Andrew M'manga, Shamal Faily, J. McAlaney, Christopher Williams
{"title":"System design considerations for risk perception","authors":"Andrew M'manga, Shamal Faily, J. McAlaney, Christopher Williams","doi":"10.1109/RCIS.2017.7956554","DOIUrl":null,"url":null,"abstract":"The perception of risk is a driver for security analysts' decision making. However, security analysts may have conflicting views of a risk based on personal, system and environmental factors. This difference in perception and opinion, may impact effective decision making. In this paper, we propose a model that highlights areas contributing to the perception of risk in a socio-technical environment and their implication to system design. We validate the model through the use of a hypothetical scenario, which is grounded in both the literature and empirical data.","PeriodicalId":193156,"journal":{"name":"2017 11th International Conference on Research Challenges in Information Science (RCIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 11th International Conference on Research Challenges in Information Science (RCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCIS.2017.7956554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The perception of risk is a driver for security analysts' decision making. However, security analysts may have conflicting views of a risk based on personal, system and environmental factors. This difference in perception and opinion, may impact effective decision making. In this paper, we propose a model that highlights areas contributing to the perception of risk in a socio-technical environment and their implication to system design. We validate the model through the use of a hypothetical scenario, which is grounded in both the literature and empirical data.