Virtual Firewalling For Migrating Virtual Machines In Cloud Computing

被引:0
|
作者
Anwar, Mahwish [1 ]
机构
[1] HiQ Karlskrona AB, Sch Comp, Blekinge Tekn Hogskola, Karlskrona, Sweden
关键词
firewalling; virtual machine; migration;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cloud Computing (CC) uses virtualization to provide computing resources on demand via Internet. Small and large organizations benefit from CC because of reduced operating costs and increase in business agility. The migrating Virtual Machine (VM) is vulnerable from attacks such as fake migration initiations, service interruptions, manipulation of data or other network attacks. Hence, during live migration any security lax in VM firewall policy can put the VM at risk. A malicious VM can further pose threat to other VMs in its host and consequently for VMs in LAN. Hardware firewalls only protect VM before and after migration. Plus, they are blind to virtual traffic. Hence, virtual firewalls (VFs) are used to secure VMs. Mostly; they are deployed at Virtual Machine Monitor-level (VMM) under Cloud provider's control. Source VMM-level VF provides security to VM before the migration incurs and the destination VMM-level VF starts securing VM after migration is completed. It thus, becomes possible for attacker to use the intermediate migrating window to launch attacks on VM. This research contributes towards providing understanding of having open source virtual firewall at VM-level for migrating VMs to reduce attack window of VM during the migration. The final contribution is the validation and uptime evaluation of the implemented Packet Filter firewall for VM at VM-level during migration in City Network data center. Such an approach would enable hardened security for overall VM migration.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Vulnerability Assessment for Virtual Machines in Virtual Environment of Cloud Computing
    Patil, Rajendra
    Modi, Chirag
    [J]. RECENT FINDINGS IN INTELLIGENT COMPUTING TECHNIQUES, VOL 1, 2019, 707 : 569 - 576
  • [2] Efficient Distribution of Virtual Machines for Cloud Computing
    Schmidt, Matthias
    Fallenbeck, Niels
    Smith, Matthew
    Freisleben, Bernd
    [J]. PROCEEDINGS OF THE 18TH EUROMICRO CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING, 2010, : 567 - 574
  • [3] Optimal Allocation of Virtual Machines in Cloud Computing
    Lin, Ming-Hua
    Tsai, Jung-Fa
    Hu, Yi-Chung
    Su, Tzu-Hsuan
    [J]. SYMMETRY-BASEL, 2018, 10 (12):
  • [4] Improving cloud computing virtual machines balancing through hosts and virtual machines similarities
    Brascher, Gabriel Beims
    Weingartner, Rafael
    Westphall, Carlos Becker
    [J]. 2017 13TH IEEE WORLD CONGRESS ON SERVICES (SERVICES), 2017, : 76 - 85
  • [5] Dynamic Creation of Virtual Machines in Cloud Computing Systems
    Luo, Fei
    Scherson, Isaac D.
    Fuentes, Joel
    [J]. 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), 2017, : 316 - 323
  • [6] Multiple Virtual Machines Resource Scheduling for Cloud Computing
    Zhang, Weizhe
    He, Hui
    Chen, Gui
    Sun, Jilong
    [J]. APPLIED MATHEMATICS & INFORMATION SCIENCES, 2013, 7 (05): : 2089 - 2096
  • [7] Performance Analysis of Virtual Machines and Containers in Cloud Computing
    Barik, Rabindra K.
    Lenka, Rakesh K.
    Rao, K. Rahul
    Ghose, Devam
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA), 2016, : 1204 - 1210
  • [8] Improving Virtual Machines Networking Performance for Cloud Computing
    Bourguiba, Manel
    El Korbi, Ines
    Haddadou, Kamel
    Pujolle, Guy
    [J]. 2013 IFIP/IEEE INTERNATIONAL SYMPOSIUM ON INTEGRATED NETWORK MANAGEMENT (IM 2013), 2013, : 513 - 519
  • [9] Survey on covert channels in virtual machines and cloud computing
    Betz, Johann
    Westhoff, Dirk
    Mueller, Guenter
    [J]. TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2017, 28 (06):
  • [10] Mapping Virtual Machines onto Physical Machines in Cloud Computing: A Survey
    Pietri, Ilia
    Sakellariou, Rizos
    [J]. ACM COMPUTING SURVEYS, 2016, 49 (03)