Predictive Methods in Cyber Defense: Current Experience and Research Challenges

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F20%3A10133295" target="_blank" >RIV/63839172:_____/20:10133295 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14610/21:00120728

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0167739X20329836" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0167739X20329836</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.future.2020.10.006" target="_blank" >10.1016/j.future.2020.10.006</a>

Result language

angličtina

Original language name

Predictive Methods in Cyber Defense: Current Experience and Research Challenges

Original language description

Predictive analysis allows next-generation cyber defense that is more proactive than current approaches based on intrusion detection. In this paper, we discuss various aspects of predictive methods in cyber defense and illustrate them on three examples of recent approaches. The first approach uses data mining to extract frequent attack scenarios and uses them to project ongoing cyberattacks. The second approach uses a dynamic network entity reputation score to predict malicious actors. The third approach uses time series analysis to forecast attack rates in the network. This paper presents a unique evaluation of the three distinct methods in a common environment of an intrusion detection alert sharing platform, which allows for a comparison of the approaches and illustrates the capabilities of predictive analysis for current and future research and cybersecurity operations. Our experiments show that all three methods achieved a sufficient technology readiness level for experimental deployment in an operational setting with promising accuracy and usability. Namely prediction and projection methods, despite their differences, are highly usable for predictive blacklisting, the first provides a more detailed output, and the second is more extensible. Network security situation forecasting is lightweight and displays very high accuracy, but does not provide details on predicted events.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Future Generation Computer Systems

ISSN

0167-739X

e-ISSN

—

Volume of the periodical

115

Issue of the periodical within the volume

February

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

14

Pages from-to

517-530

UT code for WoS article

000591438900018

EID of the result in the Scopus database

2-s2.0-85092215125