• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.11b
• /
• pp.1053-1056
• /
• 2003

라우터에서 패킷을 특정 "플로우"로 분류하는 과정을 패킷 분류라고 한다. 어떤 플로우에 소한 모든 패킷들은 미리 정의된 규칙을 따르며. 라우터는 비슷한 처리과정을 제공한다. 예를 들면, 같은 줄발지 IP주소와 도착지 IP주소를 가진 패킷들은 하나의 플로우로 분류된다. 이러한 패킷 분류는 최선형(best-effort) 서비스가 아닌 품질보장(QoS), VPN, 방화벽 서비스 등과 같이 플로우와 플로우를 구별하여야하는 서비스 제공에 필요하다. 일반적으로 다수의 필터에 대한 패킷 분류는 매우 어려운 문제로 하드웨어 및 소프트웨어 기반의 다양한 알고리즘들이 제시되었다. 본 논문은 트라이를 기반으로 작은 메모리 공간을 사용하면서 빠른 패킷 분류를 탄 수 있는 기법을 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.3B
• /
• pp.143-152
• /
• 2007

In order to provide new value-added services such as a policy-based routing and the quality of services in next generation network, the Internet routers need to classify packets into flows for different treatments, and it is called a packet classification. Since the packet classification should be performed in wire-speed for every packet incoming in several hundred giga-bits per second, the packet classification becomes a bottleneck in the Internet routers. Therefore, high speed packet classification algorithms are required. In this paper, we propose an efficient packet classification architecture based on a hierarchical binary search fee. The proposed architecture hierarchically connects the binary search tree which does not have empty nodes, and hence the proposed architecture reduces the memory requirement and improves the search performance.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.1
• /
• pp.75-80
• /
• 2014

The quality of real-time Voice over Internet Protocol (VoIP) network is affected by network impariments such as delays, jitters, and packet loss. This paper proposes a packet loss concealment algorithm based on voice classification for enhancing VoIP speech quality. In the proposed method, arriving packets are classified by an adaptive thresholding approach based on the analysis of multiple features of short signal segments. The excellent classification results are used in the packet loss concealment. Additionally, linear prediction-based packet loss concealment delivers high voice quality by alleviating the metallic artifacts due to concealing consecutive packet loss or recovering lost packet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.1
• /
• pp.646-650
• /
• 2005

요즘 아날로그 방송에서 디지털 방송시대로 변화함에 따라 디지털 방송기술이 많이 발전되었다. 디지털 방송은 방송국으로부터 만들어지는 영상, 음성, 데이터 스트림들이 MPEG을 통해 효율적으로 압축하고 동기식으로 패킷화되어서 MPEG TS 패킷형식으로 서비스 이용자에게 위성 또는 지상파를 통해 전송되어진다. 방송되어지는 데이터 정보는 물론 그 외의 비관련 데이터도 제공되어짐으로써 서비스 이용범위도 많이 늘어나고 특히 기존의 영상과 음성위주의 방송과는 달리 사업자와 이용자간의 쌍방향으로 데이터를 송수신할 수 있는 기술이 고부가가치 사업으로 대두되고 있다. 디지털 방송을 수신해서 보기 위해서는 튜너로부터 수신되어 디지털화된 MPEG TS 패킷들을 분류해주는 과정이 필요하다. 본 연구에서는 실제 디지털 방송되었던 패킷 파일을 가지고 분류하였다. 영상 스트림과 음성 스트림을 분류하고 데이터 스트림을 분리하였다. 그리고 데이터 방송 규격의 데이터 스트림 파일을 별도로 입력하여 데이터를 분류하였다. 프로그램은 Microsoft visual c++6.0을 사용하여 구현하였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.04d
• /
• pp.593-595
• /
• 2003

패킷 분류는 품질보장(QoS), VPN(Virtual Private Network), 고성능 방화벽(high speed firewall). 인터넷 사용료 부과(pricing)를 제공하는 차세대 라우터에 반드시 필요한 기능이다. 라우터는 송신 주소, 수신 주소. 프로토콜 타입. 흑은 포트 번호와 같은 패킷 헤더의 설러 필드를 주어진 필터 리스트와 비교하여 패킷을 분류한다. 기존에 제시된 하드웨어 기반의 패킷 분류 기법은 빠른 검색 시간을 제공하지만 확장성과 테이블 갱신 면에서 문제점이 있다. 본 논문에서는 하드웨어 기반의 빠르고 확장성있고 갱신이 가능한 2차원 필드 검색 기법을 제시한다. 차후 연구에서는 본 기법을 보다 면밀히 분석하고 다차원 필터 검색이 가능하도록 확장한 기법을 제시하겠다.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.9
• /
• pp.38-45
• /
• 2007

With the emergence of new applications, packet classification is essential for supporting advanced internet applications, such as network security and QoS provisioning. As the packet classification on multiple-fields is a difficult and time consuming problem, internet routers need to classify incoming packet quickly into flows. In this paper, we present multi-phase packet classification architecture using an internal buffer for fast packet processing. Using internal buffer between address pair searching phase and remained fields searching phases, we can hide latency from the characteristic that search times of source and destination header fields are different. Moreover we guarantee the improvement by using single entry caching. The proposed architecture is easy to apply to different needs owing to its simplicity and generality.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2018.05a
• /
• pp.16-18
• /
• 2018

최근 네트워크 상에 새롭고 다양한 어플리케이션들이 생겨나면서 이에 따른 적절한 어플리케이션별 서비스 제공을 위한 패킷 분류 방법이 요구되고 있다. 이로 인하여 딥 러닝 기술이 발전 하면서 이를 이용한 네트워크 트래픽 분류 방법들이 제안되고 있다. 따라서, 본 논문에서는 딥 러닝 기술 중 Convolution Neural Network 와 Recurrent Neural Network 를 동시에 활용한 네트워크 패킷 분류 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.331-337
• /
• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• Journal of KIISE:Information Networking
• /
• v.32 no.4
• /
• pp.543-550
• /
• 2005

Demand for better services in the Internet has been increasing due to the rapid growth of the Internet, and hence next generation routers are required to perform intelligent packet classification. For a given classifier defining packet attributes or contents, packet classification is the process of identifying the highest priority rule to which a packet conforms. A notable characteristic of real classifiers is that a packet matches only a small number of distinct source-destination prefix pairs. Therefore, a lot of schemes have been proposed to filter rules based on source and destination prefix pairs. However, most of the schemes are based on sequential one-dimensional searches using trio which requires huge memory. In this paper, we proposea memory-efficient two-dimensional search scheme using source and destination prefix pairs. By constructing binary prefix tree, source prefix search and destination prefix search are simultaneously performed in a binary tree. Moreover, the proposed two-dimensional binary prefix tree does not include any empty internal nodes, and hence memory waste of previous trio-based structures is completely eliminated.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.6
• /
• pp.21-31
• /
• 2015

The Internet users want to get real-time services for various multi-media applications. Network traffic rate has been rapidly increased, and data amounts that the Internet has to carry have been exponentially increased. A packet is the basic unit in transferring data at the Internet, and packet classification is one of the most challenging functionalities that routers should perform at wire-speed. Among various known packet classification algorithms, area-based quad-trie (AQT) algorithm is one of the efficient algorithms which can lookup five header fields simultaneously. As a representative space decomposition algorithm, the AQT requires a small amount of memory in storing classification rules, but it does not provide high-speed classification performance. In this paper, we propose a new packet classification algorithm by applying a binary search for the codewords of the AQT to overcome the issue of the AQT. Throughout simulation, it is shown that the proposed algorithm provides a better performance than the AQT in the number of rule comparisons with each input packet.