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DoS Attacks on Your Memory in Cloud

Published:02 April 2017Publication History

ABSTRACT

In cloud computing, network Denial of Service (DoS) attacks are well studied and defenses have been implemented, but severe DoS attacks on a victim's working memory by a single hostile VM are not well understood. Memory DoS attacks are Denial of Service (or Degradation of Service) attacks caused by contention for hardware memory resources on a cloud server. Despite the strong memory isolation techniques for virtual machines (VMs) enforced by the software virtualization layer in cloud servers, the underlying hardware memory layers are still shared by the VMs and can be exploited by a clever attacker in a hostile VM co-located on the same server as the victim VM, denying the victim the working memory he needs. We first show quantitatively the severity of contention on different memory resources. We then show that a malicious cloud customer can mount low-cost attacks to cause severe performance degradation for a Hadoop distributed application, and 38X delay in response time for an E-commerce website in the Amazon EC2 cloud. Then, we design an effective, new defense against these memory DoS attacks, using a statistical metric to detect their existence and execution throttling to mitigate the attack damage. We achieve this by a novel re-purposing of existing hardware performance counters and duty cycle modulation for security, rather than for improving performance or power consumption. We implement a full prototype on the OpenStack cloud system. Our evaluations show that this defense system can effectively defeat memory DoS attacks with negligible performance overhead.

References

  1. Ab - the apache software foundation. http://httpd.apache.org/docs/2.2/programs/ab.html.Google ScholarGoogle Scholar
  2. Amazon CloudWatch. https://aws.amazon.com/cloudwatch/.Google ScholarGoogle Scholar
  3. Amazon virtual private cloud. https://aws.amazon.com/vpc/.Google ScholarGoogle Scholar
  4. AMD architecture programmer's manual, volume 1: Application programming. http://support.amd.com/TechDocs/24592.pdf.Google ScholarGoogle Scholar
  5. Google Stackdriver. https://cloud.google.com/stackdriver/.Google ScholarGoogle Scholar
  6. Improving real-time performance by utilizing cache allocation technology. http://www.intel.com/content/www/us/en/communications/cache-allocation-technology-white-paper.html.Google ScholarGoogle Scholar
  7. Intel 64 and IA-32 architectures software developer's manual, volume 3: System programming guide. http://www.intel.com/content/www/us/en/processors/architectures-software-developer-manuals.html.Google ScholarGoogle Scholar
  8. Magento: ecommerce software and ecommerce platform. http://www.magento.com/.Google ScholarGoogle Scholar
  9. memtier benchmark. https://github.com/RedisLabs/memtier_benchmark.Google ScholarGoogle Scholar
  10. Microsoft Azure Application Insights. https://azure.microsoft.com/en-us/services/application-insights/.Google ScholarGoogle Scholar
  11. Sysbench: a system performance benchmark. https://launchpad.net/sysbench/.Google ScholarGoogle Scholar
  12. Welcome to the httperf homepage. http://www.hpl.hp.com/research/linux/httperf/.Google ScholarGoogle Scholar
  13. J. Ahn, C. Kim, J. Han, Y.-R. Choi, and J. Huh. Dynamic virtual machine scheduling in clouds for architectural shared resources. In USENIX Conference on Hot Topics in Cloud Computing, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Alarifi and S. D. Wolthusen. Robust coordination of cloud-internal denial of service attacks. In Intl. Conf. on Cloud and Green Computing, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. H. S. Bedi and S. Shiva. Securing cloud infrastructure against co-resident DoS attacks using game theoretic defense mechanisms. In Intl. Conf. on Advances in Computing, Communications and Informatics, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. H. Cook, M. Moreto, S. Bird, K. Dao, D. A. Patterson, and K. Asanovic. A hardware evaluation of cache partitioning to improve utilization and energy-efficiency while preserving responsiveness. In Intl. Symp. on Computer Architecture, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. C. Delimitrou and C. Kozyrakis. Paragon: QoS-aware scheduling for heterogeneous datacenters. In Intl. Conf. on Architectural Support for Programming Languages and Operating Systems, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. E. Ebrahimi, C. J. Lee, O. Mutlu, and Y. N. Patt. Fairness via source throttling: A configurable and high-performance fairness substrate for multi-core memory systems. In Architectural Support for Programming Languages and Operating Systems, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. D. Grunwald and S. Ghiasi. Microarchitectural denial of service: Insuring microarchitectural fairness. In ACM/IEEE Intl. Symp. on Microarchitecture, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Gupta, J. Sampson, and M. B. Taylor. Quality time: A simple online technique for quantifying multicore execution efficiency. In IEEE Intl. Symp. on Performance Analysis of Systems and Software, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  21. Q. Huang and P. P. Lee. An experimental study of cascading performance interference in a virtualized environment. SIGMETRICS Perf. Eval. Rev., 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. P. Jamkhedkar, J. Szefer, D. Perez-Botero, T. Zhang, G. Triolo, and R. B. Lee. A framework for realizing security on demand in cloud computing. In Conf. on Cloud Computing Technology and Science, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. T. Kim, M. Peinado, and G. Mainar-Ruiz. Stealthmem: System-level protection against cache-based side channel attacks in the cloud. In USENIX Security Symp., 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. F. Liu, Y. Yarom, Q. Ge, G. Heiser, and R. B. Lee. Last-level cache side-channel attacks are practical. In IEEE Symp. on Security and Privacy, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. H. Liu. A new form of DoS attack in a cloud and its avoidance mechanism. In ACM Workshop on Cloud Computing Security, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. F. J. Massey Jr. The Kolmogorov-Smirnov test for goodness of fit. Journal of the American statistical Association, 1951.Google ScholarGoogle Scholar
  27. T. Moscibroda and O. Mutlu. Memory performance attacks: Denial of memory service in multi-core systems. In USENIX Security Symp., 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. S. P. Muralidhara, L. Subramanian, O. Mutlu, M. Kandemir, and T. Moscibroda. Reducing memory interference in multicore systems via application-aware memory channel partitioning. In ACM/IEEE Intl. Symp. on Microarchitecture, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. D. Novaković, N. Vasić, S. Novaković, D. Kostić, and R. Bianchini. Deepdive: Transparently identifying and managing performance interference in virtualized environments. In USENIX Conf. on Annual Technical Conference, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. N. Poggi, D. Carrera, R. Gavalda, and E. Ayguade. Non-intrusive estimation of QoS degradation impact on e-commerce user satisfaction. In IEEE Intl. Symp. on Network Computing and Applications, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. T. Ristenpart, E. Tromer, H. Shacham, and S. Savage. Hey, you, get off of my cloud: Exploring information leakage in third-party compute clouds. In ACM Conf. on Computer and Communications Security, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. V. Varadarajan, T. Kooburat, B. Farley, T. Ristenpart, and M. M. Swift. Resource-freeing attacks: Improve your cloud performance (at your neighbor's expense). In ACM Conf. on Computer and Communications Security, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. V. Varadarajan, Y. Zhang, T. Ristenpart, and M. Swift. A placement vulnerability study in multi-tenant public clouds. In USENIX Security Symp., 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. D. H. Woo and H.-H. S. Lee. Analyzing performance vulnerability due to resource denial-of-service attack on chip multiprocessors. In Workshop on Chip Multiprocessor Memory Systems and Interconnects, 2007.Google ScholarGoogle Scholar
  35. Z. Wu, Z. Xu, and H. Wang. Whispers in the hyper-space: High-speed covert channel attacks in the cloud. In USENIX Security Symp., 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Y. Xu, M. Bailey, F. Jahanian, K. Joshi, M. Hiltunen, and R. Schlichting. An exploration of L2 cache covert channels in virtualized environments. In ACM Workshop on Cloud computing security, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Z. Xu, H. Wang, and Z. Wu. A measurement study on co-residence threat inside the cloud. In USENIX Security Symp., 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. H. Yang, A. Breslow, J. Mars, and L. Tang. Bubble-flux: Precise online QoS management for increased utilization in warehouse scale computers. In ACM Intl. Symp. on Computer Architecture, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. T. Zhang and R. B. Lee. CloudMonatt: An architecture for security health monitoring and attestation of virtual machines in cloud computing. In ACM Intl. Symp. on Computer Architecture, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. X. Zhang, S. Dwarkadas, and K. Shen. Hardware execution throttling for multi-core resource management. In USENIX Annual Technical Conference, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. X. Zhang, E. Tune, R. Hagmann, R. Jnagal, V. Gokhale, and J. Wilkes. CPI2: Cpu performance isolation for shared compute clusters. In ACM European Conf. on Computer Systems, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Y. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart. Cross-VM side channels and their use to extract private keys. In ACM Conf. on Computer and Communications Security, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Y. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart. Cross-tenant side-channel attacks in PaaS clouds. In ACM Conf. on Computer and Communications Security, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Y. Zhang, M. A. Laurenzano, J. Mars, and L. Tang. Smite: Precise QoS prediction on real-system smt processors to improve utilization in warehouse scale computers. In IEEE/ACM Intl. Symp. on Microarchitecture, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. F. Zhou, M. Goel, P. Desnoyers, and R. Sundaram. Scheduler vulnerabilities and coordinated attacks in cloud computing. In IEEE Intl. Symp. on Network Computing and Applications, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. S. Zhuravlev, S. Blagodurov, and A. Fedorova. Addressing shared resource contention in multicore processors via scheduling. In Intl. Conf. on Architectural Support for Programming Languages and Operating Systems, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image ACM Conferences
          ASIA CCS '17: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security
          April 2017
          952 pages
          ISBN:9781450349444
          DOI:10.1145/3052973

          Copyright © 2017 ACM

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          Publication History

          • Published: 2 April 2017

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          Acceptance Rates

          ASIA CCS '17 Paper Acceptance Rate67of359submissions,19%Overall Acceptance Rate418of2,322submissions,18%

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