• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.85-93
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• 1999

In this study, PC-based slicing machine and driving software were constructed for the purpose of automation of semi-conductor cutting process. The biggest feature of software is variation of parameter and include data base, signal monitoring, error report, corresponding action or automatic motion planing. Parameters were drawn and algorithms were developed to make software by GUI interface. The cutting experiment was done for sampled wafer to see the effectiveness of the soft automation. From the experimented and implemented results, it is shown that parameters for automation of slicing process could be drawn, then its algorithms constructed. It could be considered what is the merit of this slicing machine by comparing the PC-based and the NC-based.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.59-66
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• 2017

Hackers have obfuscated their malware to avoid being analyzed. Recently, obfuscation tools translate original codes into bytecodes to use virtualized-obfuscation, so that bytecodes are executed by virtual machines. In such cases, malware analysts fail to know about the malware before execution of the codes. We found that program slicing is one of promising program analysis techniques to solve this problem. The main concepts of program slice include slicing criteria given by analysts and sliced statements according to the slicing criteria. This paper proposes a deobfuscation method based on program slicing technique.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.13-14
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• 2012

• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.