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논문 기본 정보

자료유형
학위논문
저자정보

강효성 (경희대학교, 경희대학교 대학원)

지도교수
홍충선
발행연도
2016
저작권
경희대학교 논문은 저작권에 의해 보호받습니다.

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Recently many firms around the world reduce costs and innovate business processes by adopting cloud services, whose performance however is compromised by external spoofing or poisoning attacks against the intra-cloud Virtual Machine(VM), which hinders companies from expanding their cloud computing systems. Lots of studies have investigated the methods of preventing or responding to security incidents but proposed less viable protocols and passive attack detection techniques with limited scalability to large networks. Thus, the present paper proposes two defense techniques drawing on a reliable certification table and an intra-cloud VM-based automated ARP table management framework against network attacks called spoofing or poisoning on an open source cloud platform OpenStack used by many cloud service developers, and suggests the countermeasures for the loss of resources and decrease in performance of intra-cloud VM.

목차

Abstract iii
1. Introduction 1
2. ARP and ARP Spoofing in Cloud Environment 3
2.1 Address Resolution Protocol 3
2.2 ARP Spoofing Attack 5
3. Related Work 7
3.1 Secure Address Resolution Protocol 7
3.2 Dynamic Host Configuration Protocol Encryption 8
3.3 OpenFlow-based Anti-Spoofing Mechanism 9
3.4 ARP Attack Detection Via Server Manager 9
3.5 Preventing Attacks with VLAN-based Network Multi-Tenancy 10
4. Proposal 11
4.1 Defense Technique using Reliaㅋble Authentication Table 11
4.1.1 Installing an OpenStack Cloud Environment 12
4.1.2 Collecting IP and MAC Address Information of an Instance 13
4.1.3 Reliable Authentication Table 14
4.1.4 Comparison Handler 15
4.2 Defense Technique using VM-based Automated ARP Table Management 16
4.2.1 Controller-Agent and VM-Agent 16
4.2.2 Automated ARP Table Management Scenario 17
5. Evaluation 19
5.1 ARP Spoofing Attack Scenario 19
5.2 A Defense Scenario against ARP Spoofing 21
5.3 Defense Result 23
5.4 Performance Analysis 25
5.4.1 Data Collecting using Ceilometer 25
5.4.2 CPU Utilization Compared 27
6. Conclusion and Future Work 29
References 30

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