• Journal of Information Processing Systems
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• v.14 no.3
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• pp.740-750
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• 2018

There are a great number of Internet-connected devices and their information can be acquired through an Internet-wide scanning tool. By associating device information with publicly known security vulnerabilities, security experts are able to determine whether a particular device is vulnerable. Currently, the identification of the device information and its related vulnerabilities is manually carried out. It is necessary to automate the process to identify a huge number of Internet-connected devices in order to analyze more than one hundred thousand security vulnerabilities. In this paper, we propose a method of automatically generating device information in the Common Platform Enumeration (CPE) format from banner text to discover potentially weak devices having the Common Vulnerabilities Exposures (CVE) vulnerability. We demonstrated that our proposed method can distinguish as much adequate CPE information as possible in the service banner.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.1-10
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• 2024

Attackers tend to use similar vulnerabilities when finding their next target IT assets. They also continuously search for new attack targets. Therefore, it is essential to find the potential targets of attackers in advance. Our method proposes a novel approach for efficient vulnerable asset management and zero-day response. In this paper, we propose the ability to detect the IT assets that are potentially infected by the recently discovered vulnerability based on clustering and similarity results. As the experiment results, 86% of all collected assets are clustered within the same clustering. In addition, as a result of conducting a similarity calculation experiment by randomly selecting vulnerable assets, assets using the same OS and service were listed.