XGBoost Design byMulti-verse Optimiser: An Application forNetwork Intrusion Detection
- Title
- XGBoost Design byMulti-verse Optimiser: An Application forNetwork Intrusion Detection
- Creator
- Tair M.; Bacanin N.; Zivkovic M.; Venkatachalam K.; Strumberger I.
- Description
- This article presents the results of an experimental study, which aims to assess the efficiency of the performance of a novel multi-verse optimiser algorithm for the optimisation of parameters of a network intrusion detection system event classifier. The article gives an overview of computer network intrusion detection, outlines common issues faced by software solutions tackling this problem, and proposes using a machine learning algorithm to help solve some of these common issues. An XGBoost classification model with a multi-verse optimisation algorithm for adaptive search and optimisation is used to solve the network intrusion detection system event classifier hyper-parameter optimisation problem. Results of this experimental study are presented and discussed, the improvements compared to previous solutions is shown, and a possible direction of future work in this domain is given in the conclusion. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes on Data Engineering and Communications Technologies, Vol-126, pp. 1-16.
- Date
- 2022-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Computer networks; Intrusion detection; Machine learning; Multi-verse optimiser; Optimisation; Parameter tuning
- Coverage
- Tair M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Bacanin N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Zivkovic M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Venkatachalam K., Christ (Deemed to be University), Bangalore, India; Strumberger I., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia
- Rights
- Restricted Access
- Relation
- ISSN: 23674512
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Tair M.; Bacanin N.; Zivkovic M.; Venkatachalam K.; Strumberger I., “XGBoost Design byMulti-verse Optimiser: An Application forNetwork Intrusion Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/18649.