It is of great value for security departments to put forward an effective plan to combat pseudo-base-stations.Intelligent analysis tools and effective decision-making mechanism are important but still lacking,so this kind of analysis and decision-making is still a huge challenge.Due to the spam message data available for decision-making is discrete and random from an intuitive point of view,we can not directly explore its regularity with the change of time and space dimensions.In this paper,we propose an interactive visualization system based on spam message’s location data,time data and content data.Through these three levels,we solve the two main challenges mentioned above:firstly,we explore the relationship between spam message types and spatial-temporal distribution,and visually reveal the temporal,spatial and behavioral correlation patterns of pseudo-base stations;Then,based on the correlation patterns,decision makers can visually formulate different pseudo-base station strike candidate schemes with time preference,space preference or hazard type preference;At the same time,the system designs image characters expressing the impact attributes of recommended paths to support the correction and adjustment of candidate schemes,and adds them to the space of candidate schemes for comparison;Finally,the decision maker visually compares all solutions in the candidate space and makes the final decision.The cooperative display of multi-visualization modules and heuristic interactive exploration designed in this paper enable decision makers to establish interest sets freely according to their preferences and propose targeting candidate solutions.The system provides sufficient decision guidance for decision makers and enhances the rationality and feasibility of the scheme.In addition,the system provides data overview and some suggestions to develop plans to combat pseudo-base stations.
|Translated title of the contribution||Visual Analysis System of Striking Pseudo Base Station|
|Original language||Chinese (Simplified)|
|Place of Publication||CNKI|
|Number of pages||61|
|Publication status||Published - May 2021|
|Publication type||G2 Master's thesis, polytechnic Master's thesis|