• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.909-928
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• 2020

From the early 1970s, the US government began to recognize that penetration testing could not assure the security quality of products. Results of penetration testing such as identified vulnerabilities and faults can be varied depending on the capabilities of the team. In other words none of penetration team can assure that "vulnerabilities are not found" is not equal to "product does not have any vulnerabilities". So the U.S. government realized that in order to improve the security quality of products, the development process itself should be managed systematically and strictly. Therefore, the US government began to publish various standards related to the development methodology and evaluation procurement system embedding "security-by-design" concept from the 1980s. Security-by-design means reducing product's complexity by considering security from the initial phase of development lifecycle such as the product requirements analysis and design phase to achieve trustworthiness of product ultimately. Since then, the security-by-design concept has been spread to the private sector since 2002 in the name of Secure SDLC by Microsoft and IBM, and is currently being used in various fields such as automotive and advanced weapon systems. However, the problem is that it is not easy to implement in the actual field because the standard or guidelines related to Secure SDLC contain only abstract and declarative contents. Therefore, in this paper, we present the new framework in order to specify the level of Secure SDLC desired by enterprises. Our proposed CIA (functional Correctness, safety Integrity, security Assurance)-level-based security-by-design framework combines the evidence-based security approach with the existing Secure SDLC. Using our methodology, first we can quantitatively show gap of Secure SDLC process level between competitor and the company. Second, it is very useful when you want to build Secure SDLC in the actual field because you can easily derive detailed activities and documents to build the desired level of Secure SDLC.