• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• Journal of the Korea Society of Computer and Information
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• v.6 no.4
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• pp.131-137
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• 2001

This paper discussed to the ATM traffic measurement and analysis tool for analyzing the ATM traffic properties. This tool was applied at the ATM commercial network. The analysis result is verified effectivity to improve network resource from 20％ to 50％. Thus, this tool usefully can be used to network plan for the network expansion and new network building. Also, it can be used to the demand estimation of the ATM network traffic.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.182-191
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• 2012

This paper proposes a high performance QoS (Quality of Service) traffic transmission scheme to provide real-time multimedia services in wireless networks. This scheme is based on both a traffic estimation of the mean rate and a header compression method by dividing this network model into two parts, core RTP/UDP/IP network and wireless access parts, using the IEEE 802.11 WLAN. The improvement achieved by the scheme means that it can be designed to include a means of provisioning the high performance QoS strategy according to the requirements of each particular traffic flow by adapting the header compression for real-time multimedia data. A performance evaluation was carried out to show the effectiveness of the proposed traffic transmission scheme.

• IE interfaces
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• v.23 no.4
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.81-90
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• 2006

It is important to clarify the relationship between traffic accidents and various influencing factors in order to reduce the number of traffic accidents. This study developed a traffic accident frequency prediction model using by multi-linear regression and qualification theories which are commonly applied in the field of traffic safety to verify the influences of various factors into the traffic accident frequency The data were collected on the Korean National Highway 17 which shows the highest accident frequencies and fatality rates in Chonbuk province. In order to minimize the uncertainty of the data, the fuzzy theory and neural network theory were applied. The neural network theory can provide fair learning performance by modeling the human neural system mathematically. Tn conclusion, this study focused on the practicability of the fuzzy reasoning theory and the neural network theory for traffic safety analysis.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1544-1553
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• 2017

The network coding mechanism has attracted much attention because of its advantage of enhanced network throughput which is a desirable characteristic especially in a multi-hop wireless network with limited link capacity such as the device-to-device (D2D) communication network of 5G. COPE proposes to use the XOR-based network coding in the two-hop wireless network topology. For multi-hop wireless networks, the Distributed Coding-Aware Routing (DCAR) mechanism was proposed, in which the coding conditions for two flows intersecting at an intermediate node are defined and the routing metric to improve the coding opportunity by preferring those routes with longer queues is designed. Because the routes with longer queues may increase the delay, DCAR is inefficient in delivering real-time multimedia traffic flows. In this paper, we propose a network coding-aware routing protocol for multi-hop wireless networks that enhances DCAR by considering traffic load distribution and link quality. From this, we can achieve higher network throughput and lower end-to-end delay at the same time for the proper delivery of time-sensitive data flow. The Qualnet-based simulation results show that our proposed scheme outperforms DCAR in terms of throughput and delay.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.87-97
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• 2009

A Mobile Ad hoc Network (MANET) is characterized by multi-hop wireless connectivity, frequently changing network topology with mobile nodes and the efficiency of the dynamic routing protocol plays an important role in the performance of the network. In this paper, the performance of five routing protocols for MANET is compared by using OPNET modeler: AODV, DSR, GRP, OLSR and TORA. The various performance metrics are examined, such as packet delivery ratio, end-to-end delay and routing overhead with varying data traffic, number of nodes and mobility. In our simulation results, OLSR shows the best performance in terms of data delivery ratio in static networks, while AODV has the best performance in mobile networks with moderate data traffic. When comparing proactive protocols (OLSR, GRP) and reactive protocols (AODV, DSR) with varying data traffic in the static networks, proactive protocols consistently presents almost constant overhead while the reactive protocols show a sharp increase to some extent. When comparing each of proactive protocols in static and mobile networks, OLSR is better than GRP in the delivery ratio while overhead is more. As for reactive protocols, DSR outperforms AODV under the moderate data traffic in static networks because it exploits caching aggressively and maintains multiple routes per destination. However, this advantage turns into disadvantage in high mobility networks since the chance of the cached routes becoming stale increases.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.15-21
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• 2004

One of the most important issues in designing a network and realizing a service is dealing with traffic characteristics. Recent experimental research on LAN, WAN, and VBR traffic properties has highlighted that real traffic specificities can not be displayed because the current models based on the Poisson assumption under estimate the long range dependency of network traffic and self-similar peculiarities. Therefore, a new approach using self-similarity characteristics as a real traffic model was recently developed. In This paper we discusses the definition of self-similarity traffic. Moreover, real traffic was collected and we generated self-similar data traffic like real traffic to background load. On the existing ABR congestion control algorithm transmission throughput with the representative ERICA, EPRCA and NIST switch algorithm show the efficient reaction about the burst traffic.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.323-333
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• 2012

Network traffic demand is increasing explosively because of various smart equipment and services on smart era. It causes of traffic overload for wireless and wired network. Network management system is very important to control the explosion of data traffic. It uses SNMP to communicate with various network resources for management functions and creates lots of management traffic. Those are can be serious traffic congestion on a network. I propose an improving function of SNMP to minimize unnecessary traffics between manager and agent for collecting the Trend Analysis Information which is mainly used to monitor and accumulate for a specific time period in this paper. The results of test show it has compatibility with the existing SNMP and greatly decreases the amount of network traffic and response time.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.4
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• pp.25-34
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• 2004

UMTS network, evolved from GSM, includes packet core network that consists of SGSNS and GGSNs. Service providers should consider subscriber mobility, location registration, and subscriber distribution when designing packet core networks and network elements. Since one of the major traffic sources for IMT-2000 will be data which has bursty characteristics, new design guidelines for dimensioning of SGSN and GGSN should be proposed under various constraints of system parameters. In this paper, we first evaluate the performance of signaling traffic for packet call subscribers. After that, we also obtain the impact of bursty data traffic on the SGSN and GGSN by simulation, and suggest new dimensioning guidelines for packet core network of UMTS under various environments.