Dataset of intrusion detection alerts from a sharing platform

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F20%3A10133314" target="_blank" >RIV/63839172:_____/20:10133314 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14610/20:00116889

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2352340920314128" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352340920314128</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.dib.2020.106530" target="_blank" >10.1016/j.dib.2020.106530</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dataset of intrusion detection alerts from a sharing platform

Popis výsledku v původním jazyce

The dataset contains intrusion detection alerts obtained via an alert sharing platform (SABU) for one week. A plethora of heterogeneous intrusion detection systems deployed across several organizations contributed to the sharing platform. The alerts are stored in the intrusion Detection Extensible Alert (IDEA) format and categorized using the eCSIRT.net Incident Taxonomy. Dataset can be used in several areas of cybersecurity research for the analysis of intrusion detection alerts including temporal and spatial correlations, reputation scoring, attack scenario reconstruction, and attack projection. The network identifiers (e.g., IP addresses, hostnames) are anonymized. However, the list of interesting features (e.g., presence on blacklists, geolocation) of such entities at the time of data collection is provided.

Název v anglickém jazyce

Dataset of intrusion detection alerts from a sharing platform

Popis výsledku anglicky

The dataset contains intrusion detection alerts obtained via an alert sharing platform (SABU) for one week. A plethora of heterogeneous intrusion detection systems deployed across several organizations contributed to the sharing platform. The alerts are stored in the intrusion Detection Extensible Alert (IDEA) format and categorized using the eCSIRT.net Incident Taxonomy. Dataset can be used in several areas of cybersecurity research for the analysis of intrusion detection alerts including temporal and spatial correlations, reputation scoring, attack scenario reconstruction, and attack projection. The network identifiers (e.g., IP addresses, hostnames) are anonymized. However, the list of interesting features (e.g., presence on blacklists, geolocation) of such entities at the time of data collection is provided.

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Data in Brief

ISSN

2352-3409

e-ISSN

—

Svazek periodika

33

Číslo periodika v rámci svazku

December

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

106530

Kód UT WoS článku

000600652300195

EID výsledku v databázi Scopus

2-s2.0-85096842996