TY - GEN
T1 - A Framework of Blockchain-Based Collaborative Intrusion Detection in Software Defined Networking
AU - Li, Wenjuan
AU - Tan, Jiao
AU - Wang, Yu
N1 - Funding Information:
Acknowledgments. This work was partially supported by National Natural Science Foundation of China (No. 61802080 and 61802077).
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - To protect network assets from various cyber intrusions and fit the distributed environments like Internet of Things (IoTs), collaborative intrusion detection systems (CIDSs) are widely implemented allowing each detection node to exchange required data and information. This aims to improve the detection performance against some complicated attacks. In recent years, software defined networking (SDN) is developing rapidly, which can simplify the network complexity by separating the controller plane from the forwarding plane. In this way, the controller can manage the whole network without knowing the underlying structure and devices. To identify underlying malicious nodes or devices, CIDSs are still an important solution to secure SDN, but might be vulnerable to insider threats, in which an attacker can behave maliciously insider the network. In this work, we focus on this issue and advocate the merit on combining trust management and blockchain technology. Trust management can help evaluate the trustworthiness of each node, and blockchain technology can allow communication without a trusted party while ensuring the integrity of shared data. We then introduce a general framework of blockchain-based collaborative intrusion detection in SDN. In the study, we take challenge-based CIDS as a case, and evaluate our framework performance under both external and internal attacks. Our results indicate the viability and effectiveness of our framework.
AB - To protect network assets from various cyber intrusions and fit the distributed environments like Internet of Things (IoTs), collaborative intrusion detection systems (CIDSs) are widely implemented allowing each detection node to exchange required data and information. This aims to improve the detection performance against some complicated attacks. In recent years, software defined networking (SDN) is developing rapidly, which can simplify the network complexity by separating the controller plane from the forwarding plane. In this way, the controller can manage the whole network without knowing the underlying structure and devices. To identify underlying malicious nodes or devices, CIDSs are still an important solution to secure SDN, but might be vulnerable to insider threats, in which an attacker can behave maliciously insider the network. In this work, we focus on this issue and advocate the merit on combining trust management and blockchain technology. Trust management can help evaluate the trustworthiness of each node, and blockchain technology can allow communication without a trusted party while ensuring the integrity of shared data. We then introduce a general framework of blockchain-based collaborative intrusion detection in SDN. In the study, we take challenge-based CIDS as a case, and evaluate our framework performance under both external and internal attacks. Our results indicate the viability and effectiveness of our framework.
KW - Blockchain technology
KW - Collaborative intrusion detection
KW - Insider attack
KW - Software defined networking
KW - Trust management
UR - http://www.scopus.com/inward/record.url?scp=85098252567&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-65745-1_15
DO - 10.1007/978-3-030-65745-1_15
M3 - Conference article published in proceeding or book
AN - SCOPUS:85098252567
SN - 9783030657444
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 261
EP - 276
BT - Network and System Security - 14th International Conference, NSS 2020, Proceedings
A2 - Kutyłowski, Mirosław
A2 - Zhang, Jun
A2 - Chen, Chao
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th International Conference on Network and System Security, NSS 2020
Y2 - 25 November 2020 through 27 November 2020
ER -