Abstract
The article describes an approach to the analysis of changes in the user’s protection level from the social engineering attack actions of malefactor in the case of applying two strategies to increase the level of protection. The first deals with changing information system’s users (dismissal/advanced training), and second is changes in user access policies to critical information stored in such information systems. Numerical experiment is also presented.
The results were partially supported by RFBR, project No. 18-37-00340, and Governmental contract (SPIIRAS) No. 0073-2019-0003.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Azarov, A., Abramov, M., Tulupyev, A., Tulupyeva, T.: Models and algorithms for the information system’s users’ protection level probabilistic estimation. In: Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI 2016), vol. 2, pp. 39–46 (2016)
Azarov, A., Abramov, M., Tulupyeva, T., Tulupyev, A.: Users’ of information system protection analysis from malefactor’s social engineering attacks taking into account malefactor’s competence profile. Biologically Inspired Cognitive Architectures (BICA) for Young Scientists, pp. 25–30 (2016)
Azarov, A., Suvorova, A., Tulupyeva, T.: Changing the information system’s protection level from social engineering attacks, in case of reorganizing the information system’s users’ structure. In: II International Scientific-Practical Conference « Fuzzy Technologies in the Industry » , pp. 56–62 (2018)
Azarov, A., Suvorova, A.: Sustainability of the user’s social network graph to the social engineering attack actions: an approach based on genetic algorithms. In: XXII International Conference on Soft Computing and Measurement (SCM 2018), pp. 126–129 (2018)
D’Innocenzo, L., Mathieu, J., Kukenberger, M.: A meta-analysis of different forms of shared leadership–team performance relations. J. Manag. 42(7), 1964–1991 (2017)
Fang, R., Landis, B., Zhang, Z., Anderson, M., Shaw, J., Kilduff, M.: Integrating personality and social networks: A meta-analysis of personality, network position, and work outcomes in organizations. Organ. Sci. 26(4), 1243–1260 (2015)
Gupta, B., Tewari, A., Jain, A., Agrawal, D.: Fighting against phishing attacks: state of the art and future challenges. Neural Comput. Appl. 28, 3629–3654 (2017)
Huda, A.S.N., Živanović, R.: Accelerated distribution systems reliability evaluation by multilevel Monte Carlo simulation: implementation of two discretisation schemes. IET Gener. Transm. Distrib. 11(13), 3397–3405 (2017)
Kharitonov, N., Maximov, A., Tulupyev, A.: Algebraic Bayesian Networks: The Use of Parallel Computing While Maintaining Various Degrees of Consistency. Stud. Syst. Decis. Control 199, 696–704 (2019)
Kotenko, I., Chechulin, A., Branitskiy, A.: Generation of source data for experiments with network attack detection software. J. Phys: Conf. Ser. 820, 12–33 (2017)
Liu, J., Lyu, Q., Wang, Q., Yu, X.: A digital memories based user authentication scheme with privacy preservation. PLoS ONE 12(11), 0186925 (2017)
Schaik, P., Jeske, D., Onibokun, J., Coventry, L., Jansen, J., Kusev, P.: Risk perceptions of cyber-security and precautionary behavior. Comput. Hum. Behav. 62, 5678–5693 (2017)
Shindarev, N., Bagretsov, G., Abramov, M., Tulupyeva, T., Suvorova, A.: Approach to identifying of employees profiles in websites of social networks aimed to analyze social engineering vulnerabilities. In: International Conference on Intelligent Information Technologies for Industry, pp. 441–447 (2017)
Struharik, R., Vukobratović, B.: A system for hardware aided decision tree ensemble evolution. J. Parallel Distrib. Comput. 112, 67–83 (2018)
Suleimanov, A., Abramov, M., Tulupyev, A.: Modelling of the social engineering attacks based on social graph of employees communications analysis. In: 2018 IEEE Industrial Cyber-Physical Systems (ICPS), pp. 801–805 (2018)
Terlizzi, M., Meirelles, F., Viegas Cortez da Cunha, M.: Behavior of Brazilian banks employees on facebook and the cybersecurity governance. J. Appl. Secur. Res. 12, 224–252 (2017)
Tulupyev, A., Kharitonov, N., Zolotin, A.: Algebraic Bayesian networks: consistent fusion of partially intersected knowledge systems. In: The Second International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018”, pp. 109–115 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Azarov, A., Suvorova, A., Koroleva, M., Vasileva, O., Tulupyeva, T. (2020). Assessment of the Information System’s Protection Degree from Social Engineering Attack Action of Malefactor While Changing the Characteristics of User’s Profiles: Numerical Experiments. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_53
Download citation
DOI: https://doi.org/10.1007/978-3-030-50097-9_53
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50096-2
Online ISBN: 978-3-030-50097-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)