So-Eun Jeon, Sun-Jin Lee, Il-Gu Lee*
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2407-2419, 2023, DOI:10.32604/iasc.2023.039937
- 21 June 2023
Abstract With the development of the 5th generation of mobile communication (5G) networks and artificial intelligence (AI) technologies, the use of the Internet of Things (IoT) has expanded throughout industry. Although IoT networks have improved industrial productivity and convenience, they are highly dependent on nonstandard protocol stacks and open-source-based, poorly validated software, resulting in several security vulnerabilities. However, conventional AI-based software vulnerability discovery technologies cannot be applied to IoT because they require excessive memory and computing power. This study developed a technique for optimizing training data size to detect software vulnerabilities rapidly while maintaining learning accuracy. More >
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