Abstract
Digital information plays an essential role in supporting organizational business. However, incidents of sensitive information leakage often happen in organization environment. Therefore, risk analysis needs to be performed to recognize the impact of information security threat in organization. In order to carry out those risk analyses, risk model is needed to map risk of information security threat. The selection of proper risk model provides proper result related to risk analysis. The proper risk model must have objectivity and appropriate context. However, most of the existing risk models focus on the technical approach and use expert judgment as a weighting method. Meanwhile, organizations use business perspectives to determine decisions. Therefore, this study has the objective to fill the needs of organizations by developing a new risk model. The proposed risk model focuses on business aspects involvement and reducing subjective methods. The proposed risk model also uses three processes to result output, i.e., adaptable classification data, data measurement and cross-label analysis. Test mining and categorical clustering are involved to handle those three processes. Testing of the proposed model is carried out to define ability and limitation of model by involving 30 targets. The result states that the proposed model has advantages in objectivity, context approach and detailed output, while the limited scope of work becomes weakness of these models.









Similar content being viewed by others
References
Simorjay, F.: Data classification for cloud readiness (2014)
Li, G., Sheng Dai, J., Mi Park, E., Taek Park, S.: A study on the service and trend of Fintech security based on text-mining: focused on the data of Korean online news. J. Comput. Virol. Hack. Tech. 13(4), 249–255 (2017)
Security Industry Association: Data Privacy and Security Trends for 2018. Technical report, Security Industry Association (2018)
Verizon. 2017 Data Breach Investigations Report. Technical Report (2017)
Ponemon Institute LLC. The Impact of Data Breaches on Reputation & Share Value. Technical Report May (2017)
Kaspersky Lab ZAO, Global Corporate IT Security Risks: 2013. Technical Report May, Kaspersky (2013)
PWC. US Cybercrime: Rising Key Findings from the 2014 US State of Cybercrime Survey. PWC, July, p. 21 (2014)
Marotta, A., Martinelli, F., Nanni, S., Orlando, A., Yautsiukhin, A.: Cyber-insurance survey. Comput. Sci. Rev. 24, 35–61 (2017)
Goldstein, A., Frank, U.: Components of a Multi-perspective Modeling Method for Designing and Managing IT Security Systems. Information Systems and e-Business Management, vol. 14, pp. 101–140. Springer, Berlin (2015)
Keramati, M., Keramati, M.: Novel Security Metrics for Ranking Vulnerabilities in Computer Networks. In: 7th International Symposium on Telecommunications (IST’2014), pp. 883–888 (2014)
Ahmed, R.K.A.: Overview of security metrics. Softw. Eng. 4(4), 59–64 (2016)
Cheng, L., Liu, F., Daphne Yao, D.: Enterprise data breach: causes, challenges, prevention, and future directions. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 7(5), 1–14 (2017)
Chivers, H., Clark, J.A., Cheng, P.C.: Risk profiles and distributed risk assessment. Comput. Secur. 28(7), 521–535 (2009)
Suhartana, M., Pardamean, B., Soewito, B.: Modeling of risk factors in determining network security level. Int. J. Secur. Appl. 8(3), 193–208 (2014)
Jouini, M., Rabai, L.B.A., Aissa, A.B.: Classification of security threats in information systems. Procedia Comput. Sci. 32, 489–496 (2014)
Ghani, H., Luna, J., Suri, N.: Quantitative assessment of software vulnerabilities based on economic-driven security metrics. In: 2013 International Conference on Risks and Security of Internet and Systems (CRiSIS), pp. 1–8 (2013)
Filipe, M., da Silva, M.M.: Comparative Study of Information Security Risk Assessment Models. Instituto Superior Técnico, Universidade Técnica de Lisboa, pp. 1–11
Ponemon Institute LLC. Reputation Impact of a Data Breach. Technical Report November, Ponemon Institute LLC (2011)
Ghani, H., Khelil, A., Suri, N., Csertan, G., Gonczy, L., Urbanics, G., Clarke, J.: Assessing the security of internet connected critical infrastructures (The CoMiFin Project Approach). Secur. Commun. Netw. 7(12), 2713–2725 (2014)
Chang, S.E., Ho, C.B.: Organizational factors to the effectiveness of implementing information security management. Ind. Manag. Data Syst. 106(3), 345–361 (2006)
Ruivo, P., Santos, V., Oliveira, T.: Data protection in services and support roles—a qualitative research amongst ICT professionals. Procedia Technol. 16, 710–717 (2014)
Hart, M., Manadhata, P., Johnson, R.: Text classification for data loss prevention. In: Privacy Enhancing Technologies, pp. 18–37 (2011)
Hauer, B.: Data and information leakage prevention within the scope of information security. IEEE Access 3, 2554–2565 (2015)
Sajko, M., Rabuzin, K., Bača, M.: How to calculate information value for effective security risk assessment. J. Inf. Organ. Sci. 30(2), 263–278 (2006)
Shi, X., Li, D., Zhu, H., Zhang, W.: Research on supply chain information classification based on information value and information sensitivity, vol. 7 (2007)
Ashwin Kumar, T.K., Liu, H., Thomas, J.P., Mylavarapu, G.: Identifying sensitive data items within hadoop. In: Proceedings of2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, pp. 1308–1313 (2015)
Rao, D., Keong Ng, W.: A user-centric approach to pricing information. In: Proceedings of 2016 IEEE 2nd International Conference on Big Data Computing Service and Applications, BigDataService 2016, pp. 202–209 (2016)
OWASP. OWASP Risk Rating Methodology (2015)
Scambray, J., Olson, E.: Improving Web Application Security. Microsoft Corporation (2003)
FIRST. Common Vulnerability Scoring System v3.0: Specification Document (2015)
Alpcan, T., Bambos, N.: Modeling dependencies in security risk management. In: 2009 Fourth International Conference on Risks and Security of Internet and Systems (CRiSIS 2009), pp. 113–116 (2009)
Tamjidyamcholo, A., Sapiyan Bin, M., Tamjid Yamchello, H., Gholipour, R.: Application of fuzzy set theory to evaluate the rate of aggregative risk in information security. In: 3rd International Conference on Research and Innovation in Information Systems—2013 (ICRIIS’13), vol. 2013, pp. 410–415 (2013)
Tianshui, W., Gang, Z.: A new security and privacy risk assessment model for information system considering influence relation of risk elements. In: Proceedings—2014 9th International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2014, pp. 233–238 (2015)
El-attar, N.E, Awad, W.A., Omara, F.A.: Empirical assessment for security risk and availability in public cloud frameworks. In: 11th International Conference on Computer Engineering & Systems (ICCES), pp. 17–25. IEEE Conference Publications (2016)
Nugroho, L.E., Santosa, P.I.: An approach for risk estimation in information security using text mining and Jaccard method. Bull. Electr. Eng. Inform. 7(3), 393–399 (2018)
Ibnugraha, P.D., Nugroho, L.E., Santosa, P.I.: Metrics analysis of risk profile: a perspective on business aspects. In: International Conference on Information and Communications Technology (ICOIACT), pp. 275–279. IEEE Conference Publications (2018)
Fonseca, J., Seixas, N., Vieira, M., Madeira, H.: Analysis of field data on web security vulnerabilities. IEEE Trans. Dependable Secure Comput. 11(2), 89–100 (2014)
Elavarasan, D., Vincent, D.: Effective mining approach to produce quality search results using proposed approach. Int. J. Intell. Eng. Syst. 10(3), 435–443 (2017)
Krishna Ravinuthala, V.V.M., Reddy Chinnam, S.: A keyword extraction approach for single document extractive summarization based on topic centrality. Int. J. Intell. Eng. Syst. 10(5), 153–161 (2017)
Shubhamangala, B.R., Saha Snehanshu, P.D.: Application security risk: assessment and modeling. ISACA J. 2, 37 (2016)
Gonzalez Granadillo, G.D., Rubio Hernan, J., Garcia Alfaro, J.: Using an event data taxonomy to represent the impact of cyber events as geometrical instances. IEEE Access 6, 8810–8828 (2017)
Abdul Razak, D., Asri Abdullah, M., Ersoy, A.: Small medium enterprises (SMES) in turkey and malaysia a comparative discussion on issues and challenges. Int. J. Bus. Econ. Law 15(3), 1–10 (2018)
Seidel-Sterzik, H., McLaren, S., Garnevska, E.: Effective life cycle management in SMEs: use of a sector-based approach to overcome barriers. Sustainability (Switzerland) 10(2), 1–22 (2018)
Clark, A., Tan, T.T., Barbee, C., Donker, J., Palmer, A., Skramstad, E.: Threats to the Financial Services Sector: Financial Services Sector Analysis of PwC’s: Global Economic Crime Survey, p. 2014. Technical Report, PWC (2014)
Nickolov, E.: Critical information infrastructure protection: analysis, evaluation and expectations. Inf. Secur. 17(May), 105–119 (2005)
Shah, S., Mehtre, B.M.: An overview of vulnerability assessment and penetration testing techniques. J. Comput. Virol. Hack. Tech. 11(1), 27–49 (2015)
Cho, Y., Pan, J.: Design and implementation of website information disclosure assessment system. PLoS ONE 10(3), 1–29 (2015)
Amir, S., Mortazavi, R.: A checklist based evaluation framework to measure risk of information security management systems. Int. J. Inf. Technol. 11(3), 517–534 (2019)
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ibnugraha, P.D., Nugroho, L.E. & Santosa, P.I. Risk model development for information security in organization environment based on business perspectives. Int. J. Inf. Secur. 20, 113–126 (2021). https://doi.org/10.1007/s10207-020-00495-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10207-020-00495-7