Advanced Modeling and Optimization Techniques for Big Data

Dear Colleagues,

The rapid proliferation of big data across various sectors has challenged traditional modeling and optimization methods, which often fall short in addressing large-scale, heterogeneous, uncertain, and real-time data environments. This highlights the urgent need for advanced modeling and optimization techniques that can efficiently extract value from large datasets while ensuring system trustworthiness, security, and cryptographic robustness.

This Special Issue seeks to bring together state-of-the-art research in multi-objective optimization, intelligent computing, trustworthy computing, cybersecurity, and cryptography. Emphasis will be placed on privacy-preserving data analysis, scalable optimization algorithms, online and streaming modeling approaches, and the practical integration of cryptographic methods in applications such as intelligent manufacturing, financial analytics, the Internet of Things, and secure communications.

We invite original research articles, reviews, and case studies that explore theoretical advances, algorithmic innovations, and practical deployments. The goal of this Special Issue is to foster interdisciplinary collaboration and drive the development of secure, reliable, and cryptographically enhanced big data modeling and optimization techniques.

Dr. Jiangjiang Zhang
Guest Editor

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