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온라인게임 서비스 분야에 정보보호 사전진단 적용시 효과성에 관한 연구
유동영(Dong-Young Yoo),서동남(Dong-Nam Seo),김휘강(Huy Kang Kim),최진영(Jin Young Choi) 한국IT서비스학회 2011 한국IT서비스학회지 Vol.10 No.2
The preliminary security assessment is an information security process to analyze security weaknesses before beginning of services. Discovering security weakness through preliminary security assessment is highly required because it costs much when security incident occur in the middle of service operation. However, this assessment is not widely spread in the online game service domain yet. In this paper, we summarize the security risk existed in the online game service, and we classify the security requirements related to the each risk. Also, through the case study, we evaluated the effectiveness of preliminary security assessment ín this domain. In addition, we suggest checklists that should be reviewed once in game-client side, network-side and game-server síde for the purpose of security enhancement.
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Zhang Song,Yoo Dong Huy,Ao Xiang,김인호 아세아·태평양축산학회 2020 Animal Bioscience Vol.33 No.10
Objective: This study was conducted to investigate the effects of dietary probiotic blend and liquid feed program at different nutritional densities on growth performance, nutrient digestibility, fecal score of weaning piglets. Methods: A total of 120 weaning pigs with an initial body weight of 7.05±0.93 kg per pig (21 days of age) were randomly allocated into 1 of the following 8 dietary treatments (3 replicates per treatment with 5 pigs per replicate) in a 2×2×2 factorial arrangement (nutrition levels: apparent metabolic energy [AME] = 3,500 kcal/kg, crude protein [CP] = 20% vs AME = 3,400 kcal/kg, CP = 19.42%; feed types:dry vs wet; probiotics levels: 0 mg/kg vs 300 mg/kg). Results: During d 5 to d 15, greater average daily gain (ADG) and average daily feed intake (ADFI) (p<0.05) were observed in probiotics treatments. During d 15 to d 25, gain:feed (G:F) ratio (p<0.05) were significantly improved in probiotics, wet feed and high nutrition diet. Moreover, two interactions i) between nutrition levels and feed types, and ii) between nutrition levels and probiotics were found in G:F ratio. Furthermore, there was a significant positive interaction on G:F among those 3 factors (p<0.05). Overall, increasing ADG, ADFI, and G:F ratio were detected in probiotics treatment significantly (p<0.05). Besides, an obvious reduction on fecal score was observed in probiotics treatment from d 0 to d 5 (p<0.05). There was an interactive effect on fecal score between feed types and nutrition concentrations from d 5 to d 25 (p<0.05). Conclusion: These results indicated that probiotics supplementation could benefit growth performance and reduce the frequency of watery feces. Besides, wet feed program (feed:water = 1:1.25) could improve the G:F. The effect of liquid feed or probiotic could be influenced by dietary nutrition density in weaned piglets. An increased value of G:F was obtained when wet feeding a high nutrition diet (100 kcal higher than NRC 2012 recommendations) was supplemented with probiotics for 15 to 25 days.
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A Modified YoloV4 Network with Medium-Scale Challenging Benchmark for Efficient Animal Detection
Habib Khan,Bui Quang Huy,Zain Ul Abidin,Juhee Yoo,Minho Lee,Kyeong Wook Seo,Dong Yun Hwang,Mi Young Lee,Jae Kyu Suhr 한국차세대컴퓨팅학회 2023 한국차세대컴퓨팅학회 학술대회 Vol.2023 No.06
Animal detection and classification are crucial for effective wildlife management (WM) and reducing risks associated with animals related road accidents and attacks. Previous attempts trained the models using imbalanced data with fewer representative features and baseline models without improvement. This paper presents a new dataset of five animal classes captured in various poses, lighting conditions, and intraclass variations. The standard coupled detection head of the YoloV4 algorithm faces limitations when performing simultaneous classification and localization due to shared parameters and inputs. To address this issue, we propose a decoupled detection head (DDH) that handles these tasks separately, improving performance. We conducted extensive experiments using the proposed dataset. We found that the optimal backbone features marginally improve the performance of the modified network compared to state-of-the-art (SOTA) works in the subject domain. Our work contributes by addressing the limitations of the standard YoloV4 algorithm and proposing a new dataset for researchers to use in future studies.
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공격 기법 모델링을 통한 사이버 공격 시뮬레이터 설계 및 구현
강용구(Yong Goo Kang),유정도(Jeong Do Yoo),박은지(Eunji Park),김동화(Dong Hwa Kim),김휘강(Huy Kang Kim) 한국컴퓨터정보학회 2020 韓國컴퓨터情報學會論文誌 Vol.25 No.3
정보 기술의 발달과 시스템 및 네트워크의 규모가 증가함에 따라 사이버 위협 및 범죄가 꾸준히 증가하고 있다. 이러한 위협에 대응하기 위해서 실질적인 공격과 방어 기반의 사이버 보안 훈련이 필요하다. 그러나 사이버 보안 훈련은 전문가의 분석과 공격 수행능력을 요구하므로, 비용 및 시간적인 측면에서 비효율적이다. 본 논문에서는 공격 기법들을 자동으로 수행하는 사이버 공격 시뮬레이터를 제안한다. 이 시뮬레이터는 구현 가능하도록 모델링 된 공격 기법들을 조합하여 공격 시나리오를 도출하고, 도출된 시나리오들을 순차적으로 수행함으로써 공격을 수행한다. 제안하는 공격 시뮬레이터의 유효성을 검증하기 위해 실제 환경에서 예시 공격 목표와 시나리오를 설정하여 실험하였다. 이 공격 시뮬레이터는 5 가지 공격 기법을 자동으로 수행하여 관리자 권한을 획득하는 공격에 성공하였다. With the development of information technology and the growth of the scale of system and network, cyber threats and crimes continue to increase. To cope with these threats, cybersecurity training based on actual attacks and defenses is required. However, cybersecurity training requires expert analysis and attack performance, which is inefficient in terms of cost and time. In this paper, we propose a cyber attack simulator that automatically executes attack techniques. This simulator generates attack scenarios by combining attack techniques modeled to be implemented and executes the attack by sequentially executing the derived scenarios. In order to verify the effectiveness of the proposed attack simulator, we experimented by setting an example attack goal and scenarios in a real environment. The attack simulator successfully performed five attack techniques to gain administrator privileges.
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