TY - JOUR
T1 - Insight into insiders and IT
T2 - A survey of insider threat taxonomies, analysis, modeling, and countermeasures
AU - Homoliak, Ivan
AU - Toffalini, Flavio
AU - Guarnizo, Juan
AU - Elovici, Yuval
AU - Ochoa, Martín
N1 - Funding Information:
This work was supported by ST Electronics and the National Research Foundation, Prime Minister’s Office, Singapore under Corporate Laboratory @ University Scheme (Programme Title: STEE Infosec-SUTD Corporate Laboratory). Further, the work was supported by the H2020 EC-SEL project Aquas (8A17001), the IT4Innovations Excellence in Science project LQ1602, and the internal project of Brno University of Technology number FIT-S-17-4014.
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - Insider threats are one of today's most challenging cybersecurity issues that are not well addressed by commonly employed security solutions. In this work, we propose structural taxonomy and novel categorization of research that contribute to the organization and disambiguation of insider threat incidents and the defense solutions used against them. The objective of our categorization is to systematize knowledge in insider threat research while using an existing grounded theory method for rigorous literature review. The proposed categorization depicts the workflow among particular categories that include incidents and datasets, analysis of incidents, simulations, and defense solutions. Special attention is paid to the definitions and taxonomies of the insider threat; we present a structural taxonomy of insider threat incidents that is based on existing taxonomies and the 5W1H questions of the information gathering problem. Our survey will enhance researchers' efforts in the domain of insider threat because it provides (1) a novel structural taxonomy that contributes to orthogonal classification of incidents and defining the scope of defense solutions employed against them, (2) an overview on publicly available datasets that can be used to test new detection solutions against other works, (3) references of existing case studies and frameworks modeling insiders' behaviors for the purpose of reviewing defense solutions or extending their coverage, and (4) a discussion of existing trends and further research directions that can be used for reasoning in the insider threat domain.
AB - Insider threats are one of today's most challenging cybersecurity issues that are not well addressed by commonly employed security solutions. In this work, we propose structural taxonomy and novel categorization of research that contribute to the organization and disambiguation of insider threat incidents and the defense solutions used against them. The objective of our categorization is to systematize knowledge in insider threat research while using an existing grounded theory method for rigorous literature review. The proposed categorization depicts the workflow among particular categories that include incidents and datasets, analysis of incidents, simulations, and defense solutions. Special attention is paid to the definitions and taxonomies of the insider threat; we present a structural taxonomy of insider threat incidents that is based on existing taxonomies and the 5W1H questions of the information gathering problem. Our survey will enhance researchers' efforts in the domain of insider threat because it provides (1) a novel structural taxonomy that contributes to orthogonal classification of incidents and defining the scope of defense solutions employed against them, (2) an overview on publicly available datasets that can be used to test new detection solutions against other works, (3) references of existing case studies and frameworks modeling insiders' behaviors for the purpose of reviewing defense solutions or extending their coverage, and (4) a discussion of existing trends and further research directions that can be used for reasoning in the insider threat domain.
KW - 5W1H questions
KW - Grounded theory for rigorous literature review
KW - Insider threat
KW - Malicious insider threat
KW - Masqueraders
KW - Traitors
KW - Unintentional insider threat
UR - http://www.scopus.com/inward/record.url?scp=85065724158&partnerID=8YFLogxK
U2 - 10.1145/3303771
DO - 10.1145/3303771
M3 - Review article
AN - SCOPUS:85065724158
SN - 0360-0300
VL - 52
JO - ACM Computing Surveys
JF - ACM Computing Surveys
IS - 2
M1 - a30
ER -