WIT Press


Development And Applications Of A Multiple Risk Communicator

Price

Free (open access)

Paper DOI

10.2495/RISK080251

Volume

39

Pages

9

Page Range

241 - 249

Published

2008

Size

798 kb

Author(s)

R. Sasaki, Y. Hidaka, T. Moriya, M. Taniyama, H. Yajima, K. Yaegashi, Y. Kawashima & H. Yoshiura

Abstract

Development and applications of a multiple risk communicator R. Sasaki1,2, Y. Hidaka3, T. Moriya1, M. Taniyama1, H. Yajima1,2, K. Yaegashi4, Y. Kawashima5 & H. Yoshiura2,6 1Tokyo Denki University, Tokyo, Japan 2RISTEX of the Japan Science and Technology Agency, Tokyo, Japan 3IT DORAKU RESEARCH LAB. Ltd, Tokyo, Japan 4Pinpoint Service, Inc, Tokyo, Japan 5AdIn Research, Inc, Tokyo, Japan 6University of Electro-Communications, Tokyo, Japan Abstract Businesses and society face various risks, and measures to reduce one risk often cause another risk. Thus, obtaining the optimal combination of measures to reduce one risk while considering other risks has become a major issue. Because risk decisions involve multiple participants, such as a manager, customer, and employee, communication between all decision makers is important for reaching an agreement on the necessary risk measures. Moreover, due to opposing factors such as security, privacy, and development cost, it is not always easy to find the optimal combination of measures that reduce the risk and are agreeable to all decision makers. Therefore, this situation would benefit from the development of a \“multiple risk communicator” (MRC) with the following functions: (1) a model of the support role of the risk specialist, (2) an optimization engine, and (3) a display of the computed results for viewing by the decision makers. In this paper, we propose a design for developing the MRC program and present an example implementation. Then, we apply the results to problems of personal information leakage, illegal copying, and internal control. Keywords: security, privacy, risk, risk communication, discrete optimization.

Keywords

security, privacy, risk, risk communication, discrete optimization.