low rate tcp targeted denial of service attacks the shrew vs the mice and elephants
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Low-Rate TCP-Targeted Denial of Service Attacks (The Shrew vs. the Mice and Elephants). Aleksandar Kuzmanovic Edward W. Knightly. Rice Networks Group http://www.ece.rice.edu/networks. Background. Traditional view of DoS attacks

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low rate tcp targeted denial of service attacks the shrew vs the mice and elephants

Low-Rate TCP-Targeted Denial of Service Attacks(The Shrew vs. the Mice and Elephants)

Aleksandar Kuzmanovic

Edward W. Knightly

Rice Networks Group

http://www.ece.rice.edu/networks

background
Background
  • Traditional view of DoS attacks
    • Attacker consumes resources and denies service to legitimate users
      • Ex. traffic floods, DDoS
      • Result: TCP backs off
    • Observe: statistical anomalies that are relatively easily detectable
      • Due to attacker’s high rate
thesis tcp is vulnerable to low rate attacks
Thesis: TCP is Vulnerable to Low-rate Attacks
  • Shrew: low-rate TCP-targeted attacks
    • Elude detection by counter-DoS mechanisms
    • Able to severely deny service to legitimate users
  • Goals
    • Analyze TCP mechanisms that can be exploited by DoS attackers
    • Explore TCP frequency response to Shrews
    • Evaluate detection mechanisms
    • Analyze effectiveness of randomization strategies
  • Methodology: modeling, simulations, Internet experiments
shrew
Shrew
  • Very small but aggressive mammal that ferociously attacks and kills much larger animals with a venomous bite
  • Reviewer 3: “only some shrews are venomous and the amount of venom in even the venomous species is very mild.”
tcp a dual time scale perspective
TCP: a Dual Time-Scale Perspective
  • Two time-scales fundamentally required
    • RTT time-scales (~10-100 ms)
      • AIMD control
    • RTO time-scales (RTO=SRTT+4*RTTVAR)
      • Avoid congestion collapse
  • RTO must be lower bounded to avoid spurious retransmissions
    • [AllPax99] and RFC2988 recommends minRTO = 1 sec
tcp timeline
TCP Timeline
  • Timeline of TCP congestion window
    • AIMD control
the shrew attack 1 3
The Shrew Attack (1/3)
  • Pulse-induced outage – multiple losses force TCP to enter RTO mechanism

Short outages (~RTT)force TCP to timeout

All flows simultaneously enter this state

the shrew attack 2 3
The Shrew Attack (2/3)
  • When flows attempt to simultaneously exit timeout and enter slow-start…
  • Shrew pulses again and forces flows synchronously back into timeout state
the shrew attack 3 3
The Shrew Attack (3/3)
  • Shrew periodically repeats pulse
    • RTT-time-scale outages inter-spaced on minRTO periods can deny service to TCP
    • Flows synchronize their state to the Shrew
shrew principles
Shrew Principles
  • Shrews exploit protocol homogeneity and determinism
    • Protocols react in a pre-defined way
    • Tradeoff of vulnerability vs. predictability
  • Periodic outages synchronize TCP flow states and deny their service
  • Slow time scale protocol mechanisms enable low-rate attacks
    • Outages at RTO scale, pulses at RTT scale imply low average rate
creating outages in the network
Creating Outages in the Network
  • Shrew: square-wave stream (l~RTT, T~minRTO)
    • Optimal pattern in paper
  • Low-rate “TCP friendly” DoS  hard to detect
    • Counter-DOS mechanisms tuned for high rate attacks
    • Detecting Shrews may have unacceptably many false alarms (due to legitimate bursty flows)
outline
Outline
  • Shrew attack
  • Simulation and Internet experiments
  • DoS detection mechanisms
  • minRTO randomization
the shrew in action
The Shrew in Action
  • How much is TCP

throughput degraded?

  • DoS stream:
      • R=C=1.5Mb/s;
      • l=70ms (~TCP RTT)
the shrew in action1
The Shrew in Action
  • Shrews induce null frequency near RTO
  • Shrew has low average rate  .08C
  • Analytical model accurately predicts degradation
challenges for shrews
Challenges for Shrews
  • Aggregation
    • Vulnerable due to Shrew-induced flow synchronization
  • RTT heterogeneity
    • Shrews are high-RTT pass filters
  • DoS peak rate
    • Less-than-bottleneck bursts can damage short-RTT flows
  • Short-lived TCP flows
    • Web browsing
  • Internet experiments
    • Can Shrews be successful on the Internet?
shrews vs short lived tcp traffic
Shrews vs. Short-lived TCP Traffic
  • Scenario: Web browsing [FGHW99]
    • Average damage to
      • a mouse (<100pkts)

=400% delay increase

      • an elephant (>100pkts)

=24500%delay increase

shrews vs short lived tcp traffic1
Shrews vs. Short-lived TCP Traffic
  • Scenario: Web browsing
    • Larger files more

vulnerable

      • most suffer
      • some benefit
internet experiments scenario
Internet Experiments: Scenario
  • Scenario: victim on a lightly loaded 10 Mb/sec LAN
  • Attacker on same LAN, nearby LAN, or over WAN
  • WAN path:
    • EPFLETH, 8 hops (10/100/OC-12)
internet experiments results
Internet Experiments: Results
  • Shrew average rate: 909 kb/sec
    • R = 10 Mb/sec, l = 100 msec, T = 1.1 sec
  • TCP throughput
    • 9.8 Mb/sec without Shrew
    • 1.2 Mb/sec with Shrew, 87.8% degradation
outline1
Outline
  • Shrew attack
  • Simulation and Internet experiments
  • Counter DoS mechanisms
    • Robust TCP variants (NewReno, Sack…)
    • Router detection mechanisms (RED, RED-PD, …)
  • minRTO randomization
detecting shrews
Detecting Shrews
  • Shrews have low average rate, yet send high-rate bursts on short time-scales
  • Key questions
    • Can algorithms intended to find high-rate attacks detect Shrews?
    • Can we tune the algorithms to detect Shrews without having too many false alarms?
  • A number of schemes can detect malicious flows
    • E.g., RED-PD:
      • use the packet drop history to detect high-bandwidth flows and preferentially drop packets from these flows
router assisted mechanisms
Router-Assisted Mechanisms
  • Scenario: 9 TCP Sack flows with RED and RED-PD
  • RED-PD only detects Shrews with unnecessarily high rate
  • Reducing RED-PD measurement time scale results in excessive false positives
outline2
Outline
  • Shrew attack
  • Simulation and Internet experiments
  • Counter DoS mechanisms
  • minRTO randomization
end point minrto randomization
End-point minRTO Randomization
  • Observe
    • Shrews exploit protocol homogeneity and determinism
  • Question
    • Can minRTO randomization alleviate threat of Shrews?
  • TCP flows’ approach
    • Randomize the minRTO = uniform(a,b)
  • Shrews’ counter approach
    • Given flows randomize minRTO, the optimal Shrew pulses at time-scale T=b
      • Wait for all flows to recover and then pulse again
end point minrto randomization1
End-point minRTO Randomization
  • TCP throughput for T=b time-scale of the Shrew attack
      • a small  spurious retransmissions [AllPax99]
      • b large  bad for short-lived (HTTP) traffic
  • Randomizing the minRTO parameter shifts and smoothes TCP’s null time-scales
  • Fundamental tradeoff between TCP performance and vulnerability to low-rate DoS attacks remains
conclusions
Conclusions
  • Shrew principles
    • Exploit slow-time-scale protocol homogeneity and determinism
  • Real-world vulnerability to Shrew attacks
    • Internet experiment: 87.8% throughput loss without detection
  • Shrews are difficult to detect
    • Low average rate and “TCP friendly”
    • Cannot filter short bursts
    • Fundamental mismatch of attack/defense timescales
open questions
Open Questions
  • Can filters specific to Shrews be designed without excessive false positives?
  • Can end-point algorithms be sufficiently randomized, so that
    • attackers cannot exploit their known reactions
    • performance is not sacrificed
  • Reconsider “TCP friendly” definition
aggregation
Aggregation
  • Homogeneous TCP aggregates are vulnerable
  • Shrews induce flow synchronization
  • Analytical model accurately predicts degradation

Scenario: 5 TCP flows, homogenous RTTs

dos peak rate
DoS Peak Rate
  • Less-than-bottleneck bursts

can damage short-RTT flows

    • Scenario: 4 TCP flows + DoS
      • 1 short-RTT & 3 long-RTT flows
      • DoS outage ~ RTT of

the short-RTT flow

dos peak rate1
DoS Peak Rate
  • Long-RTT flows inadvertently collaborate in the attack
  • DoS flow is masked with long-RTT TCP flows
tcp variants
TCP Variants
  • TCP Reno is the most fragile
  • NewReno? Sack?
  • Scenario:
    • TCP variants
      • Reno
      • New Reno
      • Tahoe
      • SACK
    • DoS stream
      • Burst rate equals the bottleneck capacity
      • Burst length:30ms, 50ms, 70ms, and 90ms
tcp variants1
TCP Variants
  • Burst length = 30ms
    • TCP Reno is the most fragile
tcp variants2
TCP Variants
  • Burst length = 50ms
    • TCP is the most vulnerable in 1-1.2 sec time-scale region due to slow start
tcp variants3
TCP Variants
  • All TCP variants obtain the same profile
    • Sufficient pulse width ensures timeout
    • Windows remain small
tcp variants4
TCP Variants
  • Burst length = 90ms
    • When burst length is severe enough ->

all TCP stacks are equally fragile

the role of time scales
The Role of Time-Scales
  • Scenario: R=2 Mb/s; T=1 sec; l~50-450 ms
the role of time scales1
The Role of Time-Scales
  • RED-PD detects l=300 ms shrews
    • Recall that 30 ms enough for DoS
  • A fundamental mismatch
    • If shorter time-scales are used =>
      • high false alarm probability (bursty TCP flows)
shrews vs heterogeneous rtts
Shrews vs. Heterogeneous RTTs
  • Hypothesis: Shrews are high-RTT-pass filters
    • Service is denied to short-RTT flows
flow filtering
Flow Filtering
  • Shrews damage short-RTT flows the most
    • Scenario
      • 20 TCP flows; RTT ~ 20-460 ms
      • Cut-off time scale ~ 180 ms
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