Enhancing intelligent alarm reduction for distributed intrusion detection systems via edge computing

Weizhi MENG, Yu WANG, Wenjuan LI, Zhe LIU, Jin LI, Christian W. PROBST

Research output: Chapter in Book/Report/Conference proceedingChapters

20 Citations (Scopus)

Abstract

To construct an intelligent alarm filter is a promising solution to help reduce false alarms for an intrusion detection system (IDS), in which an appropriate algorithm can be selected in an adaptive way. Taking the advantage of cloud computing, the process of algorithm selection can be offloaded to the cloud, but it may cause communication delay and additional burden on the cloud side. This issue may become worse when it comes to distributed intrusion detection systems (DIDSs), i.e., some IoT applications might require very short response time and most of the end nodes in IoT are energy constrained things. In this paper, with the advent of edge computing, we propose a framework for improving the intelligent false alarm reduction for DIDSs based on edge computing devices (i.e., the data can be processed at the edge for shorter response time and could be more energy efficient). The evaluation shows that the proposed framework can help reduce the workload for the central server and shorten the delay as compared to the similar studies. Copyright © 2018 Springer International Publishing AG, part of Springer Nature.

Original languageEnglish
Title of host publicationInformation security and privacy: 23rd Australasian Conference, ACISP 2018, Wollongong, NSW, Australia, July 11-13, 2018, proceedings
EditorsWilly SUSILO, Guomin YANG
Place of PublicationCham
PublisherSpringer
Pages759-767
ISBN (Electronic)9783319936383
ISBN (Print)9783319936376
DOIs
Publication statusPublished - 2018

Citation

Meng, W., Wang, Y., Li, W., Liu, Z., Li, J., & Probst, C. W. (2018). Enhancing intelligent alarm reduction for distributed intrusion detection systems via edge computing. In W. Susilo & G. Yang (Eds.), Information security and privacy: 23rd Australasian Conference, ACISP 2018, Wollongong, NSW, Australia, July 11-13, 2018, proceedings (pp. 759-767). Springer. https://doi.org/10.1007/978-3-319-93638-3_44

Keywords

  • Intrusion detection
  • Intelligent false alarm filtration
  • Edge computing
  • Distributed environment
  • Cloud computing

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