path disruption games (cooperative game theory meets network security)

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Path Disruption Games (Cooperative Game Theory meets Network Security) Yoram Bachrach, Ely Porat Microsoft Research Cambridge

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Path Disruption Games (Cooperative Game Theory meets Network Security). Yoram Bachrach , Ely Porat Microsoft Research Cambridge. Agenda. Hospitals and Cost Sharing. Three private hospitals need an X-Ray machine Optimal solution Two cheap machines cost £10M Buy the £9M machine share it - PowerPoint PPT Presentation

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Page 1: Path Disruption Games (Cooperative Game Theory meets Network Security)

Path Disruption Games(Cooperative Game Theory meets Network Security)

Yoram Bachrach, Ely PoratMicrosoft Research Cambridge

Page 2: Path Disruption Games (Cooperative Game Theory meets Network Security)

Agenda

Page 3: Path Disruption Games (Cooperative Game Theory meets Network Security)

Hospitals and Cost Sharing• Three private hospitals need an X-Ray machine

• Optimal solution – Two cheap machines cost £10M– Buy the £9M machine share it

• Private sector problem– Private hospitals negotiate

• What to buy• How to share the costs

Machine Cost Serving

Cheap £5M 2 hospitals

Expensive £9M 3 hospitals

Page 4: Path Disruption Games (Cooperative Game Theory meets Network Security)

X-Ray Problem

• Some hospital pair must pay at least £6M• These hospitals can simply buy the cheap

machine and pay only £5M• Any cost sharing agreement is unstable

p1 p2 p3

£9M

Page 5: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island

• Jim, Billy and Smollett are looking for a buried treasure, worth a £1000– Billy and Jim each have half of the map

• Each half is useless on its own

– Smollett has a ship that can sail to treasure island• Renting a ship from anyone else costs £800

– v(J)=v(B)=v(S)=v(J,S)=v(B,S)=£0– v(J,B)=£200– V(J,B,S)=£1000

• How should they split the gains?

Page 6: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island – Forming Coalitions

£200 £1000

Page 7: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island – Sharing Rewards

–Some agreements won’t last long, and others are stable• E.g. giving Smollett £900 and Jim and Billy £50 each

–What is a fair way to divide the money?• Cannot win without Jim and Billy• Smollett’s ship really helps the gains

p1 p2 p3

£1000

Page 8: Path Disruption Games (Cooperative Game Theory meets Network Security)

UK Elections 2010: Budgets and Politics

• No party had the required majority (326 seats)– Hung parliament

• Second time since World War II – Previous time was 1974

• First coalition government to eventuate from elections– The Lib-Dems only had 57/650=8.8% of seats

• But large influence on policy• Other alternative for the conservatives – government with labour

– Not very appealing to the conservatives…

Conservatives Labour Lib-Dems306 258 57

Page 9: Path Disruption Games (Cooperative Game Theory meets Network Security)

An Alternate Universe

• Would the Conservatives be more powerful or less powerful in this alternate universe?– Intuition: much more alternatives to choose from!

• What determines the balance of power?– Suppose parties have to allocate a budget…

Conservatives Labour Liberals Democrats306 258 28 29

Page 10: Path Disruption Games (Cooperative Game Theory meets Network Security)

Cooperative Games

• Agents must cooperate to achieve their goals…• … but are still selfish– Maximize their share of the rewards– Obtain the outcome maximizing their utility– Minimize their own cost– Maximize their influence

• What teams and agreements would form?

Page 11: Path Disruption Games (Cooperative Game Theory meets Network Security)

Coalitional Game Theory

Page 12: Path Disruption Games (Cooperative Game Theory meets Network Security)

Transferable Utility Games• Agents: • Coalition:• Characteristic function:

– Two flavors: cost and surplus sharing

• Simple coalitional games:– Coalitions either win or lose

• Monotone games => – More agents => More money

• Super-additive games – It is always worthwhile for coalitions to merge– The Grand Coalition would form

Page 13: Path Disruption Games (Cooperative Game Theory meets Network Security)

Transferable Utility Games

Page 14: Path Disruption Games (Cooperative Game Theory meets Network Security)

Agent properties• Veto agent

– Can’t win without the agent (simple games)– Can’t generate any value without the agent (Non-simple games)

• Dummy agent– Never contributes to any coalition

• Equivalent agents , => – Contribute equally to any coalition that contains neither of them

• Critical agent for a coalition– The coalition wins with the agent, but loses without the agent

Page 15: Path Disruption Games (Cooperative Game Theory meets Network Security)

• Imputations define how the total utility is distributed• A payoff vector such that • Individual rationality

– Otherwise, an agent can do better alone• The payoff of a coalition C is• A coalition C is blocking if p(C) < v(C)

Payoffs

Page 16: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island – Imputations

–Is the vector p=(900,50,50) blocked? By what coalition?–What about p=(100,500,400)?–And p=(100,899,1)?–Or p=(0,1,999)?

• Stability does not mean fairness!

p1900£

p250£

p350£

1000£

Page 17: Path Disruption Games (Cooperative Game Theory meets Network Security)

• All imputations that are not blocked by any coalition• For any coalition C, p(C) ≥ v(C)

– For cost sharing games, the inequality is reversed

• No coalition is incentived to defect from the grand coalition• Gillies (1953) and von Neumann & Morgenstein (1947)

The Core (Stability)

Page 18: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island – the Core

• Two coalitions can block:

• Only need to make sure get at least 200£

p1 p2 p3

1000£

£200 £1000

Page 19: Path Disruption Games (Cooperative Game Theory meets Network Security)

X-Ray Problem – the Core

• c1 + c2 + c3 = £9M– For any imputation c, some pair must pay at least £6M

• So ci+cj > 5– However v( {I,j} ) = 5– Thus any imputation c is blocked by some pair {i,j}

• The core is empty

c1 c2 c3

£9M

Page 20: Path Disruption Games (Cooperative Game Theory meets Network Security)

Weighted Voting Games (WVG)

• Set of agents• Each agent has a weight • A game has a quota• A coalition C wins if • A simple game (coalitions either win or lose)

ia A iw R

i

ia C

w q

q

Page 21: Path Disruption Games (Cooperative Game Theory meets Network Security)

WVGs and the UK Elections

• Game 1: [306, 258, 57; 326]

• Game 2: [306, 258, 28, 29; 326]

• What is a fair way of allocating the budget?• How does this “weight splitting” affect power?– Is power proportional to the weight?

Conservatives Labour Lib-Dems306 258 57

Conservatives Labour Liberals Democrats306 258 28 29

Page 22: Path Disruption Games (Cooperative Game Theory meets Network Security)

Power in WVGs• Consider

– No single agent wins– Any coalition of two agents wins– The grand coalition wins– No agent has more power than any other

• Voting power is not proportional to voting weight– Ability to change the outcome of the game with your vote– How do we measure voting power?

1 2 351, 50, 26, 26q w w w

Page 23: Path Disruption Games (Cooperative Game Theory meets Network Security)

Fairness

• Return of the Pirates

Treasure Island (1000£) Treasure Cave (2000£)

Page 24: Path Disruption Games (Cooperative Game Theory meets Network Security)

Fairness Requirements• A solution concept maps a game (characteristic function) to an

imputation for that game• Efficiency Axiom: • Dummy Axiom: dummy agents get nothing• Symmetry Axiom: Equivalent agents get the same• Additivity axiom:

– If a game is composed of two sub-games• (v+w)(C) = v(C)+w(C)• E.g. playing both treasure island and treasure cave

– Then an agent’s payoff in v+w is the sum of her payoffs in v and in w

• Is there a solution concept that fulfills all these fairness axioms?

Page 25: Path Disruption Games (Cooperative Game Theory meets Network Security)

Marginal Contribution

• Treasure island

• The coalition has a value of 0£– No full map

• The coalition has a value of 1000£

• Agent has a marginal contribution of 1000£-0£=10000£ to coalition

Page 26: Path Disruption Games (Cooperative Game Theory meets Network Security)

Marginal Contribution

• Treasure island

• The coalition has a value of 200£– Full map, no ship

• The coalition has a value of 1000£

• Agent has a marginal contribution of 1000£-200£=800£ to coalition

Page 27: Path Disruption Games (Cooperative Game Theory meets Network Security)

The Shapley Value: Fairness• Given an ordering of the agents in I, denotes the set

of agents that appear before i in• The Shapley value is an agent’s marginal contribution to its

predecessors, averaged across all permutations• The only solution concepts that fulfills all of the previously

defined fairness axioms • Can also be used to measure power

Page 28: Path Disruption Games (Cooperative Game Theory meets Network Security)

Treasure Island – the Shapley Value

0 0 1000

0 1000 0

0 0 1000

800 0 200

800 200 0

0 1000 0

Average 266.66 366.66 366.66

Page 29: Path Disruption Games (Cooperative Game Theory meets Network Security)

Power Indices

• Power in weighted voting games can be computed using the Shapley value– WVGs are simple games

• The Shapely value measures the proportion of coalitions where an agent is critical

• Each permutation has exactly one critical agent• Simple generative model

• Are there alternative models or power indices?

Page 30: Path Disruption Games (Cooperative Game Theory meets Network Security)

Power in the UK Elections

• Game 1: [306, 258, 57; 326]

• Game 2: [306, 258, 28, 29; 326]

• Split makes the labour less powerful– But the power goes to the conservatives…– … not the Lib-Dems

Conservatives Labour Lib-Dems306 258 57

66.66% 16.66% 16.66%

Conservatives Labour Liberals Democrats306 258 28 29

75% 8.33% 8.33% 8.33%

Page 31: Path Disruption Games (Cooperative Game Theory meets Network Security)

Security in Networks

• Physical network security– Placing checkpoints – Locations for routine checks

• Network security– Protecting servers and links from attacks

• Various costs for different nodes and links– How easy it is to deploy a check point– Performance degradation for protected servers

• How should the budget be spent on security resources?

Page 32: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 33: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 34: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 35: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 36: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 37: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 38: Path Disruption Games (Cooperative Game Theory meets Network Security)

Blocking an adversary

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Page 39: Path Disruption Games (Cooperative Game Theory meets Network Security)

Incorporating costs

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2

5

3

3

2

1

2

2

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Page 40: Path Disruption Games (Cooperative Game Theory meets Network Security)

Incorporating costs

s

t8

2

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3

3

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1

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7

Page 41: Path Disruption Games (Cooperative Game Theory meets Network Security)

Network Security Hotspots• Agents must for coalitions to successfully block the adversary

– Obtain a certain reward or budget for achieving the task– How should this reward be shared between the agents

• Stability– No subset of the coalition should have an incentive to form an alternative coalition

• Fairness– Reflect the contribution of the each agent

• Security resources are limited– Which node / link should be allocated these resources first?– Power indices allow finding such reliability hotspots

Page 42: Path Disruption Games (Cooperative Game Theory meets Network Security)

Path Disruption Games• Games played on a graph G=<V,E> (a network)

– Simple version (PDGs): coalition wins if it can block the adversary and loses otherwise

– Model with costs (PDGCs): a coalition is guaranteed a reward r for blocking the adversary, but incurs the cost of its checkpoints

Page 43: Path Disruption Games (Cooperative Game Theory meets Network Security)

Power and Security

• Suppose all check points have equal probability,50%, of blocking the adversary or not blocking– We have limited security resources– Which nodes should be protected first?

• “Powerful” nodes are more critical– Suppose we can only choose one node where the adversary is blocked

with 100% probability – The Banzhaf index of a node is the probability of stopping the

adversary when:• This node blocks with probability 100%• All other nodes block with probability of 50%

Page 44: Path Disruption Games (Cooperative Game Theory meets Network Security)

Stability in PDGs: the Core

• Given a reward for blocking the adversary what check point coalitions would form?– We want the agents to work under enforceable contracts:

• Which check points are used and • How to share the reward

• The core constitutes a stable allocation– A distribution not in the core would break down the

coalition structure– Unable to agree on a contract and infinite negotiation

Page 45: Path Disruption Games (Cooperative Game Theory meets Network Security)

Results

• PDGs (several adversaries, no cost)– Can test for veto agents and compute the core in

polynomial time– Computing the maximal excess for an imputation

(payoff vector) is NP-complete• NP-hard to compute the least core

– Testing for dummy agents is coNP-Complete– Computing the Banzhaf index is #P-complete• But for trees it is computing in polynomial time

Page 46: Path Disruption Games (Cooperative Game Theory meets Network Security)

Results (cont.)

• Model with costs (PDGCs):– Computing the value of a coalition is NP-hard• Min cost vertex cut

– Can do better for trees

Page 47: Path Disruption Games (Cooperative Game Theory meets Network Security)

Conclusion & Future Directions

• Suggested a game theoretic model for network security based on blocking adversaries

• Future work– Other solution concepts: power indices, nucleolus, kernel– More complex network security domains