Guest Editors
Prof. Xingsi Xue, Fujian University of Technology, China.
Prof. Jeng-Shyang Pan, Shandong University of Science and Technology, China.
Dr. Pei-Wei Tsai, Swinburne University of Technology, Australia.
Summary
In our rapidly advancing digital age, we continuously generate a staggering amount of data spanning across various sectors such as healthcare, finance, marketing, education, and government. The advent of big data has yielded both opportunities and challenges, positioning data mining at the core of deriving valuable insights and facilitating data-driven decisions. With its intricate algorithms, data mining has the capability of revealing essential patterns, associations, and knowledge hidden within large and complex datasets. Nevertheless, these extracted insights often necessitate sophisticated computational intelligence techniques to interpret and understand. Techniques like artificial neural systems, swarm intelligence, and evolutionary programming, among others, have become vital in deciphering the knowledge unveiled by data mining and optimizing its algorithms for efficiency and accuracy. Moreover, in our interconnected world, data security holds paramount importance. Data mining, which often involves accessing and analyzing sensitive information, presents numerous challenges relating to information security, such as data privacy, cryptography, secure data sharing, and system integrity. The development of robust solutions to tackle these issues is an ongoing endeavor in the realm of data mining.
The proposed special issue aims to shed light on recent developments and findings in these closely related domains. By offering a platform for expert researchers, scholars, and practitioners from computational intelligence, information security, and data mining to share their latest findings, we hope to encourage cross-disciplinary dialogue and stimulate innovative approaches. Through this convergence of expertise, we aim to expedite the development of more secure, efficient, and intelligent data mining systems, thus contributing to the progression of this critical field. Essentially, the proposed special issue strives to depict not only the state-of-the-art in data mining, computational intelligence, and information security, but also to chart the trajectory for future research directions and applications.
The potential topics include but are not limited to:
1. Computational Intelligence in Data Mining
(1) Novel data mining algorithms based on Artificial Neural Systems, Evolutionary Programming, and Bayesian Learning
(2) Autonomy-oriented computing for data mining
(3) Application of Reinforcement Learning and Supervised Learning in data mining
(4) Intelligent systems for data mining
(5) Integration of Swarm Intelligence and Multi-agent systems in data mining
(6) Bio-inspired computing methods such as Artificial Immune Systems, DNA Computing, and Biological Computing in data mining
(7) Use of Particle Swarm Optimization, Multi-Objective EA, and other evolutionary algorithms in data mining
(8) Knowledge Discovery techniques for complex datasets
(9) Information Security in Data Mining
2. Cryptography and coding techniques for secure data mining
(1) Data Privacy and Information hiding in data mining
(2) Authentication and Authorization in data mining processes
(3) Security management and Internet/Intranet Security in data mining
(4) Mobile Communications Security and Network & Wireless Security for data mining
(5) Cryptanalysis and Public Key Infrastructure in data mining
(6) Applications of Data Mining
3. Biometrics and Digital Signatures applications in data mining
(1) Database Security and System Security in data mining applications
(2) Financial Security and Electronic Commerce Security in data mining
(3) Application of data mining in Statistical Data Analysis and Detection of Abnormality
(4) Web Privacy, Web Authentication, and Web Security and Integrity in data mining applications
We invite high-quality original research papers as well as review articles. Submissions will undergo a rigorous review process to assess their novelty, significance to the field, and technical quality.
Keywords
Data Mining
Computational Intelligence
Intelligent Systems
Information Security
Knowledge Engineering
Published Papers
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