On Collaboration and Automation in the Context of Threat Detection and Response with Privacy-Preserving Features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F25%3A10133794" target="_blank" >RIV/63839172:_____/25:10133794 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14610/25:00140657

Výsledek na webu

<a href="https://doi.org/10.1145/3707651" target="_blank" >https://doi.org/10.1145/3707651</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3707651" target="_blank" >10.1145/3707651</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Collaboration and Automation in the Context of Threat Detection and Response with Privacy-Preserving Features

Popis výsledku v původním jazyce

Organizations and their security operation centers often struggle to detect and respond effectively to an extensive quantity of ever-evolving cyberattacks. While collaboration, such as threat intelligence sharing between security teams, and response automation are often discussed in the cybersecurity community, issues like data sensitivity and confidence in detection may hinder their adoption. This work investigates the potentials and challenges of collaboration and automation to enhance incident response processes. We propose a reference architecture for data sharing in threat detection and response, aiming to boost collaborative and automated efforts across organizations while also considering privacy-preserving features. To address these challenges and potentials, we discuss how such a framework could enhance current response processes within and between organizations, validated with results in local attack detection, incident response, and data sharing.

Název v anglickém jazyce

On Collaboration and Automation in the Context of Threat Detection and Response with Privacy-Preserving Features

Popis výsledku anglicky

Organizations and their security operation centers often struggle to detect and respond effectively to an extensive quantity of ever-evolving cyberattacks. While collaboration, such as threat intelligence sharing between security teams, and response automation are often discussed in the cybersecurity community, issues like data sensitivity and confidence in detection may hinder their adoption. This work investigates the potentials and challenges of collaboration and automation to enhance incident response processes. We propose a reference architecture for data sharing in threat detection and response, aiming to boost collaborative and automated efforts across organizations while also considering privacy-preserving features. To address these challenges and potentials, we discuss how such a framework could enhance current response processes within and between organizations, validated with results in local attack detection, incident response, and data sharing.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/LM2023054" target="_blank" >LM2023054: e-Infrastruktura CZ</a><br>

Návaznosti

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

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

DIGITAL THREATS: RESEARCH AND PRACTICE

ISSN

2692-1626

e-ISSN

2576-5337

Svazek periodika

6

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

36

Strana od-do

5

Kód UT WoS článku

001470073800003

EID výsledku v databázi Scopus

2-s2.0-105002995143