| Title | Dynamic Model of Cyber Defense Diagnostics of Information Systems With The Use of Fuzzy Technologies |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Laptiev, O., Shuklin, G., Hohonianc, S., Zidan, A., Salanda, I. |
| Conference Name | 2019 IEEE International Conference on Advanced Trends in Information Theory (ATIT) |
| Keywords | cryptographic level, cryptography, cyber defense diagnostics, cyber defense systems, cyberattack, cyberattack intensity, cyberattacks, cybersecurity, cybersecurity status, delayed differential equation theory, differential equations, dynamic model, Fuzzy Cryptography, fuzzy function, Fuzzy logic, fuzzy set theory, fuzzy technologies, information activity, Information security, information system, Information systems, logical fuzzy function, membership function, Metrics, negative consequence probability, probability, probability distribution density., pubcrawl, Resiliency, Scalability, security level, security status diagnosis, Task Analysis, Trojan horses |
| Abstract | When building the architecture of cyber defense systems, one of the important tasks is to create a methodology for current diagnostics of cybersecurity status of information systems and objects of information activity. The complexity of this procedure is that having a strong security level of the object at the software level does not mean that such power is available at the hardware level or at the cryptographic level. There are always weaknesses in all levels of information security that criminals are constantly looking for. Therefore, the task of promptly calculating the likelihood of possible negative consequences from the successful implementation of cyberattacks is an urgent task today. This paper proposes an approach of obtaining an instantaneous calculation of the probabilities of negative consequences from the successful implementation of cyberattacks on objects of information activity on the basis of delayed differential equation theory and the mechanism of constructing a logical Fuzzy function. This makes it possible to diagnose the security status of the information system. |
| DOI | 10.1109/ATIT49449.2019.9030465 |
| Citation Key | laptiev_dynamic_2019 |
Dynamic Model of Cyber Defense Diagnostics of Information Systems With The Use of Fuzzy Technologies