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Employees’ Social Graph Analysis : A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack’s Spread. / Khlobystova, A.; Abramov, M.; Tulupyev, A.

PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19). ред. / S Kovalev; Tarassov; Snasel; A Sukhanov. Springer Nature, 2020. стр. 198-205 (Advances in Intelligent Systems and Computing; Том 1156).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Khlobystova, A, Abramov, M & Tulupyev, A 2020, Employees’ Social Graph Analysis: A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack’s Spread. в S Kovalev, Tarassov, Snasel & A Sukhanov (ред.), PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19). Advances in Intelligent Systems and Computing, Том. 1156, Springer Nature, стр. 198-205, 4th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2019, Ostrava-Prague, Чехия, 2/12/19. https://doi.org/10.1007/978-3-030-50097-9_20

APA

Khlobystova, A., Abramov, M., & Tulupyev, A. (2020). Employees’ Social Graph Analysis: A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack’s Spread. в S. Kovalev, Tarassov, Snasel, & A. Sukhanov (Ред.), PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19) (стр. 198-205). (Advances in Intelligent Systems and Computing; Том 1156). Springer Nature. https://doi.org/10.1007/978-3-030-50097-9_20

Vancouver

Khlobystova A, Abramov M, Tulupyev A. Employees’ Social Graph Analysis: A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack’s Spread. в Kovalev S, Tarassov, Snasel, Sukhanov A, Редакторы, PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19). Springer Nature. 2020. стр. 198-205. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-50097-9_20

Author

Khlobystova, A. ; Abramov, M. ; Tulupyev, A. / Employees’ Social Graph Analysis : A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack’s Spread. PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19). Редактор / S Kovalev ; Tarassov ; Snasel ; A Sukhanov. Springer Nature, 2020. стр. 198-205 (Advances in Intelligent Systems and Computing).

BibTeX

@inproceedings{85a4814981ce4e619c429dfb448df69d,
title = "Employees{\textquoteright} Social Graph Analysis: A Model of Detection the Most Criticality Trajectories of the Social Engineering Attack{\textquoteright}s Spread",
abstract = "In this research we present the hybrid model of finding the most critical distribution trajectories of multipath Social engineering attacks, passing through which by the malefactor on a global basis has the topmost degree of probability and will bring the greatest loss to the company. The solution of search problem concerning the most critical trajectories rests upon the assumption that the estimated probabilities of the direct Social engineering attack on user, degree evaluation of documents{\textquoteright} criticality, the estimated probabilities of Social engineering attack{\textquoteright}s distribution from user to user are premised on linguistic indistinct variables are already calculated. The described model finds its application at creation when constructing the estimates of information systems users{\textquoteright} safety against Social engineering attacks and promotes well-timed informing of decision-makers on the vulnerabilities which being available in system.",
keywords = "Analysis of social graph of company employees, Finding of the most criticality trajectory of the spread multiway social engineering attack, Hybrid model of linguistic fuzzy variable, Multiway social engineering attacks, Propagation of the multiway social engineering attack, Social engineering",
author = "A. Khlobystova and M. Abramov and A. Tulupyev",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-3-030-50097-9_20",
language = "English",
isbn = "9783030500962",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Nature",
pages = "198--205",
editor = "S Kovalev and Tarassov and Snasel and A Sukhanov",
booktitle = "PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19)",
address = "Germany",
note = "4th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2019 ; Conference date: 02-12-2019 Through 07-12-2019",

}

RIS

TY - GEN

T1 - Employees’ Social Graph Analysis

T2 - 4th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2019

AU - Khlobystova, A.

AU - Abramov, M.

AU - Tulupyev, A.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - In this research we present the hybrid model of finding the most critical distribution trajectories of multipath Social engineering attacks, passing through which by the malefactor on a global basis has the topmost degree of probability and will bring the greatest loss to the company. The solution of search problem concerning the most critical trajectories rests upon the assumption that the estimated probabilities of the direct Social engineering attack on user, degree evaluation of documents’ criticality, the estimated probabilities of Social engineering attack’s distribution from user to user are premised on linguistic indistinct variables are already calculated. The described model finds its application at creation when constructing the estimates of information systems users’ safety against Social engineering attacks and promotes well-timed informing of decision-makers on the vulnerabilities which being available in system.

AB - In this research we present the hybrid model of finding the most critical distribution trajectories of multipath Social engineering attacks, passing through which by the malefactor on a global basis has the topmost degree of probability and will bring the greatest loss to the company. The solution of search problem concerning the most critical trajectories rests upon the assumption that the estimated probabilities of the direct Social engineering attack on user, degree evaluation of documents’ criticality, the estimated probabilities of Social engineering attack’s distribution from user to user are premised on linguistic indistinct variables are already calculated. The described model finds its application at creation when constructing the estimates of information systems users’ safety against Social engineering attacks and promotes well-timed informing of decision-makers on the vulnerabilities which being available in system.

KW - Analysis of social graph of company employees

KW - Finding of the most criticality trajectory of the spread multiway social engineering attack

KW - Hybrid model of linguistic fuzzy variable

KW - Multiway social engineering attacks

KW - Propagation of the multiway social engineering attack

KW - Social engineering

UR - http://www.scopus.com/inward/record.url?scp=85088210655&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/88ce401c-3c83-3950-a813-558968dcfd45/

U2 - 10.1007/978-3-030-50097-9_20

DO - 10.1007/978-3-030-50097-9_20

M3 - Conference contribution

AN - SCOPUS:85088210655

SN - 9783030500962

T3 - Advances in Intelligent Systems and Computing

SP - 198

EP - 205

BT - PROCEEDINGS OF THE FOURTH INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'19)

A2 - Kovalev, S

A2 - Tarassov, null

A2 - Snasel, null

A2 - Sukhanov, A

PB - Springer Nature

Y2 - 2 December 2019 through 7 December 2019

ER -

ID: 62789221