OpenFlow Research on the Georgia Tech Campus Network

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OpenFlow Research on the Georgia Tech Campus Network. Russ Clark Nick Feamster Students: Yogesh Mundada, Hyojoon Kim, Ankur Nayak, Anirudh Ramachandran, Umayr Hassan. Summary of Research Projects. Campus Network Deployment Resonance: Dynamic Access Control for Campus Networks - PowerPoint PPT Presentation

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OpenFlow Research on the Georgia Tech Campus Network

Russ ClarkNick Feamster

Students: Yogesh Mundada, Hyojoon Kim, Ankur Nayak, Anirudh

Ramachandran, Umayr Hassan

2

Summary of Research Projects

• Campus Network Deployment– Resonance: Dynamic Access Control for Campus Networks – Pedigree: Traffic Tainting for Securing Enterprise Networks

• Home Network Deployments– User-Proof Networking (with Prof. Keith Edwards)

• Class Projects: Network Management/Network Security– OpenFlow Traffic Classification– SNMP MIB for OpenFlow– Home-Network Management using OpenFlow– OpenFlow for High Availability/Service Migration– OpenFlow and Virtualization – Access Control for Home Networks– Automated Intrusion Detection with OpenFlow

3

Dynamic Access Control

• Enterprise and campus networks are dynamic– Hosts continually coming and leaving

– Hosts may become infected

• Today, access control is static, and poorly integrated with the network layer itself

• Resonance: Dynamic access control– Track state of each host on the network

– Update forwarding state of switches per host as these states change

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Authentication at GT: “START”

3. VLAN with Private IP

6. VLAN with Public IP

.1. New MAC Addr 2. VQP

7. REBOOT

Web Portal

4. Web Authentication 5. Authentication

Result

VMPS

Switch

New Host

5

Problems with Current Approach

• Access Control is too coarse-grained– Static, inflexible and prone to misconfigurations– Need to rely on VLANs to isolate infected machines

• Cannot dynamically remap hosts to different portions of the network– Needs a DHCP request which for a windows user

would mean a reboot

• Monitoring is not continuous

Idea: Access control policies should reflect network dynamics.

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Resonance Approach

• Step 1: Controller associates each host with generic states and security classes.

• Step 2: Specify a state machine for moving machines from one state to the other.

• Step 3: Control forwarding state in switches based on the current state of each host.

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Applying resonance to START

Registration

AuthenticatedOperation

Quarantined

SuccessfulAuthentication

Vulnerability detected

Clean after update

Failed Authentication

Infection removed or manually fixed

Still Infected afte

r an update

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Challenges

• Scale– How many forwarding entries

per switch?– How much traffic at the

controller?

• Performance– Responsiveness

• Security– MAC address spoofing– Securing the controller (and

control framework)

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Enterprise Information Flow Control• Goal: Control how information flows between different

hosts in the network– Control the spread of malware– Prevent data leaks

• Challenges– Heterogeneous devices– Hosts may not be trusted

• Solution: Pedigree– Classify traffic based on

• What process generated the traffic• Where that process has taken inputs

– Implement control policies in the network

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Pedigree Design• Trusted tagging

component resides on host.

• Traffic carries taints that reflect provenance of network traffic.

• Switch one hop from hosts makes access control decisions.

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Current FunctionInternet

1. Host sends request over control channel toopen with flow with taint set.

2. Traffic diverted to controller,which checks policy.

3. Controller inserts flowtable entry, if policy compliant.