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Internet-scale malware mitigation: combining intelligence of the control and data plane
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Source Conference on Computer and Communications Security archive
Proceedings of the 4th ACM workshop on Recurring malcode table of contents
Alexandria, Virginia, USA
SESSION: Worm characterization table of contents
Pages: 33 - 40  
Year of Publication: 2006
ISBN:1-59593-551-9
Authors
Ying Zhang  University of Michigan
Evan Cooke  University of Michigan
Z. Morley Mao  University of Michigan
Sponsors
ACM: Association for Computing Machinery
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
Publisher
ACM  New York, NY, USA
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ABSTRACT

Security on the Internet today is treated mostly as a data plane problem. IDS's, firewalls, and spam filters all operate on the simple principle of detecting malicious data plane behavior and erecting data plane filters. In this paper we explore how breaking down the barrier between the control and data plane can significantly enhance our understanding of how to detect and filter Internet threats like worms and botnets. Our investigation is guided by two specific goals: using information and anomalies detected on the data plane to inform control plane decision support and using anomalies detected on the control plane to inform data plane filtering. We begin by analyzing the source of persistent worms and other persistent malicious and misconfigured data plane traffic to understand the scope of this behavior on the control plane. We then analyze how anomalies on the control plane associated with poorly managed networks and are correlated with the sources of malicious and misconfigured traffic detected on the data plane. Our results show that malicious and misconfigured data plane behavior is widely spread across the control plane suggesting that constructing a few control plane filters to block the most infected organizations will not have a significant impact. We demonstrate that networks with data plane anomalies tend to exhibit more routing misconfigurations. Finally, we discuss how these correlations could be used to reject or filter routes and help stop recurring threats like persistent worms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Ying Zhang: colleagues
Evan Cooke: colleagues
Z. Morley Mao: colleagues