755-26416570