• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.7
• /
• pp.2261-2280
• /
• 2014

Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence (PSS) signature. The proposed method generates unique PSS signatures for each application using packet order, direction and payload size of the first N packets in a flow, and uses them to classify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy rates, over 99.97%. Furthermore, the method can also classify application traffic that uses the same application protocol or is encrypted.

• Journal of Radiation Industry
• /
• v.8 no.3
• /
• pp.155-159
• /
• 2014

RI-Biomics is a new concept that combines radioisotopes (RI) and Biomics. For efficient collection of information, establishment of database for technical information system and its application to the system, there is an increasing need for constructing the standard classification system of technical information by its systematical classification. In this paper, we have summarized the development process of the standard classification system of technical information in the field of RI-Biomics and its application to the system. Constructing the draft version for the standard classification system of technical information was based on that standard classification one in national science and technology in Korea. The final classification system was then derived through the reconstruction and the feedback process based on the consultation from the 7 experts. These results were applied to the database of technical information system after transforming as standard code. Thus, the standard classification system were composed of 5 large classifications and 20 small classifications, and those classification are expected to establish the foundation of information system by achieving the circular structure of collection-analysis-application of information.

• Journal of Radiation Industry
• /
• v.9 no.1
• /
• pp.29-35
• /
• 2015

Radiation technology is the one for developing new products or processes by applying radiation or for creating new functions in industry, research and medical fields, and its application is increasing consistently. For securing an advanced technology competitiveness, it is required to create a new added value by information consumer through providing an efficient system for supporting information, which is the infrastructure for research and development, contributed to its collection, analysis and use with a rapidity and structure in addition to some direct research and development. Provision of the management structure for information resources is especially crucial for efficient operating the system for supporting information in radiation technology, and then a standard classification structure of information must be first developed as the system for supporting information will be constructed. The standard classification structure has been analyzed by reviewing the definition of information resources in radiation technology, and those classification structures in similar systems operated by institute in radiation and other scientific fields. And, a draft version of the standard classification structure has been then provided as 7 large, 25 medium and 71 small classifications, respectively. The standard classification structure in radiation technology will be developed in 2015 through reviewing this draft version and experts' opinion. Finally, developed classification structure will be applied to the system for supporting information by considering the plan for constructing this system and database, and requirements for designing the system. Furthermore, this structure will be designed in the system for searching information by working to the individual need of information consumers.

• Journal of Korean Medical classics
• /
• v.36 no.3
• /
• pp.89-128
• /
• 2023

Objectives : This study aims to diachronically examine the classification systems of all materia medica, followed by categorization and analysis of each category to deduce each category's characteristic. This will provide foundation for further examining classifications of bencao in contemporary herbology. Methods : Classification systems from a total of 93 bencao related texts were collected and categorized. Each category's classification system was analyzed to determine its meaning. The classification systems were compared from a diachronic perspective, to further deduce each system's problem from a historical context. Results : The classification systems of materia medica could be summarized as following three standards: quality, origin, and medical application. In reality, bencao could be generally classified according to origin and medical application. The origin-based classification system provided a stable and flexible classification outline in the expansion process of bencao. The medical application-based classification strengthened the relationship between bencao and illness pattern, improving clinical applicability. Conclusions : In the history of herbology, the two classification systems created the current of herbology through mutual contribution and conflict. We hope that further discussion on the direction towards which classification system of bencao in contemporary herbology should head will proceed based on this study.

• Journal of the Korean Society for Library and Information Science
• /
• v.50 no.2
• /
• pp.101-118
• /
• 2016

For the effective classification of complex subjects, a library classification scheme should adopt multiple division principles (or facets). Each of the multiple principles adopted for the division of complex subjects is sequentially applied at each stage of division. The order of application of these multiple principles during the process of division of complex subjects is called citation order. In order for a classification scheme to be consistent and logical, the citation order of division principles applied to classify complex subjects should be concrete and consistent. Especially, in case of enumerative classification system, decisions on citation order to represent complex subjects significantly affect the structure and organization of the classification system. There are basic principles and theoretical canons of the classification theory on the citation order and its application, but they cannot be applied solidly in the process of classification system development for practical reasons. Therefore, this paper first reviews previous works on classification theories regarding citation order, then explores the conditions and circumstances for the application of citation order.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.8B
• /
• pp.921-928
• /
• 2011

The increase of Internet users and services has caused the upsurge of data traffic over the network. Nowadays, variety of Internet applications has emerged which generates complicated and diverse data traffic. For the efficient management of Internet traffic, many traffic classification methods have been proposed. But most of the methods focused on the application-level classification, not the function-level classification or state changes of applications. The functional classification of application traffic makes possible the in-detail understanding of application behavior as well as the fine-grained control of applications traffic. In this paper we proposed automata based functional classification method of IM application traffic. We verified the feasibility of the proposed method with function-level control experiment of IM application traffic.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.5
• /
• pp.859-876
• /
• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• Journal of the Korean Society for Library and Information Science
• /
• v.48 no.4
• /
• pp.5-23
• /
• 2014

This study reports the first step in the Classification-based Search and Knowledge Discovery (CSKD) project, which aims to combine information organization and retrieval approaches for building digital library applications. In this study, we explored the generation and application of a faceted vocabulary as a potential mechanism to enhance knowledge discovery. The faceted vocabulary construction process revealed some heuristics that can be refined in follow-up studies to further automate the creation of faceted classification structure, while our concept search application demonstrated the utility and potential of integrating classification-based approach with retrieval-based approach. Integration of text- and classification-based methods as outlined in this paper combines the strengths of two vastly different approaches to information discovery by constructing and utilizing a flexible information organization scheme from an existing classification structure.

• Journal of Korea Multimedia Society
• /
• v.21 no.10
• /
• pp.1150-1161
• /
• 2018

Classification is widely used in medical images to categorize patients and non-patients. However, conventional classification requires a complex procedure, including some rigid steps such as pre-processing, segmentation, feature extraction, detection, and classification. In this paper, we propose a novel convolutional neural network (CNN), called LeukemiaNet, to specifically classify two different types of leukemia, including acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), and non-cancerous patients. To extend the limited dataset, a PCA color augmentation process is utilized before images are input into the LeukemiaNet. This augmentation method enhances the accuracy of our proposed CNN architecture from 96.9% to 97.2% for distinguishing ALL, AML, and normal cell images.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.11B
• /
• pp.1234-1244
• /
• 2009

Nowadays, the traffic type and behavior are extremely diverse due to the appearance of various services and applications on Internet, which makes the need of application-level traffic classification important for the efficient management and control of network resources. Although lots of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in terms of accuracy and completeness. In this paper we propose an application traffic classification method using statistic signatures, defined as a directional sequence of packet size in a flow, which is unique for each application. The statistic signatures of each application are collected by our automatic grouping and extracting mechanism which is mainly described in this paper. By matching to the statistic signatures we can easily and quickly identify the application name of traffic flows with high accuracy, which is also shown by comprehensive excrement with our campus traffic data.