Stubborn Mining : Generalizing Selfish Mining and Combining - PowerPoint Presentation

Slide1

Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack

With Srijan Kumar, Andrew Miller and Elaine Shi

1

Kartik

NayakSlide2

2

Alice

Bob

Charlie

Emily

Blockchain

Bitcoin Mining

Dave

Fairness: If Alice has 1/4

th

computation power, she gets 1/4

th

of the total rewardSlide3

3

Selfish Mining

[ES’14]

If Alice deviates from the protocol, can she gain more?

Yes!

Computation power > 0.33

Alice

Emily

Charlie

Bob

DaveSlide4

4Prior work:Selfish Mining

One way of deviating so that one miner earns more revenue at the expense of others

Stubborn Mining

We show other attacks in the same model that perform better than selfish mining

Earn

~$137,000

/ day more than by Selfish Mining attack

1

Our Contribution:

All miners earn

~$1.5 M

/ daySlide5

5

Eclipse Attacks

[HKZG’15]

World 1

World 2

Alice can double-spend

Compose Stubborn Mining and Eclipse Attacks

Alice

Bob

Charlie

Emily

Dave

2

Our Contribution:Slide6

61

2

Compose Stubborn Mining and Eclipse Attacks

Stubborn Mining

Key Contributions

Sometimes, the best strategies benefit the “victim”

Both of these attacks are better than were previously known for the attackerSlide7

7Selfish Mining(in more detail)

Alice

Emily

Charlie

Bob

Dave

Alice

(α)

Public

(β)

γ: Alice’s ability to win race conditions

(α, γ): network model parameters

40%: Ghash.IO largest pool in 2014

α

41%: two largest mining pools

21%: largest mining pool

γ

0-0.92: depending on attacker’s influence

https://blockchain.info/pools - May 16, 2015Slide8

8Selfish Mining(in more detail)

Public’s view

0

1

α

2

α

3

α

β

β

Alice’s private chain

Alice

(α)

Public

(β)

γ: Alice’s ability to win race conditions

(α, γ): network model parametersSlide9

9Selfish Mining(in more detail)

Alice

(α)

Public

(β)

Public’s view

0

1

α

2

α

3

α

β

βSlide10

10Selfish Mining(in more detail)

Alice

(α)

Public

(β)

Public’s view

0

1

α

2

α

3

α

β

β

0’

β

α

γβ

(1-γ)β

γ:

Fraction of public mining on Alice’s block

Alice’s private chain

A strategy where Alice reveals blocks under certain conditionsSlide11

11Our Contribution: Stubborn Mining

Intuition:

A selfish miner gives up too easily

Three stubborn mining strategies

:

Lead Stubborn Mining

Equal-Fork Stubborn

Mining

Trail Stubborn MiningSlide12

12Lead Stubborn Mining

Alice

(α)

Public

(β)

0

1

α

2

α

3

α

β

β

0’

β

α

γβ

(1-γ)β

Public’s view

2’

α

1’

β

Alice’s private chainSlide13

13Equal-Fork Stubborn Mining

Alice

(α)

Public

(β)

0

1

α

2

α

3

α

β

β

0’

β

α

γβ

(1-γ)β

Public’s view

Alice’s private chainSlide14

14Trail Stubborn Mining

Alice

(α)

Public

(β)

0

1

α

2

α

3

α

β

β

0’

β

α

γβ

(1-γ)β

Public’s view

-1

(1-γ)β

Alice’s private chainSlide15

15Hybrid Stubborn Mining Strategies

S

L

F

T

1

Lead Stubbornness

Equal-Fork Stubbornness

Trail Stubbornness

LF

T

2

LT

1

FT

1

LFT

1Slide16

16

There is no one-size-fits-all dominant strategy.

γ:

Alice’s network influence

(fraction of public mining on Alice’s chain in case of a fork)

Results

MonteCarlo

simulations

Multiple

samples and report meanSlide17

17

For a large parameter space, Stubborn Mining strategies perform better than Selfish Mining.Slide18

18

Trail stubborn strategies perform better than non-trail-stubborn counterparts when

α

> 0.33Slide19

19

Attacker’s Revenue: Compared to Honest Miningα = 0.4, γ = 0.9

63% higher revenue

Increase in revenue:

~$375,000

/ daySlide20

20

Attacker’s Revenue: Compared to Selfish Miningα = 0.4, γ = 0.9

23% higher revenue

Increase in revenue:

~$137,000

/ daySlide21

21

Eclipse Attacks

(reminder)

World 1

World 2

Alice

Bob

Lucy

Emily

DaveSlide22

22

Eclipse Attacks

(reminder)

World 1

World 2

Alice

Bob

Lucy

Emily

Dave

Alice

(α)

Public

(β)

Lucy

(

λ

)

λ

< βSlide23

23Exploiting Eclipse Attack Victims

Alice

(α)

Public

(β)

Lucy

(

λ

)

1. Forward all messages – no eclipsing

2. Partition all messages – waste Lucy’s computation power

3. Collude with Lucy

4. Destroy if no stake (DNS)

No Eclipsing

Partition all messages

Collude with Lucy

Destroy if no stake

Eclipsing degreeSlide24

24

Non-trivial compositions of Stubborn Mining + Eclipsing outperform naïve strategies

8%

gain

Alice’s relative gain

wrt

naïve

Dominant Strategies

Naïve: Honest/Selfish Mining – Stubbornness, Collude/Destroy Lucy - EclipsingSlide25

25

Gain compared to Selfish Mining

25%

gain

Alice’s relative gain

wrt

Selfish MiningSlide26

26

The attack may benefit Lucy

Lucy’s relative gain:Slide27

27Detecting and inferring attacks

Are these attacks likely to occur?

Discussed in the paper

Countermeasures?

Dispersed mining power

Selfish Mining not observed until now

~$375,000 / day

Other cryptocurrenciesSlide28

28Conclusion

1

2

Compose Stubborn Mining and Eclipse Attacks

Stubborn

Mining

kartik@cs.umd.edu

Thank You!

Dominant Strategies