Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust

Wenjuan Li; Weizhi Meng; Hui Zhu

doi:10.1109/TrustCom50675.2020.00158

Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust

Wenjuan Li, Weizhi Meng^*, Hui Zhu

^*Corresponding author for this work

Department of Applied Mathematics and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

With the speedy growth of distributed networks such as Internet of Things (IoT), there is an increasing need to protect network security against various attacks by deploying collaborative intrusion detection systems (CIDSs), which allow different detector nodes to exchange required information and data with each other. While due to the distributed architecture, insider attacks are a big threat for CIDSs, in which an attacker can reside inside the network. To address this issue, designing an appropriate trust management scheme is considered as an effective solution. In this work, we first analyze the development of CIDSs in the past decades and identify the major challenges on building an effective trust management scheme. Then we introduce a generic framework aiming to enhance the security of CIDSs against advanced insider threats by deriving multilevel trust. In the study, our results demonstrate the viability and the effectiveness of our framework.

Original language	English
Title of host publication	Proceedings of 19^th IEEE International Conference on Trust, Security and Privacy in Computing and Communications
Editors	Guojun Wang, Ryan Ko, Md Zakirul Alam Bhuiyan, Yi Pan
Publisher	IEEE
Publication date	Dec 2020
Pages	1179-1186
ISBN (Electronic)	9780738143804
DOIs	https://doi.org/10.1109/TrustCom50675.2020.00158
Publication status	Published - Dec 2020
Event	19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications - Guangzhou, China Duration: 29 Dec 2020 → 1 Jan 2021 Conference number: 19

Conference

Conference	19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications
Number	19
Country/Territory	China
City	Guangzhou
Period	29/12/2020 → 01/01/2021

Bibliographical note

Funding Information:
This work was partially supported by the National Natural Science Foundation of China (No. 61802077).

Publisher Copyright:
© 2020 IEEE.

Keywords

Collaborative Intrusion Detection
Distributed Network
Insider Threat
Multi-Level Trust
Trust Management

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10.1109/TrustCom50675.2020.00158

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Li, W., Meng, W., & Zhu, H. (2020). Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust. In G. Wang, R. Ko, M. Z. A. Bhuiyan, & Y. Pan (Eds.), Proceedings of 19^th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (pp. 1179-1186). IEEE. https://doi.org/10.1109/TrustCom50675.2020.00158

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title = "Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust",

abstract = "With the speedy growth of distributed networks such as Internet of Things (IoT), there is an increasing need to protect network security against various attacks by deploying collaborative intrusion detection systems (CIDSs), which allow different detector nodes to exchange required information and data with each other. While due to the distributed architecture, insider attacks are a big threat for CIDSs, in which an attacker can reside inside the network. To address this issue, designing an appropriate trust management scheme is considered as an effective solution. In this work, we first analyze the development of CIDSs in the past decades and identify the major challenges on building an effective trust management scheme. Then we introduce a generic framework aiming to enhance the security of CIDSs against advanced insider threats by deriving multilevel trust. In the study, our results demonstrate the viability and the effectiveness of our framework.",

keywords = "Collaborative Intrusion Detection, Distributed Network, Insider Threat, Multi-Level Trust, Trust Management",

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note = "Funding Information: This work was partially supported by the National Natural Science Foundation of China (No. 61802077). Publisher Copyright: {\textcopyright} 2020 IEEE.; 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 ; Conference date: 29-12-2020 Through 01-01-2021",

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language = "English",

pages = "1179--1186",

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Li, W, Meng, W & Zhu, H 2020, Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust. in G Wang, R Ko, MZA Bhuiyan & Y Pan (eds), Proceedings of 19^th IEEE International Conference on Trust, Security and Privacy in Computing and Communications. IEEE, pp. 1179-1186, 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Guangzhou, China, 29/12/2020. https://doi.org/10.1109/TrustCom50675.2020.00158

Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust. / Li, Wenjuan; Meng, Weizhi; Zhu, Hui.
Proceedings of 19^th IEEE International Conference on Trust, Security and Privacy in Computing and Communications. ed. / Guojun Wang; Ryan Ko; Md Zakirul Alam Bhuiyan; Yi Pan. IEEE, 2020. p. 1179-1186.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Towards collaborative intrusion detection enhancement against insider attacks with multi-level trust

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Keywords

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