• 한국산업정보학회논문지
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• 제20권5호
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• pp.37-44
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• 2015

An antivirus is a widely used solution for detecting malicious softwares in client devices. The performance of antivirus solutions in the mobile client environment is critical due to its resource constrains. Many solutions light-weighting client's overhead in the mobile client environment have been developed. However, most solutions require platform modifications or software installations and it decreases their realizations in practice. In this paper, we propose a solution detecting malwares on networks using the Software Defined Network (SDN). Our main goal is designing a solution detecting malwares of mobile client without involving the client into the work. We contribute to provide a solution that does not require client-side installations or modifications and so is easily applicable in practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권2호
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• pp.846-864
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• 2017

Software Defined Network (SDN) realizes management and control over the underlying forwarding device, along with acquisition and analysis of network topology and flow characters through south bridge protocol. Data path Identification (DPID) is the unique identity for managing the underlying device, so forged DPID can be used to attack the link of underlying forwarding devices, as well as carry out DoS over the upper-level controller. This paper proposes a dynamic defense method based on Client-Puzzle model, in which the controller achieves dynamic management over requests from forwarding devices through generating questions with multi-level difficulty. This method can rapidly reduce network load, and at the same time separate attack flow from legal flow, enabling the controller to provide continuous service for legal visit. We conduct experiments on open-source SDN controllers like Fluid and Ryu, the result of which verifies feasibility of this defense method. The experimental result also shows that when cost of controller and forwarding device increases by about 2%-5%, the cost of attacker's CPU increases by near 90%, which greatly raises the attack difficulty for attackers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.874-890
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• 2021

With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

• 한국산학기술학회논문지
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• 제18권9호
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• pp.34-41
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• 2017

무선 매시 네트워크는 무선 노드 간에는 다중 홉 라우팅을 통해 통신을 하며 인터넷과 연결된 게이트웨이를 통해 인터넷과 연결되는 네트워크이다. 이러한 네트워크는 부분적으로 기존 무선 접근 네트워크의 유선 백본 역할을 수행할 수 있어서, 다양한 응용이 가능한 확장 가능한 네트워크이다. 본 논문에서는 무선 매시 네트워크 환경에서 소프트웨어 정의 네트워킹 기술을 이용하여 QoS를 지원하는 기법을 설계한다. 제안 기법에서는 무선 매시 라우터의 자원 제약적인 상황을 고려하여 비용 효율적이고 상황 적응적인 QoS 지원 기법을 설계한다. 제안 기법은 QoS 지원 기법을 차별 서비스와 통합 서비스로 구분하여 설계하고, 소프트웨어 정의 네트워킹 기술인 오픈플로우 프로토콜을 이용하여 MPLS 기법과 RSVP를 통해 각각의 상황에 적합한 모델을 제시한다. 제안 기법의 타당성 검증을 위해 다양한 QoS 메트릭들에 대한 성능 평가 모델을 제시하였으며 제안 기법이 제시하는 QoS 지원 기법이 비용 효율적으로 동작하는 지를 제시한다.

• 정보보호학회논문지
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• 제29권2호
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• pp.393-399
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• 2019

조직으로부터 인가받지 않고 내부로 반입한 비인가SW가 조직의 네트워크 보안에서 위협으로 대두되고 있는 상황에서 SDN(Software-Defined Network) 기반의 네트워크 환경이 구축된 조직에서는 별도의 보안장비를 설치하지 않고도 조직의 특성을 고려한 보안 어플리케이션 개발을 통해 네트워크보안을 강화할 수 있다. 기존 SDN 환경의 보안기술은 방화벽, 침입탐지시스템 등 외부 네트워크로부터 내부 네트워크를 보호하는 연구가 이루어져 왔으나 내부자 위협에 대해서는 부족하였다. 따라서 이러한 SDN 환경에서 조직 내부 위협 중 하나인 비인가SW로 부터 내부 네트워크를 보호할 수 있는 시스템을 제안한다.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.511-524
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• 2016

The Virtual Local Area Network (VLAN) has been used for a long time in campus and enterprise networks as the most popular network virtualization solution. Due to the benefits and advantages achieved by using VLAN, network operators and administrators have been using it for constructing their networks up until now and have even extended it to manage the networking in a cloud computing system. However, their configuration is a complex, tedious, time-consuming, and error-prone process. Since Software Defined Networking (SDN) features the centralized network management and network programmability, it is a promising solution for handling the aforementioned challenges in VLAN management. In this paper, we first introduce a new architecture for campus and enterprise networks by leveraging SDN and OpenFlow. Next, we have designed and implemented an application for easily managing and flexibly troubleshooting the VLANs in this architecture. This application supports both static VLAN and dynamic VLAN configurations. In addition, we discuss the hybrid-mode operation where the packet processing is involved by both the OpenFlow control plane and the traditional control plane. By deploying a real test-bed prototype, we illustrate how our system works and then evaluate the network latency in dynamic VLAN operation.

• 정보처리학회논문지C
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• 제18C권6호
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• pp.413-422
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• 2011

오버레이 네트워크는 인터넷 연결성을 손상시키지 않고 새로운 네트워킹 기능을 제공할 수 있는 현실적인 방안이다. 본 논문은 서비스 오버레이의 용이한 구성을 지원하는 사용자 정의 네트워크 서비스를 소개하고 구성된 오버레이 네트워크 상에서 고속 데이터 평면 처리를 수행하는 서비스 게이트웨이의 하드웨어 및 소프트웨어 구조를 살펴본다. 또한, 멀티캐스트 응용 지원을 위한 서비스 오버레이 네트워크의 생성 과정을 예시한다. 국가과학기술연구망에 구축된 실험환경에서 서비스 게이트웨이의 성능 평가를 수행하고 수백 Mbps급 멀티미디어 서비스의 적용가능성을 확인한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.181-184
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• 2018

최근 주목 받고 있는 소프트웨어 정의 네트워크(SDN: Software-Defined Networks)는 기존 네트워크 운용의 비효율성과 복잡성을 근본적으로 해결하기 위해 등장한 개방형 네트워크 인프라이다. SDN 시스템이 점차 상용화, 개방화 되는 시점에서, 내재되어있는 보안적 위협을 줄이기 위하여 효율적이고 자동화된 취약점 탐지의 필요성이 대두되고 있다. 본 논문에서는 자동화된 소프트웨어 테스트 기법 중 하나인 퍼즈테스팅이 SDN에 적용되어야 할 이유를 살펴보고자 한다. 또한, 기존에 관련된 연구의 분석을 통해 현재 학계의 연구동향을 파악하고 앞으로의 연구 방향성을 제시한다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.374-386
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• 2022

Nowadays, research in deep learning leveraged automated computing and networking paradigm evidenced rapid contributions in terms of Software Defined Networking (SDN) and its diverse security applications while handling cybercrimes. SDN plays a vital role in sniffing information related to network usage in large-scale data centers that simultaneously support an improved algorithm design for automated detection of network intrusions. Despite its security protocols, SDN is considered contradictory towards DDoS attacks (Distributed Denial of Service). Several research studies developed machine learning-based network intrusion detection systems addressing detection and mitigation of DDoS attacks in SDN-based networks due to dynamic changes in various features and behavioral patterns. Addressing this problem, this research study focuses on effectively designing a multistage hybrid and intelligent deep learning classifier based on modified deep forest classification to detect DDoS attacks in SDN networks. Experimental results depict that the performance accuracy of the proposed classifier is improved when evaluated with standard parameters.