Earticle

The rapid proliferation of encrypted traffic in modern networks presents significant challenges for security monitoring and threat detection. While encryption enhances privacy, it also provides cover for malicious activities, making traditional deep packet inspection ineffective. To address this challenge, this paper proposes an interpretable and efficient deep learning framework for malicious encrypted traffic identification. Our model integrates 1D-CNN, BiLSTM, and a lightweight self-attention mechanism to capture both spatial and temporal characteristics of network flows while providing explainable predictions through attention visualization. Unlike computationally intensive Transformer-based approaches, our method achieves an optimal balance between accuracy and efficiency, making it suitable for real-world deployment. Extensive experiments on benchmark datasets (USTC-TFC2016 and CICIDS-2017) demonstrate that our model achieves high accuracy with 0.82 ms inference time per flow, outperforming state-of-the-art methods while offering transparency in decision-making for security analysts. The proposed approach not only enhances detection performance but also provides operational interpretability, bridging the gap between automated threat detection and human-in-the-loop security operations.

With the rapid advancement of Internet services, there has been a dramatic increase in services that dynamically provide Internet resources on demand, such as cloud computing. In a cloud computing service, because the number of users in the cloud is changing dynamically, it is more efficient to utilize a flexible network technology such as software-defined networking (SDN). However, to efficiently support the SDN-based cloud computing service with limited resources, it is important to effectively manage the flow table at the SDN switch. Therefore, in this paper, a new flow management scheme is proposed that is able to, through efficient management, speed up the flow-entry search speed and simultaneously maximize the number of flow entries. The proposed scheme maximizes the capacity of the flow table by efficiently storing flow entry information while quickly executing the operation of flow-entry search by employing a hash index. In this paper, the proposed scheme is implemented by modifying the actual software SDN switch and then, its performance is analyzed. The results of the analysis show that the proposed scheme, by managing the flow tables efficiently, can support more flow entries.

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

Proxy Mobile IPv6 (PMIPv6) is a network-based mobility support protocol and it does not require Mobile Nodes (MNs) to be involved in the mobility support signaling. In the case when multiple interfaces are active in an MN simultaneously, each data flow can be dynamically allocated to and redirected between different access networks to adapt to the dynamically changing network status and to balance the workload. Such a flow redistribution control is called "flow mobility". In the existing PMIPv6-based flow mobility support, although the MN's logical interface can solve the well-known problems of flow mobility in a heterogeneous network, some missing procedures, such as an MN-derived flow handover, make PMIPv6-based flow mobility incomplete. In this paper, an enhanced flow mobility support is proposed for actualizing the flow mobility support in PMIPv6. The proposed scheme is also based on the MN's logical interface, which hides the physical interfaces from the network layer and above. As new functional modules, the flow interface manager is placed at the MN's logical interface and the flow binding manager in the Local Mobility Anchor (LMA) is paired with the MN's flow interface manager. They manage the flow bindings, and select the proper access technology to send packets. In this paper, we provide the complete flow mobility procedures which begin with the following three different triggering cases: the MN's new connection/disconnection, the LMA's decision, and the MN's request. Simulation using the ns-3 network simulator is performed to verify the proposed procedures and we show the network throughput variation caused by the network offload using the proposed procedures.

The examination on the operating mechanism of a pulsating heat pipe (PHP) using visualization revealed that the working fluid in the PHP oscillated to the axial direction by the contraction and expansion of vapor plugs. This contraction and expansion is due to the formation and extinction of bubbles in the evaporating and condensing section, respectively. In this paper, a theoretical model of PHP was presented. The theoretical model was based on the separated flow model with two liquid slugs and three vapor plugs. The results show that the diameter, surface tension and charge ratio of working fluid have significant effects on the performance of the PHP. The following conclusions were obtained. The periodic oscillations of liquid slugs and vapor plugs were obtained under specified parameters. When the hydraulic diameter of the PHP was increased to d=3mm, the frequency of oscillation decreased. By increasing the charging ratio from 40 to 60 by volume ratio, the pressure difference between the evaporating section and condensing section increased, the amplitude of oscillation reduced, and the oscillation frequency decreased. The working fluid with higher surface tension resulted in an increase in the amplitude and frequency of oscillation. Also the average temperature of vapor plugs decreased.

The Yellow River Delta (YRD) wetlands are the largest coastal wetlands in China, and it serves to control soil erosion, nourish the climate and protect biodiversity. At present, due to climate change and human activities, the wetlands of the YRD are facing ecological and environmental problems such as species invasion, vegetation degradation, and biodiversity reduction. In order to study the evolution of wetland landscape types more intuitively, this paper proposed a semantic segmentation network based on the encoder and decoder structure of ResNet-18. Then, the wetland landscapes in the YRD were classified into five types by combining the Landsat series of remote sensing images. In addition, this paper used the optical flow algorithm to visualize the identification results, which can represent the evolution pattern of wetland landscape types in different years. The results of this paper have an important significance for the subsequent development planning and protection in the YRD.

The popularity of the Internet introduces many network-enabled services that can be accessed by the user. But the adversaries are trying to deny these critical services to the user through Denial of Service (DoS) attacks. Presently, dealing with DoS attack which targets the application layer using slow traffic rate is one of the key challenges faced by the service providers. In this paper, a deep classification model using flow data is proposed to detect slow DoS attack on HTTP. The classifier is evaluated using CICIDS2017 dataset. The results obtained show that the classifier can obtain 99.61% accuracy.

Climate change has worsened droughts and floods, and created conditions more likely to lead to pathogen contamination of surface water and groundwater. Thus, there is a growing need to disinfect livestock water. Ultraviolet (UV) irradiation is widely accepted as an appropriate method for disinfecting livestock water, as it does not produce hazardous chemical compounds and kills pathogens. However, UV-based disinfection inevitably consumes electricity, so it is necessary to improve UV disinfection effectiveness. Aluminum-based reflective nanolens arrays that enhanced the effectiveness of a continuous-flow UV water disinfection system were developed using electrochemical and chemical processes, including electropolishing and two-step anodization. A continuous UV disinfection system was custom designed and the parts were produced using a three-dimensional printer. Electropolished aluminum was anodized at 40 and 80 V in 0.3 M oxalic acid, at 120 and 160 V in 1.0 M phosphoric acid, and at 200 and 240 V in 1.5 M citric acid. The average nanolens diameters (D) of the aluminum-based reflective nanolens arrays prepared using 40, 80, 120, 160, 200, and 240 V anodization were 95.44, 160.98, 226.64, 309.90, 296.32, and 339.68 nm, respectively. Simple UV reflection behind irradiated water disinfected Escherichia coli O157:H7 in water more than did the non-reflective control. UV reflection and focusing behind irradiated water using an aluminum-based reflective nanolens array disinfected E. coli O157:H7 more than did simple UV reflection. Such enhancement of the UV disinfection effectiveness was significantly effective when a nanolens array with D 226.64 nm, close to the wavelength of the irradiated UV (254 nm), was used.

As a new entertainment and social way, online games now have a huge and increasing user group, so it is of great significance to identify the data stream of online games. Using the excellent nonlinear fitting ability of BP neural network and the advantages of global search of genetic algorithm, the initial weights and thresholds of BP neural network are optimized, and the BP neural network model optimized by genetic algorithm is established. The muti-dimensional input information is proposed to identify online game data streams. Through the experimental simulation, it shows that the selected muti-dimensional information and the established model can be well applied to online game stream recognition.

기후 변화와 토지 개발로 인해 산지재난의 규모가 대형화되고 그 발생빈도 또한 증가하고 있다. 국토의 64%가 산지로 구성되어 있으며 대부분의 강우가 여름철에 집중되어 있는 우리 나라는 다양 한 산지재난에 취약한 특징을 가지고 있다. 특히, 산사태, 토석류와 같은 산지 재난의 발생 빈도가 높아지면서 산지 재난 저감을 위한 대책 마련이 요구되고 있다. 본 연구에서는 토석류 발생 현장에 대한 조사를 바탕으로 토석류를 모의하고 실제 피해가 발생된 시설물에 대한 취약성을 평가하였다. 모의에 따르면 실제 토석류 피해지역과는 약 62% 정확도로 일치하였고, 실제 피해가 발생된 시설물 이 위치한 구간에서는 약 2.0~24.8kPa의 충격력이 발생하였다. 또 취약성은 0.6 보다 높은 것으로 나타났다.

The scale of mountain disasters and the frequency of their occurrence are increasing due to climate change and land development. The country of 64% is composed of mountainous areas and most of the rainfall is concentrated in summer, making Korea vulnerable to mountain disasters. In particular, as the frequency of landslides and debris flow increases, countermeasures to reduce the mountain disasters are required. In this study, we simulated the debris flow based on the investigation on site where debris flows occurred and evaluated the vulnerability of the facilities that actually damaged. The simulation result coincided with an accuracy of about 62% for the area damaged by the actual debris flow. The impact forces about 2.0 to 24.8 kPa were generated in the section where the actual damage occurred. In addition, the vulnerability was found to be higher than 0.6.

To promote process effectiveness and efficiency, it is necessary that port logistics employ automated equipments for handling containers. There exists a system for automatically managing the container flow, called Control Module. However, it has limitation to assign the execution order to the machine and monitor the container flow in real time process. Business process management (BPM) provides a suitable and effective framework to address this problem including controlling and monitoring the flow of each container. Since the nature of container handling process is different with the common process in BPM that is conducted by human performer, it is necessary to adjust the BPM framework in the domain of port logistic management. This study presents a BPM framework corresponds with both human-based and machine-based activity to enhance the efficiency of port process flow including container flow. This framework is introduced as an integrated approach and mechanism of BPM application into the container handling system for the purpose of port logistics process automation.

감염병 재난은 단기적 충격을 받는 기존의 재난과는 달리 수 년간 지속될 수 있다는 점에서 차별화된다. 또한, 감염병은 감염 여부에 따른 발생 흐름에 따라 취약성이 변할 수 있는 만큼, 재난 대응 시에도 동적인 개념의 접근이 필요하다. 이에 본 연구는 감염병의 감염여부에 따른 시간적 흐름에 따라 취약성의 변화를 살펴보기 위해, 시군구 단위의 감염병 취약성을 감염 취약성과 건강 취약성으로 세분화하여 살펴보았다. 분석 결과, 감염 취약성과 건강 취약성은 높은 음의 상관관계를 보임을 확인할 수 있었다. 도시적 성격이 강하고 인구밀도가 높은 수도권 지역일수록 감염위험이 높은 경향을 보인 반면, 인구가 많지 않거나 인구유출 현상이 나타나는 지역, 인프라 구축이 상대적으로 좋지 않은 지역의 경우 감염위험 은 낮았지만 건강위험이 높은 것으로 나타났다. 이러한 결과는 감염병 재난 대응에서 취약성의 복합적이 고 지역 특화된 접근이 필요함을 시사한다.

Infectious disease outbreaks differ from traditional disasters in that they can last for several years, leading to prolonged impacts rather than short-term shocks. Vulnerability to these outbreaks also changes over time as the disease evolves, requiring a flexible and dynamic response. This study explores the temporal changes in infectious disease vulnerability at the municipal level, focusing on two aspects: “infection risk vulnerability” and “health risk vulnerability.” The findings show a strong negative correlation between these two types of vulnerability. Urbanized areas, like metropolitan regions, tend to have higher infection risk, while areas with smaller or declining populations face lower infection risk but higher health vulnerability. These results emphasize the need for tailored, region-specific strategies in managing infectious disease outbreaks, considering the distinct vulnerability profiles of each area.

게임에서의 스토리는 상호작용 할 수 있는 인터렉티브 스토리텔링이라는 점에서 사용자의 몰입 을 유도한다. 이러한 인터렉티브 스토리텔링은 기존의 이야기의 선형 구조와 달리 비선형 구조를 띄고 있기 때문에 기존의 서술구조와는 다른 서술구조가 연구되어왔다. 크게 사건 중심인 트리 기반 서술구조, 제약 기반 서술구조, 캐릭터 중심인 캐릭터 기반 서술구조가 있다. 트리 기반 서 술구조는 HTN, HSP등 여러 알고리즘으로 발전되었고, 분기가 많을수록 트리의 크기가 커진다는 단점과 이야기의 자유도가 떨어진다는 단점이 존재하였고, 캐릭터 기반 서술구조의 경우 사건이 아닌 캐릭터를 설계한 다음 캐릭터가 자유롭게 행동하게 하여 이야기를 진행하는 방식으로 사용 자가 몰입하는 대상이 캐릭터라는 점에서 게임에 더 적합할 수는 있지만, 캐릭터의 행동을 세밀 하게 설계하기 힘들다는 단점이 존재한다. 본 연구는 이 중 제약 기반 서술구조를 전체 이야기의 흐름 파악과 다양한 사건전개가 용이하도록 새로운 태그들을 제시하여 재설계하였다. 새롭게 제 시된 <event>라는 태그는 이야기의 흐름 파악을 쉽게 할 수 있게 하고, <plot>이라는 태그는 다 양한 사건전개가 용이하도록 설계되었다. 제안하는 서술구조를 이용하여 예시로 이솝우화 중 토 끼와 거북이에 적용하였다.

The story in the game induces the user 's immersion in that it is an interactive storytelling. Since the interactive storytelling has a nonlinear structure unlike the existing linear structure of the story, a narrative structure different from the existing narrative structure has been studied. There are largely case-based tree-based narrative structure, constraint-based narrative structure, and character-based narrative structure. Tree-based narrative structure has developed to various algorithms such as HTN and HSP. There are disadvantages that the size of tree becomes larger as the number of branches increases and that the degree of freedom of story is lowered. In the case of character-based narrative structure, this narrative structure designs the character, not the events, and lets the character to act freely. it could be more suitable for the game because the player immerses in the character. There is a disadvantage that it is difficult to design the behavior of the character elaborately. This study redesigned the constraint - based narrative structure by presenting new tags to facilitate the understanding of the whole process of the story and various events. The newly proposed <event> tag is designed for easier understanding of the story flow, and the <plot> tag is designed to facilitate development of various events. This study applies the suggested narrative structure to “The Tortoise and the Hare“ in Aesop's fables as an example.

We propose a novel programmable miniature vision module based on a custom designed analog VLSI (aVLSI) chip. The vision module consists of the optical flow vision sensor embedded with commercial off-the-shelves digital hardware; in our case is the Intel XScale PXA270 processor enforced with a programmable gate array device. The aVLSI sensor provides gray-scale imager data as well as smooth optical flow estimates, thus each pixel gives a triplet of information that can be continuously read out as three independent images. The particular computational architecture of the custom designed sensor, which is fully parallel and also analog, allows for efficient real-time estimations of the smooth optical flow. The Intel XScale PXA270 controls the sensor read-out and furthermore allows, together with the programmable gate array, for additional higher level processing of the intensity image and optical flow data. It also provides the necessary standard interface such that the module can be easily programmed and integrated into different vision systems, or even form a complete stand-alone vision system itself. The low power consumption, small size and flexible interface of the proposed vision module suggests that it could be particularly well suited as a vision system in an autonomous robotics platform and especially well suited for educational projects in the robotic sciences.

기저유출은 지표하를 통하여 느리게 하천으로 유입되며 하천 관리에 있어서 중요한 요소이다. 기저유출의 정확한 파악을 위하여 본 연구에서 활용된 주지하수감수곡선(MRC) 방법을 포함한 다양한 방법들이 연구되었지만, 측정 불가능한 기저유출의 특성상 정량적인 평가는 어렵다. MRC를 활용한 선행 연구들은 연구 기간 내에 존재하는 모든 감수부를 활용하였으며 이는 국내환경에서 부정확한 MRC를 유도하였다. 본 연구는 기존에 행해지던 주지하수감수곡선(MRC) 분리방법을 국내 특성을 고려하여 계절과 유황특성으로 구분하고 기저유출 분리에 적용하였다. 연구대상지역은 한강, 낙동강 그리고 금강수계에서 각 3곳의 유량관측점을 선정하여 총 9 곳이며, 수리구조물의 영향이 없도록 상류지역에서 선정하였다. MRC를 도출하기 위하여 기존에 제작된 프로그램을 사용하였으며, 관측점 별로 총 세 개의 MRC를 도출하였다. 전체 기간에 대한 MRC와 본 연구에서 구분한 계절과 유황을 고려한 MRC 두 가지이다. 유황을 고려한 MRC는 낮은 R2값과 감수곡선과 비슷한 추세의 MRC를 도출하였다. 계절을 고려한 MRC의 경우 기저유출분리에 적합한 양상을 보여주었으며 계절별 특성이 뚜렷하게 반영된 MRC를 도출하였다. 두 가지 방법에 따라 도출된 MRC를 비교하였을 때, 계절을 고려한 MRC는 기존의 MRC를 사용한 분리과정에서 과산정 되었던 기저유출량이 감소되고 안정되게 분리되었다. 유황을 고려한 MRC의 경우 그래프 상의 감수부가 다양한 감수양상을 가지고 있었으며 이에 따라 낮은 R2값의 MRC가 도출되었다. 따라서 기저유출을 분리하기 위해선 계절을 고려한 MRC가 더 높은 정확성을 보일 것으로 판단되며, 유황을 고려한 MRC의 경우, 추가적인 보정 작업을 통해서 신뢰도 높은 MRC의 도출이 필요할 것으로 판단된다.

Baseflow which is one of the unmeasurable components of streamflow and slowly flows through underground is important for water resource management. Despite various separation methods from researches preceded, it is difficult to find a significant separation method for baseflow separation. This study applied the MRC method and developed the improved approach to separate baseflow from total streamflow hydrograph. Previous researchers utilized the whole streamflow data of study period at once to derive synthetic MRCs causing unreliable results. This study has been proceeded with total nine areas with gauging stations. Each three areas are selected from 3 domestic major watersheds. Tool for drawing MRC had been used to draw MRCs of each area. First, synthetic MRC for whole period and two other MRCs were drawn following two different criteria. Two criteria were set by different conditions, one is flow condition and the other is seasonality. The whole streamflow was classified according to seasonality and flow conditions, and MRCs had been drawn with a specialized program. The MRCs for flow conditions had low R2 and similar trend to recession segments. On the other hand, the seasonal MRCs were eligible for the baseflow separation that properly reflects the seasonal variability of baseflow. Comparing two methods of assuming MRC for baseflow separation, seasonal MRC was more effective for relieving overestimating tendency of synthetic MRC. Flow condition MRCs had a large distribution of the flow and this means accurate MRC could not be found. Baseflow separation using seasonal MRC is showing more reliability than the other one, however if certain technique added up to the flow condition MRC method to stabilize distribution of the streamflow, the flow conditions method could secure reliability as much as seasonal MRC method.

In Korea, where 63% of the land is mountainous, damage caused by shallow landslides is increasing annually. Therefore, it is crucial to evaluate shallow landslide and debris flow risks at the small mountain watershed scale and devise effective mitigation measures. This study assessed the potential for shallow landslide initiation and debris flow extent in a 16-ha small mountain watershed in Mungyeong-si, Gyeongsangbuk-do, using physics-based models, and evaluated the impact of check dam installation on damage reduction. TRIGRS (USGS) was employed for landslide simulation and RAMMS (WSL) for debris flow simulation. Both models used a 5-m DEM, and model parameters were estimated based on field measurements and conditions of nearby affected watersheds. TRIGRS simulation results identified 17% of the watershed as unstable (FS < 1), and potential collapse points were selected by comparing with the landslide hazard map. RAMMS simulations based on these points showed a debris flow area of 10.43 ha without a check dam, which decreased to 8.37 ha with the dam installed. Notably, debris flow impact downstream of the check dam was reduced by 78% after installation, significantly mitigating risk to nearby infrastructure. This study empirically examines the applicability of a physics-based model and the mitigation effect of check dams, and it is expected to serve as foundational data for planning related to mountain sediment disasters.

본 연구에서는 한국을 방문한 개별 여행자들의 디지털 기록을 수집하여 정량적 통계 분석과 소셜 네트워크 분석(SNA)을 통해 한국을 방문하는 개별 중국 여행자들의 한국 관광 경로의 특징을 분석하였다. 연구결과 서울, 제주 도, 부산 및 대구는 한국을 찾는 중국 여행자들의 주요 방문 장소이며, 중국의 청도, 천진, 심양, 홍콩, 포산 및 마카오는 한국을 찾는 중국 개별 여행자들의 주요 중계지 임을 알 수 있었다. 본 연구는 한국을 찾는 중국 개별 여행자들의 표본 특성과 각 여행 노드의 기능적 위치설정을 정확히 확인함으로써 정밀한 관광 마케팅과 관광 노선 개발에 활용할 수 있는데 의의가 있다. 향후 본 연구에 사용된 데이터의 추출 기간을 확대하고 더 많은 샘플을 확보하여 관광 경로의 연간 변동특성과 주요 방문지의 변동 특성을 분석할 필요가 있다.

This study takes Chinese independent tourists to South Korea as the research object, mines the data of tourists’ digital footprints from online travel notes, and analyzes the characteristics of the tourism flow of Chinese independent tourists to South Korea by using the method of quantitative statistics and social network analysis(SNA). The results show that Seoul, Jeju Island, Busan and Daegu are the important tourist destinations for Chinese independent tourists entering South Korea. In addition, Qingdao, Tianjin, Shenyang, Hong Kong, Foshan and Macao are crucial hubs for Chinese independent tourists to visit South Korea. In future studies, the number of sample data should be increased. The time span of data collection should be extended for studying the annual variation characteristics of tourism flow and the trend of tourism hot spots.