AUTHOR=Abbiati Giovanni , Ranise Silvio , Schizzerotto Antonio , Siena Alberto 

TITLE=Merging Datasets of CyberSecurity Incidents for Fun and Insight

JOURNAL=Frontiers in Big Data

VOLUME=Volume 3 - 2020

YEAR=2021

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2020.521132

DOI=10.3389/fdata.2020.521132

ISSN=2624-909X

ABSTRACT=Cyber security incidents can have dramatic economic, social and
institutional impact.
 Providing an adequate assessment of the cyber-security posture for
companies and organisations needs to collects information about
threats from a wide range of sources.
 One of such sources is history, intended as the knowledge about past
cyber-security incidents, their size, type of attacks, industry sector
and so on.
 Ideally, having a large enough dataset of past security incidents, it
would be possible to analyse it with artificial intelligence tools and
draw conclusions that may help in preventing future incidents.
 Unfortunately, it seems that there are only a few publicly available
datasets of this kind that are of good quality.
 The paper reports our initial efforts in collecting all publicly
available security incidents datasets, and building a single, large
dataset that can be used to draw statistically significant
observations.
 In order to argue about its statistical quality, we analyse the
resulting combined dataset against the source ones.
 Additionally, we perform an analysis of the combined dataset, and
compare our results with the existing literature.
 Finally, we discuss our findings, and discuss the limitations of the
proposed approach and point out interesting research directions.