• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37B no.11
• /
• pp.1082-1089
• /
• 2012

Recent malicious attempts in Cyber space are intended to emerge national threats such as Suxnet as well as to get financial benefits through a large pool of comprised botnets. The evolved botnets use the Domain Name System(DNS) to communicate with the C&C server and zombies. DNS is one of the core and most important components of the Internet and DNS traffic are continually increased by the popular wireless Internet service. On the other hand, domain names are popular for malicious use. This paper studies on DNS-based cyber threats domain detection by data classification based on supervised learning. Furthermore, the developed cyber threats domain detection system using DNS traffic analysis provides collection, analysis, and normal/abnormal domain classification of huge amounts of DNS data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.7
• /
• pp.3191-3196
• /
• 2011

Smart home system are being installed in the most new construction of building for the convenience of living life. As smart home systems are becoming more common and their diffusion rates are faster, hacker's attack for the smart home system will be increased. In this paper, Risk level of smart home's to do respond to intrusion that occurred from the wired network and wireless network intrusion cases and attacks can occur in a virtual situation created scenarios to build a database. This is based on the smart home users vulnerable to security to know finding illegal intrusion traffic in real-time and attack prevent was designed the intrusion detection algorithm.

• Journal of information and communication convergence engineering
• /
• v.6 no.3
• /
• pp.294-300
• /
• 2008

This study was conducted to investigate what to consider for active response in the intrusion detection system, how to implement active response, and 6-phase response models to respond actively, including the active response scheme to detect unknown attacks by using a traffic measuring engine and an anomaly detection engine.

• ETRI Journal
• /
• v.32 no.2
• /
• pp.241-247
• /
• 2010

We propose and experimentally demonstrate a service-aware optical transport system. The proposed service-aware optical transport system makes a flow based on service type and priority of traffic. The generated flow is mapped to a corresponding sub-${\lambda}$ for transport over an optical network. Using sub-${\lambda}$ provided by the centralized control plane, we could effectively provide quality-of-service guaranteed Ethernet service and best-effort service simultaneously in a single link. The committed information rate (CIR) traffic and best-effort traffic are assigned to different sub-${\lambda}s$. The bandwidth of the CIR traffic is guaranteed without being affected by violation traffic because the bandwidth is managed per each sub-${\lambda}$. The failure detection time and restoration time from a link failure is measured to be about 60 ${\mu}s$ and 22 ms, respectively, in the ring network. The measured restoration time is much smaller than the 50 ms industry requirement for real-time services. The fast restoration time allows the proposed service-aware optical transport system to offer high availability and reliability which is a requirement for transport networks.

• Journal of Navigation and Port Research
• /
• v.44 no.2
• /
• pp.110-118
• /
• 2020

With the expansion of the shipping and port logistics industry in the 21st century, the traffic density is continuously increased because of the increase in volumes of world sea freight and fleets, as well as the increase in the causes of potential marine accidents, such as ship collisions and stranding. Accordingly, the International Maritime Organization (IMO) has requested that the installation and operation of VTS should be applied in areas with high risk of marine traffic, and the request should be included as one of the Safety of Life at Sea (SOLAS) regulations. In this paper, the fundamental requirements of the radar system for vessel traffic services were analyzed and the analyzing factors were based on the IALA guideline.s This paper also includes results for the requirement and recommendation analysis on detection distance, target separation, and the target position accuracy of X-band radar. Also, to check if it satisfies the requirement of detection distance, range and azimuth separation of small point targets, and target position accuracy from the IALA guidelines, the test was conducted through the radar image acquired at the VTS center, and hence, the validity of the technical performance requirements was confirmed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.2
• /
• pp.36-54
• /
• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.449-456
• /
• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.4
• /
• pp.11-19
• /
• 2000

Real-time extraction of traffic information such as the number of vehicles passing, speed, road-occupancy rate, distance between vehicles, and vehicle types from the traffic scenes acquired from the camera on the road, is a core component of the intelligent transportation system(lTS) We present a scheme of extracting the traffic informations based on the spatio-temporal image analysis, which is robust to the variation of weather conditions and the shades. The images of two detection regions for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shade, using the statistical and structural features Quantitative traffic informations are retrieved by analysing the two spatio-temporal images. Since only the local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized while ensuring the detection performance robust to the operating condition.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.4
• /
• pp.6-15
• /
• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• Journal of Information Processing Systems
• /
• v.1 no.1 s.1
• /
• pp.27-31
• /
• 2005

Vehicle detector system based on image processing technology is a significant domain of ITS (Intelligent Transportation System) applications due to its advantages such as low installation cost and it does not obstruct traffic during the installation of vehicle detection systems on the road[1]. In this paper, we propose architecture for vehicle detection by using image processing. The architecture consists of two main parts such as an image processing part, using high speed FPGA, decision and calculation part using CPU. The CPU part takes care of total system control and synthetic decision of vehicle detection. The FPGA part assumes charge of input and output image using video encoder and decoder, image classification and image memory control.