Privacy protection has recently attracted the attention of both academics and industries . Society protects individual data privacy through complex legal frameworks. This has become a topic of interest with the increasing applications of data science and artificial intelligence that have created a higher demand to the ubiquitous application of the data. The privacy protection of the broad Data-InformationKnowledge-Wisdom (DIKW) landscape, the next generation of URLanization, has not been in the limelight. Next , we will explore DIKW architecture through the applications of  popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will look at it from a DIKW domain perspective. Swarm Intelligence could effectively optimize and reduce the number of items in DIKW used in differential privacy, this way accelerating both the effectiveness and the efficiency of differential privacy for crossing multiple modals of conceptual DIKW. The proposed approach is proved through the application of personalized data that is based on the open-sourse IRIS dataset. This experiment demonstrates the efficiency of Swarm Intelligence in reducing computing complexity.
Privacy protection has recently been in the spotlight of attention to both academia and industry . Society protects individual data privacy through complex legal frameworks. The increasing number of applications of data science and artificial intelligence has resulted in a higher demand for the ubiquitous application of the data. The privacy protection of the broad Data-Information-Knowledge-Wisdom (DIKW) landscape, the next generation of URLanization, has taken a secondary role. In this paper , we will explore DIKW architecture through the applications of the popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will look at it from a DIKW domain perspective. Swarm Intelligence can effectively optimize and reduce the number of items in DIKW used in differential privacy, thus accelerating both the effectiveness and the efficiency of differential privacy for crossing multiple modals of conceptual DIKW. The proposed approach is demonstrated through the application of personalized data that is based on the open-sourse IRIS dataset. This experiment demonstrates the efficiency of Swarm Intelligence in reducing computing complexity.
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