Proposals for knowledge driven and data driven applications in security systems

Abstract

The topic of the presented research is contemporary threats leading to serious problems in the nearest future. Advantages and disadvantages of typical synthetic advanced analytics methods are investigated, and obstacles are revealed to their distribution in IT, especially in security systems (SS). Security education issues also have been discussed because the high-quality learning inevitably leads to independent research. Original results for juxtaposing statistical versus logical intelligent information processing methods aiming at possible evolutionary fusions are described, and recommendations are made on how to build more effective applications of classical and/or elaborated novel methods: Kaleidoscope, Funnel, Puzzle, and Contradiction. Characteristic peculiarities, advantages, and problems with coordination and control of the investigated group of methods are demonstrated. It is shown that their combination makes possible not only data driven applications, but more complex knowledge guided control of evolutionary computing using nonstandard sets of constraints. The focus is mainly on advanced analytics applications named Puzzle methods and their interactions with other described methods. It is studied aiming at collaborative statistical and logical research based on quantitative method applications, deep processing and effective management of accumulated knowledge. It is shown that applications of intelligent technologies advance the efficiency of statistical applications by using original set of evolutionary methods for data and knowledge fusion. It is shown that all the demonstrated advantages may be successfully combined with well-known methods from big data, advanced analytics, knowledge discovery, data/web/deep data mining or other modern fields. Also, it is shown how the considered applications enhance the quality of statistical inference, reveal the reasons of its effective use, improve the human-machine interaction between the user and system and hence serve the process of gradual but a sustainable improvement of the results. The usage of ontologies is investigated with the purpose of information transfer by a sense in security multiagent environments or to reduce the computational complexity of practical applications. Applications from many fields using the same set of methods have been displayed aiming to show the strength of the domain independent part of the research.