Dauda Adenusi, B. K. Alese, B. Kuboye, A. Thompson
{"title":"网络态势感知模型的开发","authors":"Dauda Adenusi, B. K. Alese, B. Kuboye, A. Thompson","doi":"10.1109/CyberSA.2015.7166135","DOIUrl":null,"url":null,"abstract":"This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.","PeriodicalId":432356,"journal":{"name":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Development of cyber situation awareness model\",\"authors\":\"Dauda Adenusi, B. K. Alese, B. Kuboye, A. Thompson\",\"doi\":\"10.1109/CyberSA.2015.7166135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.\",\"PeriodicalId\":432356,\"journal\":{\"name\":\"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberSA.2015.7166135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberSA.2015.7166135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.