NICE: Network intrusion detection and countermeasure selection in virtual network systems

Chun Jen Chung, Pankaj Khatkar, Tianyi Xing, Jeongkeun Lee, Dijiang Huang

Research output: Contribution to journalArticlepeer-review

244 Scopus citations

Abstract

Cloud security is one of most important issues that has attracted a lot of research and development effort in past few years. Particularly, attackers can explore vulnerabilities of a cloud system and compromise virtual machines to deploy further large-scale Distributed Denial-of-Service (DDoS). DDoS attacks usually involve early stage actions such as multistep exploitation, low-frequency vulnerability scanning, and compromising identified vulnerable virtual machines as zombies, and finally DDoS attacks through the compromised zombies. Within the cloud system, especially the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is extremely difficult. This is because cloud users may install vulnerable applications on their virtual machines. To prevent vulnerable virtual machines from being compromised in the cloud, we propose a multiphase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph-based analytical models and reconfigurable virtual network-based countermeasures. The proposed framework leverages OpenFlow network programming APIs to build a monitor and control plane over distributed programmable virtual switches to significantly improve attack detection and mitigate attack consequences. The system and security evaluations demonstrate the efficiency and effectiveness of the proposed solution.

Original languageEnglish (US)
Article number6419708
Pages (from-to)198-211
Number of pages14
JournalIEEE Transactions on Dependable and Secure Computing
Volume10
Issue number4
DOIs
StatePublished - 2013

Keywords

  • Attack graph
  • Cloud computing
  • Intrusion detection
  • Network security
  • Zombie detection

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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