Voter, What Message Will Motivate You to Verify Your Vote? Maina - - PowerPoint PPT Presentation

voter what message will motivate you to verify your vote
SMART_READER_LITE
LIVE PREVIEW

Voter, What Message Will Motivate You to Verify Your Vote? Maina - - PowerPoint PPT Presentation

Voter, What Message Will Motivate You to Verify Your Vote? Maina Olembo, Karen Renaud, Steffen Bartsch, Usable Security Lab Crypto Lab and Melanie Volkamer Maina Olembo | USEC 14| 23.02.14 Background in electronic voting x o Yes No Yes o


slide-1
SLIDE 1

Usable Security Lab Crypto Lab

Voter, What Message Will Motivate You to Verify Your Vote?

Maina Olembo | USEC ‘14| 23.02.14

Maina Olembo, Karen Renaud, Steffen Bartsch, and Melanie Volkamer

slide-2
SLIDE 2

Background in electronic voting

2 Maina Olembo | USEC ‘14| 23.02.14

Yes

  • Yes
  • Not

x

No Yes No Yes No Possibility to verify Possibility to verify Possibility to verify Voter Observers

slide-3
SLIDE 3

§ Integrity violation can only be noticed if voter verifies § But voters are not very likely to verify

§ As user studies have shown § Due to high trust in processes and people

Level of security

3 Maina Olembo | USEC ‘14| 23.02.14

slide-4
SLIDE 4

§ Increase voter’s general intention to verify

Goal

4 Maina Olembo | USEC ‘14| 23.02.14

slide-5
SLIDE 5

§ To what extent can a tailored message increase intention to verify? § Will such a message have any effect on pre- existing intention to vote online?

Research questions

5 Maina Olembo | USEC ‘14| 23.02.14

slide-6
SLIDE 6

§ Reviewed literature on behaviour-change in information security § Identified 28 theories and models § Classified into 5 groups

Developing the messages

6

Risk Provide information about risks & how to cope Norms Inform people about the behaviours of others Analogies Personal experience is linked to new idea Rewards/Penalties Reward desired / penalize undesired behaviour Training Training programs/ security messages

Maina Olembo | USEC ‘14| 23.02.14

slide-7
SLIDE 7

The individual messages

7 Maina Olembo | USEC ‘14| 23.02.14

Studies by the Federal Office for Information Security show that most PCs

  • r laptops with Internet access are infected with malicious software, e.g.
  • viruses. This malicious software could change your vote before encrypting

and sending it to the election server, and you would not notice it. You can use the Election Verifying App to check if there is any malicious software on your PC or laptop that has changed your vote. Voters who want to protect democracy check if the voting system has correctly encrypted the selected candidates. You have previously voted in several elections. Whenever you participated in an election, you voted on a ballot paper that was counted manually. You could be sure that your ballot paper was correct because you were the one who put a cross next to your candidate’s name, folded the ballot paper and placed it in the ballot box. In Internet voting, you put a cross next to your candidate’s name by clicking on the candidate. Your vote is then encrypted

  • n your PC or laptop and is sent to the election server. The Election

Verifying App enables you to ensure that your vote was not modified before encryption.

§ Risk § Norm § Analogy

slide-8
SLIDE 8

Testing the messages

8

§ Survey – focus on intention

§ Only potential Internet voters § Four groups § First one of the messages (or none – control) § Then instructions how to verify

§ Data from 123 participants

§ 54 (43.9%) male; 69 (56.1%) female § Average age – 30 § Most had university level education § Most had high computer proficiency

Maina Olembo | USEC ‘14| 23.02.14

slide-9
SLIDE 9

Intention to verify (all messages)

9 Maina Olembo | USEC ‘14| 23.02.14

26.7% 13% 10% 9.7% 63.3% 77.4%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Control Messages

Disagree Neutral Agree

Mann-Whitney U test (p<0.05; r = 0.45)

slide-10
SLIDE 10

Intention to verify (ind. messages)

10 Maina Olembo | USEC ‘14| 23.02.14

9.7% 16.7% 12.5% 9.7% 13.3% 6.3% 80.7% 70% 81.3%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%

Analogy Norm Risk

Disagree Neutral Agree

Kruskall-Wallis test (p>0.05)

slide-11
SLIDE 11

Intention to vote online (ind. messages)

11

Risk (N = 32) % Norm (N = 30) % Analogy (N = 31) % Control (N = 30) % No 9.4 6.7 16.1 16.7 I don’t know 6.3 26.7 3.23 16.7

Maina Olembo | USEC ‘14| 23.02.14

Chi square test (p>0.05)

15.7% 33.4% 33.4% 19.3% Total

slide-12
SLIDE 12

§ Sample not representative for population § Only insight on intention not actual behavior

Study limitations

12 Maina Olembo | USEC ‘14| 23.02.14

slide-13
SLIDE 13

§ Tested three messages (Risk, Norm, Analogy)

§ Messages in general increase intention to verify § No one message is more effective than the others § Some effect on intention to vote online

§ Future

§ More insights from interviews § Test actual behaviour

Conclusion and future work

13 Maina Olembo | USEC ‘14| 23.02.14