Detailed Information on Publication Record
2019
Survey of Attack Projection, Prediction, and Forecasting in Cyber Security
HUSÁK, Martin, Jana KOMÁRKOVÁ, Elias BOU-HARB and Pavel ČELEDABasic information
Original name
Survey of Attack Projection, Prediction, and Forecasting in Cyber Security
Authors
HUSÁK, Martin (203 Czech Republic, guarantor, belonging to the institution), Jana KOMÁRKOVÁ (203 Czech Republic, belonging to the institution), Elias BOU-HARB and Pavel ČELEDA (203 Czech Republic, belonging to the institution)
Edition
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, PISCATAWAY, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019, 1553-877X
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
RIV identification code
RIV/00216224:14610/19:00108866
Organization
Ústav výpočetní techniky – Repository – Repository
UT WoS
000459730200024
Keywords in English
cyber security;intrusion detection;situational awareness;prediction;forecasting;model checking
Links
EF16_019/0000822, research and development project.
Změněno: 6/9/2020 06:12, RNDr. Daniel Jakubík
Abstract
V originále
This paper provides a survey of prediction, and forecasting methods used in cyber security. Four main tasks are discussed first, attack projection and intention recognition, in which there is a need to predict the next move or the intentions of the attacker, intrusion prediction, in which there is a need to predict upcoming cyber attacks, and network security situation forecasting, in which we project cybersecurity situation in the whole network. Methods and approaches for addressing these tasks often share the theoretical background and are often complementary. In this survey, both methods based on discrete models, such as attack graphs, Bayesian networks, and Markov models, and continuous models, such as time series and grey models, are surveyed, compared, and contrasted. We further discuss machine learning and data mining approaches, that have gained a lot of attention recently and appears promising for such a constantly changing environment, which is cyber security. The survey also focuses on the practical usability of the methods and problems related to their evaluation.