Technology of Information Security
|
2845-2850

Data poisoning defense based on sample distribution characteristics

Yang Lisheng
Luo Wenhua
School of Public Security Information Technology & Intelligence, Criminal Investigation Police University of China, Shenyang 110035, China

Abstract

The traffic classification model is vulnerable to the interference of data pollution in the update process and reduces the performance of the model. The existing defense methods based on data cleaning need to rely on expert experience and manual screening, and cannot effectively deal with the poison attack constructed by using unknown distributed samples. In view of the above problems, inspired by out-of-distribution detection and discrimination active learning, this paper designed a data poisoning prevention method based on sample distribution characteristics, and used the binary classification discriminator to screen out the known and unknown distribution samples in each new round of samples. For the new known distribution samples, it used the concordant rate of prediction and annotation to evaluate the data quality of the new samples and determine whether to update the model. For the new unknown distribution samples, it used the small sample sampling based on the labeling accuracy to evaluate the sample availability. The experimental results show that this method can guarantee the accuracy of the model while resisting the data poisoning attack, and effectively identify the data poisoning attack constructed by using unknown distribution samples.

Foundation Support

国家重点研发计划资助项目(2018YFC0830600)
中国刑事警察学院研究生创新能力提升项目(2022YCZD05)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.01.0025
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Technology of Information Security
Pages: 2845-2850
Serial Number: 1001-3695(2023)09-045-2845-06

Publish History

[2023-04-04] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

杨立圣, 罗文华. 基于样本分布特征的数据投毒防御 [J]. 计算机应用研究, 2023, 40 (9): 2845-2850. (Yang Lisheng, Luo Wenhua. Data poisoning defense based on sample distribution characteristics [J]. Application Research of Computers, 2023, 40 (9): 2845-2850. )

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.

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