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신승원 교수

Seungwon Shin

KAIST 김재철AI대학원 · 컴퓨터과학

연구실 소개

신승원 교수의 연구실은 소프트웨어정의네트워킹(SDN)과 클라우드 환경에서의 네트워크 보안을 핵심으로 삼고 있습니다. 특히 SDN 아키텍처의 제어층에 대한 취약성 분석과 자원 고갈 공격, 네트워크 포지셔닝 공격 등 새로운 형태의 사이버 위협을 탐지하고 대응하는 기반 기술을 연구하고 있습니다. 또한 대규모 동적 환경인 클라우드 네트워크에서의 실시간 모니터링 및 위협 탐지 프레임워크를 개발하여, 보안과 가용성의 균형을 추구하고 있습니다. 연구는 실질적 보안 위협에 대응하기 위한 기술적 솔루션과 체계적 분석을 기반으로 진행됩니다.

SDN 보안네트워크 공격 탐지클라우드 네트워크 모니터링제어층 취약성자원 고갈 공격

연구 현황

논문 수
140
총 인용 수
4,164
최근 5년 논문
52
주요 분야
컴퓨터과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
52총합
2022
2023
2024
2025
2026
5개년 연도별 피인용 수
302총합
20222023202420252026

주요 논문

15
1
논문|인용수 555·2013
AVANT-GUARD
Seungwon Shin, Vinod Yegneswaran, Phillip Porras, Guofei Gu

Among the leading reference implementations of the Software Defined Networking (SDN) paradigm is the OpenFlow framework, which decouples the control plane into a centralized application. In this paper, we consider two aspects of OpenFlow that pose security challenges, and we propose two solutions that could address these concerns. The first challenge is the inherent communication bottleneck that arises between the data plane and the control plane, which an adversary could exploit by mounting a "

Computer Networks and CommunicationsComputer Science
2
논문|인용수 315·2013
Attacking software-defined networks
Seungwon Shin, Guofei Gu

In this paper, for the first time we show a new attack to fin- gerprint SDN networks and further launch efficient resource consumption attacks. This attack demonstrates that SDN brings new security issues that may not be ignored. We provide the first feasibility study of such attack and hope to stimulate further studies in SDN security research.

Computer Networks and CommunicationsComputer Science
3
논문|인용수 193·2014
Rosemary
Seungwon Shin, Yongjoo Song, Taekyung Lee, Sang-Ho Lee, Jaewoong Chung, Phillip Porras, Vinod Yegneswaran, Jiseong Noh, Brent Byunghoon Kang

Within the hierarchy of the Software Defined Network (SDN) network stack, the control layer operates as the critical middleware facilitator of interactions between the data plane and the network applications, which govern flow routing decisions. In the OpenFlow implementation of the SDN model, the control layer, commonly referred to as a network operating system (NOS), has been realized by a range of competing implementations that offer various performance and functionality advantages: Floodligh

Computer Networks and CommunicationsComputer Science
4
논문|인용수 185·2012
CloudWatcher: Network security monitoring using OpenFlow in dynamic cloud networks (or: How to provide security monitoring as a service in clouds?)
Seungwon Shin, Guofei Gu

Cloud computing is becoming a popular paradigm. Many recent new services are based on cloud environments, and a lot of people are using cloud networks. Since many diverse hosts and network configurations coexist in a cloud network, it is essential to protect each of them in the cloud network from threats. To do this, basically, we can employ existing network security devices, but applying them to a cloud network requires more considerations for its complexity, dynamism, and diversity. In this pa

Computer Networks and CommunicationsComputer Science
5
논문|인용수 125·2016
Enhancing Network Security through Software Defined Networking (SDN)
Seungwon Shin, Lei Xu, Sungmin Hong, Guofei Gu

Software Defined Networking (SDN) is an emerging technology that attracts significant attention from both industry and academia recently. By decoupling the control logic from the closed and proprietary implementations of traditional network devices, it enables researchers and practitioners to design new innovative network functions/protocols in a much more flexible, powerful, and easier way. We believe SDN provides new research opportunities to security, and it can greatly impact network securit

Computer Networks and CommunicationsComputer Science
6
논문|인용수 83·2010
Conficker and beyond
Seungwon Shin, Guofei Gu

Conficker [26] is the most recent widespread, well-known worm/bot. According to several reports [16, 28], it has infected about 7 million to 15 million hosts and the victims are still increasing even now. In this paper, we analyze Conficker infections at a large scale, including about 25 millions victims, and study various interesting aspects about this state-of-the-art malware. By analyzing Conficker, we intend to understand current and new trends in malware propagation, which could be very hel

Computer Networks and CommunicationsComputer Science
7
논문|인용수 75·2022
Vulcan: Automatic extraction and analysis of cyber threat intelligence from unstructured text
Hyeonseong Jo, Yongjae Lee, Seungwon Shin
SJR Q1Computers & Security
Information SystemsComputer Science
8
논문|인용수 67·2015
A First Step Toward Network Security Virtualization: From Concept To Prototype
Seungwon Shin, Haopei Wang, Guofei Gu
SJR Q1IEEE Transactions on Information Forensics and Security

Network security management is becoming more and more complicated in recent years, considering the need of deploying more and more network security devices/middle-boxes at various locations inside the already complicated networks. A grand challenge in this situation is that current management is inflexible and the security resource utilization is not efficient. The flexible deployment and utilization of proper security devices at reasonable places at needed time with low management cost is extre

Computer Networks and CommunicationsComputer Science
9
논문|인용수 65·2011
A Large-Scale Empirical Study of Conficker
Seungwon Shin, Guofei Gu, Narasimha Reddy, Christopher P. Lee
SJR Q1IEEE Transactions on Information Forensics and Security

Conficker is the most recent widespread, well-known worm/bot. According to several reports, it has infected about 7 million to 15 million hosts and the victims are still increasing even now. In this paper, we analyze Conficker infections at a large scale, about 25 million victims, and study various interesting aspects about this state-of-the-art malware. By analyzing Conficker, we intend to understand current and new trends in malware propagation, which could be very helpful in predicting future

Computer Networks and CommunicationsComputer Science
10
논문|인용수 50·2006
Malware prevalence in the KaZaA file-sharing network
Seungwon Shin, Jaeyeon Jung, Hari Balakrishnan

In recent years, more than 200 viruses have been reported to use a peer-to-peer (P2P) file-sharing network as a propagation vector. Disguised as files that are frequently exchanged over P2P networks, these malicious programs infect the user's host if downloaded and opened, leaving their copies in the user's sharing folder for further propagation. Using a light-weight crawler built for the KaZaA file-sharing network, we study the prevalence of malware in this popular P2P network, the malware's pr

Computer Networks and CommunicationsComputer Science
11
논문|인용수 40·2019
SODA: A software-defined security framework for IoT environments
Yeonkeun Kim, Jaehyun Nam, Taejune Park, Sandra Scott-Hayward, Seungwon Shin
SJR Q1Computer NetworksOA
Computer Networks and CommunicationsComputer Science
12
논문|인용수 37·2020
A comprehensive security assessment framework for software-defined networks
Seungsoo Lee, Jinwoo Kim, Seungwon Woo, Changhoon Yoon, Sandra Scott-Hayward, Vinod Yegneswaran, Phillip Porras, Seungwon Shin
SJR Q1Computers & Security
Computer Networks and CommunicationsComputer Science
13
논문|인용수 20·2005
D-SAT: Detecting SYN Flooding Attack by Two-Stage Statistical Approach
Seungwon Shin, Kiyoung Kim, Jongsoo Jang

We propose D-SAT (detecting SYN flooding attack by two-stage statistical approach) system that is simple and robust approach to detect SYN flooding attacks by observing network traffic. Instead of managing all ongoing traffic on the network, D-SAT only monitors SYN count and ratio between SYN and other TCP packets at first time. And it detects SYN flooding and finds victims more accurately in its second stage. To make the detection mechanism robustly and easily, D-SAT uses CUSUM (cumulative sum)

Computer Networks and CommunicationsComputer Science
14
book chapter|인용수 18·2011
Cross-Analysis of Botnet Victims: New Insights and Implications
Seungwon Shin, Raymond Tzer Pin Lin, Guofei Gu
SJR Q2Lecture notes in computer science
Computer Networks and CommunicationsComputer Science
15
논문|인용수 16·2013
EFFORT: A new host–network cooperated framework for efficient and effective bot malware detection
Seungwon Shin, Zhaoyan Xu, Guofei Gu
SJR Q1Computer Networks
Computer Networks and CommunicationsComputer Science

대표 연구 분야

Computer Networks and CommunicationsArtificial IntelligenceInformation SystemsSignal ProcessingHardware and ArchitectureSociology and Political Science

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