Summary information

Study title

Threat Level Index for Advanced Persistent Threats (APT) - European Repository of Cyber Incidents

Creator

Borrett, Camille ( Stiftung Wissenschaft und Politik)

Study number / PID

10.7802/2494 (GESIS)

10.7802/2494 (DOI)

Data access

Information not available

Series

Not available

Abstract

This dataset is a subset of the European Repository of Cyber Incidents (EuRepoC) database. It contains 198 cyber incidents that occurred between 2002 and 2021 attributed to 19 Advanced Persistent Threats (APTs). APTs are potent, persistent, and state-affiliated, if not state-integrated, cyber actors responsible for various cyber-attacks. Within the context of the EuRepoC project, we have designed a Threat Level Index for assessing the relative level of threat posed by some of the most active APTs in cyberspace. The index is made up of five indicators to assess: (1) the intensity of the attacks attributed to the APT groups; (2) the sectorial scope of their attacks; (3) the geographical scope; (4) the frequency of attacks and (5) the sophistication of their attacks. This dataset contains the specific incidents along with the different calculations used for reaching the Threat Level scores for 19 APTs. About EuRepoC: EuRepoC gathers, codes, and analyses publicly available information from over 200 sources and 600 Twitter accounts on a daily basis to report on dynamic trends in the global, and particularly the European, cyber threat environment. For more information on the scope and data collection methodology for the primary database from which this dataset is derived see: https://eurepoc.eu/methodology . The APT profiles in which the Threat Level scores are used can be found here: https://eurepoc.eu/apts .

Topics

Not available

Keywords

Not available

Methodology

Data collection period

Not available

Country

Time dimension

Not available

Analysis unit

Not available

Universe

Sampling procedure

Not available

Kind of data

Not available

Data collection mode

Aggregation
Compilation/Synthesis

Access

Publisher

GESIS Data Archive for the Social Sciences

Publication year

2022

Terms of data access

Free access (without registration) - The research data can be downloaded directly by anyone without further limitations. CC BY 4.0: Attribution (https://creativecommons.org/licenses/by/4.0/deed.de)

Related publications

Not available