Algorithm Research & Explore
|
388-393

Improved isolation forest method based on high contrast subspace

Zhou Hang
Jiang Yu
College of Software Engineering, Chengdu University of Information Technology, Chengdu 610200, China

Abstract

Aiming at the problem that isolation forest is unreliable in the face of high-dimensional data by randomly selecting attributes, this paper proposed an improved anomaly detection algorithm high contrast subspace isolation forest(HiForest). Firstly, this algorithm selected the subspace with high contrast value based on the deviation between the edge probability and the joint probability of each attribute in the subspace. After that, the algorithm constructed isolation trees which had a stronger ability to isolate outliers in the relevant subspace. Finally, the algorithm integrated these isolation trees into isolation forest, and obtained the anomaly score by traversing the average path length of data points in the isolation forest. Compared with traditional anomaly detection algorithms, the experimental results based on the ODDS database show that the HiForest algorithm improves the AUC, accuracy, recall rate significantly. Therefore, HiForest algorithm is an anomaly detection algorithm suitable for high-dimensional datasets with higher detection accuracy.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.06.0305
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 2
Section: Algorithm Research & Explore
Pages: 388-393
Serial Number: 1001-3695(2023)02-012-0388-06

Publish History

[2022-08-30] Accepted Paper
[2023-02-05] Printed Article

Cite This Article

周杭, 蒋瑜. 基于高对比度子空间的改进孤立森林方法 [J]. 计算机应用研究, 2023, 40 (2): 388-393. (Zhou Hang, Jiang Yu. Improved isolation forest method based on high contrast subspace [J]. Application Research of Computers, 2023, 40 (2): 388-393. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)