• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.229-234
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• 2021

The explosive growth of video-based services is considered as the dominant contributor to Internet traffic. Hence it is very important for video service providers to meet the quality expectations of end-users. In the past, the Quality of Service (QoS) was the key performance of networks but it considers only the network performances (e.g., bandwidth, delay, packet loss rate) which fail to give an indication of the satisfaction of users. Therefore, Quality of Experience (QoE) may allow content servers to be smarter and more efficient. This work is motivated by the inherent relationship between the QoE and the QoS. We present a no-reference (NR) prediction model based on Deep Neural Network (DNN) to predict video QoE. The DNN-based model shows a high correlation between the objective QoE measurement and QoE prediction. The performance of the proposed model was also evaluated and compared with other types of neural network architectures, and three known machine learning methodologies, the performance comparison shows that the proposed model appears as a promising way to solve the problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.663-671
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• 2016

According to rapidly increasing of network traffics, necessity of high-speed router also increased. For various purposes, like traffic statistic and security, traffic measurement function should performed by router. However, because of the nature of high-speed router, memory resource of router was limited. RCC proposed a way to measure traffics with high speed and accuracy. Additional quadratic probing hashing table used for accumulating elephant flows in RCC. However, in our experiment, quadratic probing performed many overheads when allocated small memory space or load factor was high. Especially, quadratic requested many calculations in update and lookup. To face this kind of problem, we use a cuckoo hashing which performed a good performance in update and loop for enhancing the RCC. As results, RCC with cuckoo hashing performed high accuracy and speed even when load factor of memory was high.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1311-1322
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• 1997

Performance management of ATM network is urgently required because a different quality of service should be guaranteed on each connection. A lot of performance measurement data increase the burden on agent systems and on managment stations. In this paper, an effective OAM-based performance monitoring and faulty node identification technique is proposed. A proposed VP Selection Algorithm reduces management-related traffic and when the indication of hard or soft failure state is detected, failed node is identified by Fault Identification Rule.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.428-451
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• 2010

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.1
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• pp.109-118
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• 2024

Recently, a social issue has arisen involving RDDoS attacks following the sending of threatening emails to security administrators of companies and institutions. According to a report published by the Korea Internet & Security Agency and the Ministry of Science and ICT, survey results indicate that DDoS attacks are increasing. However, the top response in the survey highlighted the difficulty in countering DDoS attacks due to issues related to security personnel and costs. In responding to DDoS attacks, administrators typically detect anomalies through traffic monitoring, utilizing security equipment and programs to identify and block attacks. They also respond by employing DDoS mitigation solutions offered by external security firms. However, a challenge arises from the initial failure in early response to DDoS attacks, leading to frequent use of detection and mitigation measures. This issue, compounded by increased costs, poses a problem in effectively countering DDoS attacks. In this paper, we propose a system that creates detection rules, periodically collects traffic using mail detection and IDS, notifies administrators when rules match, and Based on predefined threshold, we use IPS to block traffic or DDoS mitigation. In the absence of DDoS mitigation, the system sends urgent notifications to administrators and suggests that you apply for and use of a cyber shelter or DDoS mitigation. Based on this, the implementation showed that network traffic was reduced from 400 Mbps to 100 Mbps, enabling DDoS response. Additionally, due to the time and expense involved in modifying detection and blocking rules, it is anticipated that future research could address cost-saving through reduced usage of DDoS mitigation by utilizing artificial intelligence for rule creation and modification, or by generating rules in new ways.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.997-1005
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• 2010

Recently, there has been a growing interest in the use of WLAN technology due to its easy deployment, flexibility and so on. Examples of WLAN applications range from standard internet services such as Web access to real-time services with strict latency/throughput requirements such as multimedia video and voice over IP on wireless network environments. Fair and efficient distribution of the traffic loads among APs(Access Points) has become an important issue for improved utilization of WLAN. This paper focuses on an AP selection scheme for achieving better load balance, and hence increasing network resource utilization for each user on wireless network environments. This scheme makes use of active scan patterns and the network delay as main parameters of load measurement and AP selection. This scheme attempts to estimate the AP traffic loads by observing the up/down delay and utilize the results to maximize the link resource efficiency through load balancing. We compared the proposed scheme with the original SNR(Signal to Noise Ratio)-based scheme using the NS-2(Network Simulation.2). We found that the proposed scheme improves the throughput by 12.5% and lower the network up/down link delay by 36.84% and 60.42%, respectively. All in all, the new scheme can significantly increase overall network throughput and reduce up/down delay while providing excellent quality for voice and video services.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.1
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• pp.15-22
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• 2015

Estimating the number of distinct values is really well-known problems in network data measurement and many effective algorithms are suggested. Recent works have built upon technique called Linear Counting to solve the estimation problem for massive sets or spreaders in small memory. Sampling is used to reduce the measurement data, and it is assumed that sampling gives bad effect on the accuracy. In this paper, however, we show that the sampling on multi-set estimation sometimes gives better results for CSE with sampling than for MCSE that examines all the packets without sampling in terms of accuracy and estimation range. To prove this, we presented mathematical analysis, conducted experiment with real data, and compared the results of CSE, MCSE, and CSES.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.608-617
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• 2011

ubiquitous network management system (u-NMS) is the network management system based on smartphone which are recently of wide use. The purpose of the u-NMS is to provide convenience for network administrator utilizing the mobility of smartphone and to manage the network efficiently. This paper proposes the smart NMS agent and the mobility management server (MMS). The smart NMS agent enables to use the monitoring web server and remote control application on the smartphone in wireless network. The MMS is developed to reduce the problems such as handover latency and packet loss, which can be taken place in wireless network. The network manager can monitor traffic in real time through the smart NMS agent and remotely control the network efficiently when sudden failures happen in the u-NMS. In this paper, performance evaluation is carried out with our test-bed system implemented. We focus on the measurement of the MMS performance. When the MMS is compared to previous mobility management protocol, our mobility management server reduces the average latency up to 65% in initial access, handover latency and processing delay to the network management center.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.516-528
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• 2015

In this paper, we propose mobile ad hoc network configuration and its autonomous network construction method for efficiency and scalability of media streaming for mobile smart devices. To provide scalable network configuration for streaming traffic distribution, an IEEE 802.11 infrastructure network and ad hoc networks are hierarchically built. The proposed method autonomously configures a hierarchical streaming network by competition based on performance and states of devices and the wireless network, not depending on any specific nodes. Finally, we conduct performance measurement for the proposed configuration and analyze the experimental result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.5
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• pp.452-459
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• 1992

In this paper, we have estimated voice traffics using Kalman-filtering for upcoming years and evaluated performance of a grid topology circuit switched network using above outcomes. Since measurement errors and modeling errors are considered in Kalman-filtering, the system is estimated more accurately than by using any other estimation methods. A grid topology circuit switched network has alternative routing paths, therefore it is more reliable than any other networks. In this paper, we have calculated the call blocking probabilities, which is the key measuremens of performance evaluation in circuit switched networks. by using estimated voice traffics for upcoming years.