bohatei: flexible and elastic ddos...

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Ideas Challenges Implementation Responsiveness Key Results Bohatei: Flexible and Elastic DDoS Defense Seyed K. Fayaz * , Yoshiaki Tobioka * , Vyas Sekar * , Michael Bailey u * Carnegie Mellon University, u University of Illinois at Urbana-Champaign Adversary resilience Fixed location Flexibility in traffic steering using SDN Elasticity in defense deployment using NFV DDoS attacks are increasing in number, volume, and diversity. Motivation Vision: Enabling Flexible and Elastic Defense using Bohatei Bit Rate Price 1Gbps $11,000-$38,000 4Gbps $68,000 12Gbps $128,000 Price of DDoS Defense Appliances Scalability DDoS defense today relies on proprietary hardware appliances deployed at fixed locations. Fixed capacity Fixed functionality High capital cost Can we build a flexible and elastic DDoS defense platform that can handle attacks with varying type, volume, and location? Bohatei envisions a four-step workflow: 1. Attack detection (using existing methods) 2. Estimation of volume of attack traffic 3. Resource management 4. Network orchestration Bohatei Key Ideas 1- Responsive resource management: Optimal decision making about the number and type of defense VMs takes hours. 2- Scalable network orchestration: The existing SDN approach to set up switch forwarding rules in a per-flow and reactive manner swamps the SDN controller. 3- Coping with dynamic adversaries that may quickly change the type, volume, and ingress of attack. 1- Hierarchical optimization decomposition: The ISP-wide controller determines how many and what types of VMs to run in each datacenter Each per-datacenter controller determines the specific server on which each defense VM will run. 2- Proactive tag-based forwarding: Forwarding rules based on per-VM tags Pro-active switch configuration 3- Online adaptation: A defense strategy adaptation approach inspired by online algorithms for minimizing regret (i.e., how much better we could have done in retrospect) Today: Hardware appliance res. footprint=240Gbps Ideal: Elastic scaling res. footprint=130Gbps t 1 t 2 t 3 time 40 80 10 attack vol. (Gbps) Today: hardware appliance res. footprint=420Gbps Ideal: elastic scaling res. footprint=250Gbps t 1 t 2 t 3 time 60 60 10 attack vol. (Gbps) SYN flood DNS amp. 20 20 80 A C B DDoS defense appliance flow 1 flow 2 Today: traffic footprint given hardware appliance=3 hops Ideal: traffic footprint given elastic scaling=2 hops A C B VM VM flow 1 flow 2 Fundamental limitations of the current approach: 1. High capital cost 2. Fixed capacity 3. Fixed functionality 4. Fixed location 2. Strategy legit. traffic traffic path set up ISP a3ack traffic project homepage DC 2 DC 1 customer defense policy library 3. Resource management es@ma@on of volume of suspicious traffic of each a3ack type at each ingress 4. Orchestra6on quan@ty and loca@on of VMs VM 1. Detec@on mechanism provides suspicious traffic specifica@on <A1, Defense Graph1> <A n , Defense Graph n > legit. traffic VM Bohatei global SDN controller Bohatei local SDN controller Bohatei Workflow Implementation of a Bohatei controller using OpenDaylight Use of open source tools (e.g., OpenvSwitch, Snort, Bro, iptables) as defense modules Evaluation on a real testbed as well as using simulations Code is made available 2 6 10 0 20 40 60 80 100 120 140 Benign traffic throughput (Gbps) Time (s) attack starts SYN flood DNS amp. Elephant flow UDP flood Bohatei responds rapidly (<1 min) to diverse attacks. 10 1,000 100,000 10e+06 100 200 300 400 500 Max required number of rules on a switch Attack traffic volume (Gbps) Bohatei per-flow rules Handling ~1Tbps attacks requires <1K rules on a switch 0 10 20 30 40 50 60 RandIngress RandAttack RandHybrid Steady FlipPrevEpoch Regret w.r.t. volume of successful attacks (%) Uniform PrevEpoch Bohatei Bohatei’s online adaptation achieves low regret check UDP count of src fwd log rate limit traffic Sample defense graph http:// silver.web.unc.edu Cloud Security Horizons Summit, March 2016

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Page 1: Bohatei: Flexible and Elastic DDoS Defensesilver.web.unc.edu/files/2016/06/Bohatei_poster_silver.pdf · 2016-07-03 · approach to set up switch forwarding rules in a per-flow and

Ideas Challenges

Implementation Responsiveness Key Results

Bohatei: Flexible and Elastic DDoS Defense Seyed K. Fayaz*, Yoshiaki Tobioka*, Vyas Sekar*, Michael Baileyu

*Carnegie Mellon University, uUniversity of Illinois at Urbana-Champaign

Adversary resilience

Fixed location

•  Flexibility in traffic steering using SDN •  Elasticity in defense deployment using NFV

DDoS attacks are increasing in number, volume, and diversity.

Motivation

Vision: Enabling Flexible and Elastic Defense using Bohatei

Bit Rate Price 1Gbps $11,000-$38,000 4Gbps $68,000 12Gbps $128,000

Price of DDoS Defense Appliances

Scalability

DDoS defense today relies on proprietary hardware appliances deployed at fixed locations.

Fixed capacity

Fixed functionality High capital cost

Can we build a flexible and elastic DDoS defense platform that can handle attacks with varying type, volume, and location?

Bohatei envisions a four-step workflow: 1.  Attack detection (using existing methods) 2.  Estimation of volume of attack traffic 3.  Resource management 4.  Network orchestration

Bohatei Key Ideas

1- Responsive resource management: Optimal decision making about the number and type of defense VMs takes hours.

2- Scalable network orchestration: The existing SDN approach to set up switch forwarding rules in a per-flow and reactive manner swamps the SDN controller.

3- Coping with dynamic adversaries that may quickly change the type, volume, and ingress of attack.

1- Hierarchical optimization decomposition: •  The ISP-wide controller determines how many and what types of

VMs to run in each datacenter •  Each per-datacenter controller determines the specific server on

which each defense VM will run. 2- Proactive tag-based forwarding: •  Forwarding rules based on per-VM tags •  Pro-active switch configuration

3- Online adaptation: A defense strategy adaptation approach inspired by online algorithms for minimizing regret (i.e., how much better we could have done in retrospect)

Today: Hardware appliance res. footprint=240Gbps

Ideal: Elastic scaling res. footprint=130Gbps

t1 t2 t3 time

40

80

10

attack vol. (Gbps)

Today: hardware appliance res. footprint=420Gbps

Ideal: elastic scaling res. footprint=250Gbps

t1 t2 t3 time

60 60

10

attack vol. (Gbps)

SYN flood DNS amp.

20 20

80

A C

B

DDoS defense appliance flow1

flow2

Today: traffic footprint given hardware

appliance=3 hops

Ideal: traffic footprint given elastic scaling=2 hops

A C

B

VM VM VM

VM VM VM

flow1

flow2

Fundamental limitations of the current approach:

1.  High capital cost 2.  Fixed capacity 3.  Fixed functionality 4.  Fixed location

2.Strategy

legit.traffic

trafficpathsetup

ISP

a3acktraffic

project homepage

DC2DC1

customer

defensepolicylibrary

3.Resourcemanagement

es@ma@onofvolumeofsuspicioustrafficofeacha3acktypeateachingress

4.Orchestra6on

quan@tyandloca@onofVMs

• VM • VM VM

1.Detec@onmechanismprovidessuspicious

trafficspecifica@on

<A1, Defense Graph1> …

<An, Defense Graphn>

legit.traffic

• VM • VM VM

BohateiglobalSDNcontrollerBohateilocalSDNcontroller

Bohatei Workflow

•  Implementation of a Bohatei controller using OpenDaylight

•  Use of open source tools (e.g., OpenvSwitch, Snort, Bro, iptables) as defense modules

•  Evaluation on a real testbed as well as using simulations

•  Code is made available

26

10

0 20 40 60 80 100 120 140

Be

nig

n t

raff

icth

rou

gh

pu

t (G

bp

s)

Time (s)

attack starts

SYN floodDNS amp.

Elephant flowUDP flood

Bohatei responds rapidly (<1 min) to diverse attacks.

10

1,000

100,000

10e+06

100 200 300 400 500Ma

x r

eq

uire

d n

um

be

ro

f ru

les o

n a

sw

itch

Attack traffic volume (Gbps)

Bohateiper-flow rules

Handling ~1Tbps attacks requires <1K rules on a

switch

0

10

20

30

40

50

60

RandIngress

RandAttack

RandHybrid

SteadyFlipPrevEpoch

Re

gre

t w

.r.t

. vo

lum

eo

f su

cce

ssfu

l a

tta

cks (

%)

UniformPrevEpoch

Bohatei

Bohatei’s online adaptation achieves low

regret

checkUDPcountofsrc

fwdlog

ratelimit

traffic

Sample defense graph

http://silver.web.unc.edu Cloud Security Horizons Summit, March 2016