The Effects of

1
The Effects of
Switching and Information Costs
on Competition for
Spam Reduction and Email Services

• Benjamin Chiao Jeffrey MacKie-Mason
• 10/17/05

2
incur c
pass thru
pay p
make type 1 2 errors
pass thru
make type 1 2 errors
3
Prior Literature
Challenge-Response (Dwork and Naor, 1993)
incur c
Legal punishment for spammers (Bazeley, 2003)
pass thru
pay p
Content filter, white and black lists, (Cranor
and LaMacchia, 1998)
make type 1 2 errors
Email stamps (Kraut et al, 2003)
pass thru
make type 1 2 errors
Attention-Bond Mechanism (Loder, Van Alstyne and
Wash, 2005)
4
Central Ideas

• To use incentive-based strategies, embedded in
  existing markets, to discourage spam sending, and
  encourage better email services
• Our strategies are to decrease the costs of
  switching to and the information costs of finding
  the best email service providers (e.g. strongest
  spam filters)

5
Already Happening

• Gmail
• Identity-switching
• Double forwarding

6
Double Forwarding
7
Identity Switching
8
(No Transcript)
9
Identity Switching Relies on Spoofing?

• Senders original identity can still be traced in
  the X-headers
• usually not displayed in the simple header view
  of most email clients
• any digital signature solutions that prevent this
  are not desirable! They might achieve the
  opposite effects of not reducing spam by killing
  our strategies

10
(No Transcript)
11
Model

• Notations
• J email service providers
• ?juniform0,1, filter strength
• ?j,, market share
• ns, number of spam sent
• E(nr), expected no. of spam received by users
• c(.), cost function of sending spam, c'gt0, and
  c''gt0
• p, price for each spam reaching users

12

• Profit function of a spammer

13

• Assumption 1 Spammers care only about the
  average filter strength.
• So

14

• Profit function becomes
• Zero-profit implies FOC

15
Interpretation

• Set p equals to the marginal cost of each spam
  times the expected no. of spam needed for the
  user to receive one spam.
• Since ?juniform0,1 implies E(?)0.5

16
What if ? is non-stochastic?
17
Theorem 1

• The number of spam sent and received will be
  smaller when the costs of switching to and
  finding the smallest ? is zero.

18
Proof

• With no switching and information costs
• Stochastic ?
• where ?(1) is the smallest order statistics
• Non-stochastic ?,

19
Proof
20
Other Conjectures (Skipped)

• Multiplier Effect
• Email Services Improvement

21
To-Do

• Calibration. To use real data of
• - number of email users and accounts
• - ? and ?
• to simulate the number of spam reduced

22
Weaknesses

• The drop of ns , nr are continuous but users
  may care about discrete thresholds
• But if we also model the fix costs of spammers,
  ns , nr are not continuous
• Spammers are interested to send different
  quantities of spam to different filters. Should
  we disclose ? then?

23
Implementation (More Papers?)

• A reputation system to display ?
• We may or may not rely on other sources to
  estimate ?
• It can even be real time so robots can help users
  to switch to the strongest filter real time
• To make the double forwarding and identity switch
  common knowledge
• To propose to big email service providers
• To work with standard organizations to minimize
  potential conflicts of W3C RFC email headers
  etiquette, Yahoos Domain Key, PID, Microsofts
  Sender ID, other authentication system

24
Extensions

• Spam response rates
• Users care about type 1 and 2 errors
• Users switch only discretely (because of discrete
  switch cost) when ? decreases.