Sensitivity Analysis for Deep Learning Data Sets Considering the Human Immune System

Recently, open source software (OSS) has been widely used in many fields due to the spread and development facilitated by networks. The characteristics of OSS include no cost and high performance, which make it a significant component of modern society. However, the number of reported faults is increasing due to its vulnerabilities. Detecting these faults requires substantial costs, and correcting the growing number of faults necessitates a large workforce. In this paper, we propose a method for Reliability Assessment of OSS using deep learning based on the human immune system. Additionally, we present several numerical examples based on the proposed method.

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Publication Details

Journal
Journal of Graphic Era University
Published
2024-11-08
DOI
https://doi.org/10.13052/jgeu0975-1416.1228
Primary Topic
Artificial Immune Systems Applications
Type
article
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Sensitivity Analysis for Deep Learning Data Sets Considering the Human Immune System

Yoshinobu Tamura, Shigeru Yamada, Shoichiro Miyamoto, Hisashi Takeda, Lei Zhou
article en

Abstract

Recently, open source software (OSS) has been widely used in many fields due to the spread and development facilitated by networks. The characteristics of OSS include no cost and high performance, which make it a significant component of modern society. However, the number of reported faults is increasing due to its vulnerabilities. Detecting these faults requires substantial costs, and correcting the growing number of faults necessitates a large workforce. In this paper, we propose a method for Reliability Assessment of OSS using deep learning based on the human immune system. Additionally, we present several numerical examples based on the proposed method.

Journal of Graphic Era University
Yamaguchi University (JP), Tottori University (JP)
Partnerships for the goals
Openalex Percentile: Top 82%
Artificial Immune Systems Applications
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