TY - GEN
T1 - A taxonomy of metrics and tests to evaluate and validate properties of industrial intrusion detection systems
AU - Martinez, Cyntia Vargas
AU - Vogel-Heuser, Birgit
N1 - Publisher Copyright:
Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
PY - 2019
Y1 - 2019
N2 - The integration of Intrusion Detection Systems (IDS) in Industrial Automation Systems (IAS) has gained popularity over the past years. This has occurred due to their ability to detect intrusions at a device and network level. In order for these systems to provide effective and reliable protection, they must possess a set of specific properties. These properties are inherent characteristics that depend on the IDS application field, as different fields provide different deployment conditions. Unfortunately, the evaluation and validation of such properties for IAS has proven challenging, as current contributions often follow evaluation and validation approaches from the IT domain that focus solely on the effectiveness of intrusion detection approaches; hence, neglecting other aspects relevant to the industrial domain. This paper addresses this issue by presenting IDS properties derived from trends and characteristics of IAS; as well as a taxonomy of metrics and tests to evaluate and validate these properties. This taxonomy provides a foundation from which future IDS contributions for IAS can be improved and reinforced by providing an overview of pertinent metrics and tests.
AB - The integration of Intrusion Detection Systems (IDS) in Industrial Automation Systems (IAS) has gained popularity over the past years. This has occurred due to their ability to detect intrusions at a device and network level. In order for these systems to provide effective and reliable protection, they must possess a set of specific properties. These properties are inherent characteristics that depend on the IDS application field, as different fields provide different deployment conditions. Unfortunately, the evaluation and validation of such properties for IAS has proven challenging, as current contributions often follow evaluation and validation approaches from the IT domain that focus solely on the effectiveness of intrusion detection approaches; hence, neglecting other aspects relevant to the industrial domain. This paper addresses this issue by presenting IDS properties derived from trends and characteristics of IAS; as well as a taxonomy of metrics and tests to evaluate and validate these properties. This taxonomy provides a foundation from which future IDS contributions for IAS can be improved and reinforced by providing an overview of pertinent metrics and tests.
KW - Industrial Automation Systems
KW - Information Security
KW - Intrusion Detection
KW - Network Security
KW - System Testing
KW - System Validation
UR - http://www.scopus.com/inward/record.url?scp=85073071018&partnerID=8YFLogxK
U2 - 10.5220/0007833902010210
DO - 10.5220/0007833902010210
M3 - Conference contribution
AN - SCOPUS:85073071018
T3 - ICETE 2019 - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications
SP - 201
EP - 210
BT - SECRYPT
A2 - Obaidat, Mohammad S.
A2 - Obaidat, Mohammad S.
A2 - Samarati, Pierangela
PB - SciTePress
T2 - 16th International Joint Conference on e-Business and Telecommunications, ICETE 2019
Y2 - 26 July 2019 through 28 July 2019
ER -