• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.587-596
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• 2024

Cyber Attack and Cyber Threat are getting confused and evolved. Therefore, using AI(Artificial Intelligence), which is the most important technology in Fourth Industry Revolution, to build a Cyber Threat Detection System is getting important. Especially, Government's SOC(Security Operation Center) is highly interested in using AI to build SOAR(Security Orchestration, Automation and Response) Solution to predict and build CTI(Cyber Threat Intelligence). In this thesis, We introduce the Cyber Threat Detection System by analyzing Network Traffic and Web Application Firewall(WAF) Log data. Additionally, we apply the well-known TF-IDF(Term Frequency-Inverse Document Frequency) method and AutoML technology to classify Web traffic attack type.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.709-712
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• 2017

RocksDB는 Facebook에서 LevelDB를 기반으로 개발한 임베디드 key-value 스토리지 엔진이다. Log structured tree(LSM-tree)를 기본구조로 사용하는 RocksDB는 데이터를 레벨단위로 저장한다. 지속적인 데이터 입력으로 인하여 레벨의 크기를 초과하게 되면 하위 레벨의 SST 파일과 병합을 통해 하위레벨로 내려 보낸다. 이 과정에서 디바이스의 부가적인 쓰기가 발생한다. 본 논문에서는 RocksDB의 디스크영역에 있는 SST 파일의 크기가 디바이스의 쓰기 증폭에 미치는 영향을 분석하였다. SST 파일크기변화에 따른 디바이스의 쓰기 증폭과 성능변화를 측정하고 비교하였다. 실험결과를 통해 SST의 크기가 작을수록 쓰기 증폭이 줄었지만 디바이스의 쓰기와 읽기 성능이 감소하는 것을 확인하였다. 결과적으로 쓰기 증폭을 줄이고 성능을 최대화 하기 위해서는 이 둘의 트레이드오프를 파악하고 분석하여 시스템에 맞는 최적의 SST 파일 크기를 찾아야한다.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1243-1249
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• 2016

Background: Expression of p53, cyclin D1, p21 (WAF1) and Ki-67 (MIB1) was evaluated in oral squamous cell carcinoma (OSCC) to test whether levels of these markers at invasive tumour fronts (ITFs) could predict the development of local recurrence. Materials and Methods: Archived paraffin-embedded specimens from 51 patients with T1/T2 tumours were stained immunohistochemically and analysed quantitatively. Local recurrence-free survival was tested with Kaplan-Meier survival plots (log-rank test) using median values to define low and high expression groups and with a Cox's proportional hazards model in which the expression scores were entered as continuous variables. Results: The assessment of expression of all markers was highly reliable, univariate analysis showing that patients with clear surgical margins, with low cyclin D1 and high p21 expression at the ITF had the best local recurrence-free survival. Multivariate analysis showed that these three parameters were independent prognostic factors but that neither p53 nor MIB1 expression were of prognostic value. Conclusions: Assessment of p53, cyclin D1, p21 (WAF1), and Ki-67 (MIB1) at the ITF could help to predict local recurrence in early stage oral squamous cell carcinoma cases.