Guest Editors
Dr. Yi Sun
Email: sybupt@bupt.edu.cn
Affiliation: School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing, 100876, China
Homepage:
Research Interests: information security, data security, cyber security, privacy-enhancing technology
Dr. Limei Peng
Email: auroraplm@knu.ac.kr
Affiliation: School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea
Homepage:
Research Interests: cloud/edge computing, wireless communications, IoT, data security
Summary
Privacy-enhancing technologies, which are digital solutions that allow information to be collected, processed, analyzed, and shared while protecting data confidentiality and privacy, enable organizations to conduct joint data analysis in a privacy-friendly manner. The true power of privacy-enhancing technology is in keeping data "hidden" from researchers while at the same time enabling analysis of that data. The technologies could unlock new forms of collaboration and new norms in the responsible use of personal data. They may enable more collaboration across entities, sectors, and borders to help tackle shared challenges, helping drive solutions in areas such as health care, climate change, financial crime, human trafficking, and pandemic response.
Privacy-enhancing technologies offer several specific techniques to enhance privacy. Encryption techniques transform data into unreadable formats, ensuring that only authorized parties can access and decrypt the information. Anonymization methods remove personally identifiable information from datasets, making it challenging to identify specific individuals. Differential privacy techniques introduce noise or randomness to data analysis, preventing the identification of individual records.
Therefore, this special issue focuses on Privacy-Enhancing Technologies of Data Secure Cooperation and Circulation. The following subtopics are the particular interests of this special issue, including but not limited to:
· AI for enhanced data privacy
· Cybersecurity in visual data protection
· Image security
· Challenges in balancing privacy and data utility
· Data encryption and decryption
· Cybersecurity for privacy-preserving data ecosystems
· Privacy-preserving big data management
· Synthetic data generation and security
· Privacy-preserving techniques in data security
· Data anonymization
· Differential privacy theory & applications
· Federated learning for data security
Keywords
AI, image encryption, data management, CNN/RNN, industrial IoT, cyber security, industrial IoT
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