2012.12 Games We Play: Defenses & Disincentives
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This document provides an overview of game theory concepts and how they can be applied to information security issues. It discusses how security situations can be framed as games with defensive and offensive players making strategic decisions based on potential costs and benefits. Examples of typical game theory models are explained like the Prisoner's Dilemma. The document also notes that real-world behavior may not always match rational models, and that understanding human biases is important for developing effective defense strategies. Overall, it argues that risk management involves managing decisions in a game-like framework where outcomes depend on the choices of multiple players.
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2012.12 Games We Play: Defenses & Disincentives
- 1. Games We Play Defenses and Disincentives Allison Miller
- 2. Overview Overview of econ & game theory concepts Game theory games Infosec issues as games Designing games to win Walk-through a defense built on disincentives Wrap-up
- 3. Economics applied to security Utility theory Externalities Information Asymmetries Signaling Marginal cost
- 4. Game theory Branch of applied mathematics Studies decisions made by players interacting (or competing) - Scenarios have rules and pay-offs - Costs & benefits dependent on decisions of other players Used as a framework in economics, comp sci, biology, & philosophy - Also business, negotiation, and military strategy
- 5. Discussing Games Mechanics of a payoff matrix Player 2 A B Player 1 A A1, A2 A1, B2 B B1, A2 B1, B2
- 6. Discussing Games Mechanics of decision trees UP DOWN CIRCLE RED BLUE MARIO LUIGI KIRBY GIZMO 10, 3 2, 10 2, 5 -3, 3 A B B A A A
- 7. Typical game theory "games" Chicken / Brinkmanship - Push it to the edge Volunteer’s Dilemma - For the greater good Tragedy of the Commons - Share and share alike (cumulative effect of cheating) Prisoner’s Dilemma
- 8. Discussing Games Prisoner’s Dilemma Player 2 Keep quiet Confess Player 1 Keep quiet -1, -1 Mutual cooperation 0, -10 Individual defection Confess -10, 0 Individual defection -3, -3 Mutual punishment
- 10. Nash Equilibrium Equilibrium is reached when: - Players in a game have selected a strategy - Neither side can change it’s strategy independently & improve position Optimal solution in games with limited outcomes
- 11. Discussing Games Prisoner’s Dilemma Player 2 Keep quiet Confess Player 1 Keep quiet -1, -1 Mutual cooperation 0, -10 Individual defection Confess -10, 0 Individual defection -3, -3 Mutual punishment
- 12. Setting up risk problems as games Identify players in the game Clarify the “rules” Show me your moves Describe payoffs Single move or repeated game
- 13. Discussing Games Tragedy of the Commons: Spam, Bandwidth usage Everyone else’s choices > n choose wise usage Less than n choose wise usage Individual choice Use resource wisely Cost, but social benefit Mutual cooperation Cost (Subsidize social use) Overuse resource Social benefit (Benefit w/o cost) 0 Resources depleted
- 14. Discussing Games Chicken/Brinkmanship: Vulnerability Disclosure Vulnerability Researcher Report Exploit Asset Owner Reward / Respond 0, 0 Responsible disclosure -2, +2 Early disclosure Ignore / Deny +2, -2 Defer vulnerability -10, -10 0-day go boom
- 15. Discussing Games Volunteer’s Dilemma: Data breach cost info sharing All other victims At least one shares All keep quiet Victim Share 0 0 Cost, limited benefit Keep quiet 1 Benefit w/o cost -10 Everyone’s in the dark
- 16. How games are won Clarify dominant strategies Find equilibrium Pursue equilibrium or change the payoffs
- 17. Moves Current game-play - Controls are layered or chained until we're satisfied that for some set of attackers, the cost of the attack is higher than the utility associated with their payoff Reputation requirements for participation Role requirements for participation (access control) Incremental authentication Content/context based filtering Blacklisting / whitelisting Rate limiting Bot limiters (Captcha) Obfuscation/Encryption
- 18. Counter-moves For every move there is a counter-move
- 19. Putting the pieces on the board The amount of friction inserted into the system depends on: - Value of asset to the owner - Value of the asset to potential attackers - Number of attackers expected - Portion of attacks that must be averted - Disincentive value of each layer of friction for an attacker Now it’s time to play our game
- 20. Does this sound familiar?
- 21. Managing Decisions Game Theory is a framework for studying decisions - Since payoffs depends on the choices of other players, moves are risky - Players play based on their risk appetite - Risk management = decision management Defenders design control systems that make decisions - Where risks manifest in observable behavior - That make moves/counter-moves depending on the context and understanding of an actor’s identity or intent - Where system or individual costs/payoffs depend on the outcome of an actor’s actions
- 22. SHALL WE PLAY A GAME? (SINCE WE CAN’T PLAY “CLUE” FOR EVERY LOGIN TRANSACTION NEW USER MESSAGE FRIEND REQUEST ATTACHMENT PACKET WINK POKE CLICK WE BUILD RISK MODELS)
- 23. Applying Decisions Risk management is decision management ACTOR ATTEMPTS ACTION SUBMIT WHAT IS THE REQUEST HOW TO HONOR THE REQUEST SHOULD WE HONOR? RESULT ACTION OCCURS
- 24. Not all risk decisions have a competitive element, but all competition / games have risks
- 25. Create account using fake identity Script completion of verifications Outsource captcha Create accounts across virtual devices Distribute creation of accts using botnet Scrape identities from public sites Age accounts, then reactivate Use stolen credentials Defraud verification process ... Require email verification Test for human behind keyboard Rate limit by device ID Rate limit by IP/location Look for similarities across accounts Require reputation level to proceed Filter for content / context, add auth challenge Require manual verification Manual review of account/event ...
- 26. Except one small thing... ...what kind of game is this?
- 27. Multi-player Mode Offense Attempt Success Defense Deflect 4, 4 0, 10 Ignore 10, 0 1, 1 Offense Attempt Success Defense Deflect 4, 4 0, 10 Ignore 10, 0 1, 1 Offense Attempt Success Defense Deflect 4, 4 0, 10 Ignore 10, 0 1, 1 Offense Attempt Success Defense Deflect 4, 4 0, 10 Ignore 10, 0 1, 1 Attackers are not the only players in the game Legitimate users that are also affected by added friction
- 28. Team Dynamics So this adds another factor into the appropriate level of friction question, which is: - Disincentive value of each layer of friction for an innocent - Likelihood the disincentive will be incorrectly applied to an innocent - Likelihood the disincentive value > payoff value for the innocent (go find a new game)
- 29. Decisions, Decisions Authorize Block Good false positive Bad false negative RESPONSE POPULATION Incorrect decisions have a cost Correct decisions are free (usually) Good Action Gets Blocked Bad Action Gets Through Downstream Impacts
- 30. GAME OVER 1-UP?
- 31. Why are we still playing? Economic/mathematical models depend on rational participants Free will doesn’t imply rationality Economics studies what should happen, behavioral economics studies what does happen
- 32. Example of rational irrationality Ultimatum Game - Player A given $1000 Player A needs to split the $ with Player B Player A gets to choose the split - Player B receives offer If B accepts, both get $ If B rejects, both get 0
- 33. Take it or leave it Outcomes - Player A’s usually offer ~50% - Player B’s often reject if offered <30% - This behavior occurs across cultures, levels of wealth Emotions matter - Heightened brain activity in Bilateral antierior insula (disgust) w/low offers Dorsolateral prefrontal cortext (cognitive decision making) w/high offers - Fairness, Fear, Punishing the mean
- 34. Therefore: Winning strategies depend on understanding behavior Both attackers and defenders may exhibit bias when making decisions - about the game and other players Retrofit conceptual models to actual experiences Fill in the blanks on player costs/payoffs Risk controls still either need to - Change friction (cost), or - Change expected value of pay-off Continue to analyze game dynamics over time - Low-risk, high frequency interactions (data) - High-risk, low frequency interactions (negotiation)
- 35. Prediction is very difficult, especially about the future Niels Bohr Allison Miller @selenakyle
- 36. Some references Axelrod, Robert. The Evolution of Cooperation. Dixit, Avinash and Nalebuff, Barry. The Art of Strategy: A Game Theorist’s Guide to Success in Business and in Life. Fisher, Len. Rock, Paper, Scissors: Game Theory in Everyday Life. Gibbons, Robert. Game Theory for Applied Economists. Meadows, Donella. Thinking in Systems: A Primer. Wikipedia’s sections on Game Theory, Economics, & Probability.