In an extremely fast development of technology era, we are now living in the age of Industry 4.0, the age of realizing Cyber Physical System (CPS). The virtual space being realized by digital space concept will completely merge with our physical dimension in a very near future. Every smart ecosystem could make us more convenient to live. However, this technology could be a severe weapon which is able to damage our life, our assets, organization security, and national sovereignty and could affect the extinction of human kind. We strongly realize this concern and are proposing one of the solutions to secure our life in the next smart world, the Holistic Framework of Using Machine Learning for an Effective Incoming Cyber Threats Detection. We present an effective holistic framework which is easy to understand, easy to follow, and easy to implement a system to protect our digital space in an initial state. This approach describes all steps with the significant modules (I-D-A-R: Idea-Dataset-Algorithm-Result Framework with B-L-P-A: Brain-Learning-Planning-Action concept) and explains all major concern issues for developers. As a result of the I-D-A-R framework, we provide an important key success factor of each state. Finally, a comparison of detection accuracy between using Multinomial Naïve Bayes, Support Vector Machine (SVM) and Deep Learning algorithm, and the application of the feature engineering techniques between Principle Component Analysis (PCA) and Standard Deviation successfully show that we can reduce the computation time by using the proper algorithm that matches with each dataset characteristics while all prediction results still promising.
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