Weight, Weight, Dont Tell Me: Using Scales to Select Ballots for - - PowerPoint PPT Presentation

weight weight don t tell me using scales to select
SMART_READER_LITE
LIVE PREVIEW

Weight, Weight, Dont Tell Me: Using Scales to Select Ballots for - - PowerPoint PPT Presentation

Weight, Weight, Dont Tell Me: Using Scales to Select Ballots for Audi<ng Cynthia Sturton, Eric Rescorla, David Wagner 1 Elec<on Audits are Important Source: Joe Hall 2 Audi<ng Methods Precinctbased: Standard prac<ce


slide-1
SLIDE 1

Weight, Weight, Don’t Tell Me: Using Scales to Select Ballots for Audi<ng

Cynthia Sturton, Eric Rescorla, David Wagner

1

slide-2
SLIDE 2

Elec<on Audits are Important

2

Source: Joe Hall

slide-3
SLIDE 3

Audi<ng Methods

  • Precinct‐based:

– Standard prac<ce – Choose a sample of precincts to audit – Every ballot in a sampled precinct is audited

  • Ballot‐based1,2,3:

– Newer idea – Choose a sample of ballots to audit – Sample from the set of all ballots, across precincts

  • 1. Neff, C. A., Dec. 2003.
  • 2. Johnson, K. C., Oct. 2004.
  • 3. Calandrino, J. A., Halderman, J. A., and Felten, E. W., EVT 2007.

3

slide-4
SLIDE 4

Ballot‐based vs. Precinct‐based

  • Ballot‐based audi<ng is more efficient

– Confidence based on number of audit units rather than number of ballots

  • E.g., Virginia 2006 elec<on results1

– Ballot‐based audi<ng would have required the recount of between 1/17 to 1/400 as many ballots as precinct‐based audi<ng did.

  • Our focus is on ballot‐based audi<ng

4

  • 1. Calandrino, J. A., Halderman, J. A., and Felten, E. W., EVT 2007.
slide-5
SLIDE 5

Audit Sampled Ballots Verify Tabula<on

How ballot‐based audi<ng works

Returned Ballots Scanner Cast Vote Records (CVR) Elec<on Management So`ware Scanned Ballots Observer Tallies

slide-6
SLIDE 6

A Challenge for Ballot‐based Audi<ng:

Finding the sampled ballot

  • Key steps of ballot‐based audi<ng:
  • 1. Picking cast vote record
  • 2. Finding paper ballot
  • 3. Compare paper ballot to cast vote record
  • Requires a way to link each cast vote record to

its paper ballot

  • Different proposals do this in different ways

6

slide-7
SLIDE 7

Finding the Sampled Ballot Approach #1:

  • Approach:

– Pre‐printed serial number

  • Advantages:

– Conceptually simple

  • Disadvantages:

– Violates privacy – Scanners require modifica<on ‐ so`ware – Finding par<cular ballot may be slow

7

slide-8
SLIDE 8

Finding the Sampled Ballot Approach #2:

  • Approach:

– Serial number stamped on a`er elec<on

  • Advantages:

– Protects privacy – More efficient ballot selec<on

  • Disadvantages:

– Scanners require modifica<on – so`ware & hardware – Modifies already‐voted ballots

8

slide-9
SLIDE 9

Our Contribu<on

  • Explicit serial number not necessary
  • Loca<on in stack + Stack number =

Implicit serial number

9

slide-10
SLIDE 10

Finding the Sampled Ballot Approach #3:

  • Approach:

– Hand count to find implicit serial numbers

  • Advantages:

– Protects privacy – No scanner modifica<on required – Voted ballots are not modified

  • Disadvantages:

– Finding par<cular ballot may be slow – Possibility for human error

10

slide-11
SLIDE 11

Finding the Sampled Ballot Approach #4:

  • Approach:

– Use ballot weight to find implicit serial numbers

  • Advantages:

– Protects privacy – No scanner modifica<on required – Voted ballots are not modified – Faster than hand coun<ng

  • Disadvantages:

– Possibility for selec<on error

11

slide-12
SLIDE 12

5 6 7 8 9 10 11 12 4 3 2 1

Ballot Stack Flipping Index into the stack by finding the sub‐stack with the correct number of ballots. Scale

12

slide-13
SLIDE 13

A coun<ng scale efficiently counts the number of ballots in a stack

13

slide-14
SLIDE 14

Selec<on Experiment

  • Methodology

– 50kg x 0.002kg coun<ng scale – 350 Ballots – calibra<on and selec<on

  • Results

– 20 Trials – Longest <me, 31 seconds (early trial) – All trials resulted in correct ballot selec<on

14

slide-15
SLIDE 15

Sources of Selec<on Error

  • Scale error
  • Varia<on in ballot weights
  • Mis‐es<ma<ng mean ballot weight

15

slide-16
SLIDE 16

Projected Selec<on Error

  • Calculate es<mated mean ballot weight

– 1000 ballots sampled with replacement

  • Generate stacks of 500 ballots
  • For each posi<on i in the stack, would we

correctly es<mate stack size?

  • 100,000 trials

16

slide-17
SLIDE 17

Simulated Error Rate Resul<ng from Varia<on in Ballot Mass

17

slide-18
SLIDE 18

Limita<ons of this Research

  • Unknown:

– Varia<on in weight of voted ballots – Homogeneity of ballot weight distribu<on across different boxes of ballots – Prac<cality of keeping ballot stack order – End‐to‐end efficiency of scheme

18

slide-19
SLIDE 19

Conclusion

  • We present a new scheme to enable ballot‐

based audi<ng

  • Advantages over prior schemes

– Compa<ble with legacy hardware – No modifica<on of voted ballots

  • A promising idea, more research warranted

19

slide-20
SLIDE 20

End

20

slide-21
SLIDE 21

Varia<on in Ballot Weight

21

Weight (grams) Box A Weight (grams) Box B Number of Ballots Number of Ballots

slide-22
SLIDE 22

Ballot Weight Varia<on Accumulates

22

Total Weight Total Weight Probability Probability