Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91603
| Title: | A fog-based collaborative intrusion detection framework for smart grid | Authors: | Li, WJ Au, MH Wang, Y |
Issue Date: | Mar-2021 | Source: | International journal of network management, Mar./Apr. 2021, v. 31, no. 2, e2107 | Abstract: | With the rapid development of information and communication technologies (ICTs), the conventional electrical grid is evolving towards an intelligent smart grid. Due to the complexity, how to protect the security of smart grid environments still remains a practical challenge. Currently, collaborative intrusion detection systems (CIDSs) are one important solution to help identify various security threats, through allowing various IDS nodes to exchange data and information. However, with the increasing adoption of ICT in smart grid, cloud computing is often deployed in order to reduce the storage burden locally. However, due to the distance between grid and cloud, it is critical for smart grid to ensure the timely response to any accidents. In this work, we review existing collaborative detection mechanisms and introduce a fog-based CIDS framework to enhance the detection efficiency. The results show that our approach can improved the detection efficiency by around 21% to 45% based on the concrete attacking scenarios. | Publisher: | John Wiley & Sons Ltd. | Journal: | International journal of network management | ISSN: | 1055-7148 | EISSN: | 1099-1190 | DOI: | 10.1002/nem.2107 | Rights: | © 2020 John Wiley & Sons, Ltd This is the peer reviewed version of the following article: Li, W, Au, MH, Wang, Y. A fog-based collaborative intrusion detection framework for smart grid. Int J Network Mgmt. 2021; 31:e2107, which has been published in final form at https://doi.org/10.1002/nem.2107. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| IJNM-Li-2019.pdf | Pre-Published version | 617.29 kB | Adobe PDF | View/Open |
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