Economics of Cybersecurity Prospect Theory Sophie Van Der Zee The - - PowerPoint PPT Presentation

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Economics of Cybersecurity Prospect Theory Sophie Van Der Zee The - - PowerPoint PPT Presentation

Economics of Cybersecurity Prospect Theory Sophie Van Der Zee The Computer Lab, University of Cambridge Decision-making People constantly make decisions involving different levels of risk and uncertainty Psychologists and


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Sophie Van Der Zee

The Computer Lab, University of Cambridge

Economics of Cybersecurity

Prospect Theory

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  • People constantly make

decisions involving different levels of risk and uncertainty

  • Psychologists and economists

have tried to capture human decision-making under risk in theoretical models to explain and predict people’s behavior

Decision-making

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  • Daniel Bernoulli, 1738
  • Dominant theory until the mid

20th century

  • Three important concepts:
  • Utility (psychological value)
  • Wealth (current state)
  • Rational choice model

Expected utility theory (1)

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Utility

  • Utility does not increase

proportionately with the amount of money

  • Example:
  • The first pound extra is worth

more than the 10th or the 100th

  • A gamble should be assessed by

its expected utility, not by expected absolute value

Expected utility theory (2)

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Wealth

  • Utility is dependent on the

current state of wealth

  • Example:
  • £10 is worth more to someone

who only has £10 than to someone who has £100, a £1000

  • r £100,000
  • Wealth is included when

calculating the best option

Expected utility theory (3)

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Model of rational choice

  • The utility of potential outcomes

is weighted by the probability of its occurrence

  • Example:
  • 60% chance of + £10 = £ 6
  • 50% chance of + £10 = £ 5
  • People are expected to choose

the best option

Expected utility theory (4)

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Model of rational choice

  • The utility of potential outcomes

is weighted by the probability of its occurrence

  • Example:
  • 60% chance of + £10 = £ 6
  • 50% chance of + £10 = £ 5
  • People are expected to choose

the best option

Expected utility theory (4)

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  • Although we could make

decisions based on rational cost- benefit analyses, we often don’t for two reasons:

  • 1. People have an irrational

tendency to be less willing to gamble with profits than with losses  prospect theory

  • 2. We use mental shortcuts

instead of calculating all possible options  heuristics

Issues with expected utility theory

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  • Kahneman & Tversky (1979)
  • People do not always make

rational decisions because they value gains and losses differently

  • Centred around loss aversion
  • “A bird in the hand is worth two

in the bush”

Prospect theory (1)

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Prospect theory (2)

We experience stronger emotions during loss than during gain  Loss aversion

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Prospect theory (3)

People are risk-seeking when faced with potential loss, while they are risk averse and prefer certainty for gains

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  • There are 2 programs to battle a

disease

  • In program A, 200 people will be

saved

  • In program B, there is a 1/3

probability that 600 people will be saved, and a 2/3 probability that no one will be saved

Example (1) – “Asian Flu”

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  • There are 2 programs to battle a

disease

  • In program A, 200 people will be

saved

  • In program B, there is a 1/3

probability that 600 people will be saved, and a 2/3 probability that no one will be saved Absolute outcome is the same

Example (1) – Expected utility theory

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  • There are 2 programs to battle a

disease

  • In program A, 200 people will be

saved

  • In program B, there is a 1/3

probability that 600 people will be saved, and a 2/3 probability that no one will be saved  Risk averse in gain scenario

Example (1) – Prospect theory

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  • There are 2 programs to battle a

disease

  • In program C, 400 people will die
  • In program D, there is a 1/3

probability that no one will die, and a 2/3 probability that 600 people will die

Example (2)

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  • There are 2 programs to battle a

disease

  • In program C, 400 people will die
  • In program D, there is a 1/3

probability that no one will die, and a 2/3 probability that 600 people will die

Absolute outcome is the same!

Example (2) – Expected utility theory

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  • There are 2 programs to battle a

disease

  • In program C, 400 people will die
  • In program D, there is a 1/3

probability that no one will die, and a 2/3 probability that 600 people will die  Risk seeking when facing potential loss

Example (2) – Prospect theory

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  • People do not always make a

rational choice of the best

  • ption
  • Experiments show that people

deviate from rationality in a consistent, predictable manner

  • One reason is that they value

gains and losses differently

  • “It ain’t what you say, but the

way that you say it”

Prospect theory (4)

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Thank you for your attention!

Please post any questions you may have on

  • ur discussion forum.