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Young People’s Security Behavior Intentions regarding Cloud Service UseA measurement and comparison of Korean and Dutch students’ security intentions

Prof. Jang Hyun Kim*Sungkyunkwan University

Associate professor

alohakim@skku.edu

P.I.M. KamphuisSungkyunkwan University

Master student

p.i.m@skku.edu

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From USB to Personal Cloud Services

From portable storage To cloud storage For use on Cloud

Access Devices (CAD)

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A threat to security?

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RQ1 : What is students’ intention on securing their cloud access devices?

Security Behavior Intention Scale[1]

1 Egelman, Serge, and Eyal Peer. "Scaling the security wall: Developing a security behavior intentions scale (sebis)."

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2015.

SeBIS:

DeviceSecurement

Password Generation

Proactive Awareness

SoftwareUpdating

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RQ2 : What factors influence students’ intention on securing their CADs

Theory of Planned Behavior [2]

2 Ajzen, Icek (1991). "The theory of planned behavior". Organizational Behavior and Human Decision Processes. 50 (2): 179–211.

Attitude

Subjective Norm

Perceived Behavior

Control

Intention Behavior

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RQ2 : What factors influence students’ intention on securing their CADs

Proposed model

Attitude

Subjective Norm

Perceived Behavior

Control

Intention

(SeBIS)

H2.1

H2.2

H2.3

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Cultural differences between Netherlands and South Korea

0

20

40

60

80

100

120

Power Distance Individualism Masculinity Uncertainty Avoidance Long Term Orientation Indulgence

Netherlands in comparison to South Korea trough the lens of the 6D-model [3]

Netherlands Korea

3 Hofstede, G. (n.d.). Netherlands - South Korea. Retrieved January 13, 2017, from https://geert-hofstede.com/netherlands.html

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RQ3 : Is there a significant difference between Korean and Dutch students?

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Method

• Survey containing SeBIS and TPB questionnaires

• Pilot survey in June 2016 (N = 58)

• Google forms on-line survey in October 2016 (N = 226)

• Recruitment via University’s student portal

• SPSS Data analysis

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Results: Demographics (N = 226)

53%47%

Country

Korea

Netherlands

8%

75%

17%

Age

15 - 20

21 - 26

26 +

43%

57%

Gender

Male

Female

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Results: RQ1 - Students Intention

2.7

3.7

3.1

2.9

Device security

Password generation

Proactive awareness

Software updating

3.1

SeBIS Score

out of 5.0

Ds Pg Pa Su SeBIS

N 226 226 226 226 226

Mean 3.7058 2.6903 2.9502 3.1121 3.1146

Sum 837.50 608.00 666.75 703.33 703.90

Std.

Deviation

.96766 .77980 .79268 .88567 .42287

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Results: RQ2 – Influential TPB factors

Unstandardized

Coefficients

Standardized

Coefficients

B Std. Error Beta t Sig.

(Constant) 1.833 .169 10.880 .000

Attitude .185 .034 .318 5.382 .000

Subjective Norm .234 .035 .391 6.710 .000

Perceived

behavior control

-.035 .038 -.055 -.938 .349

> H1. Students attitude influences intention on securing CADs

> H2. Students subjective norms influence intention on securing CADs

> H3. Students perceived behavior control influence intention onsecuring CADs

Regression analysis results

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Attitude

Subjective

Norm

Perceived

Behavior

Control

Device

security

Password

generation

Proactive

Awareness

Software

Updating

Attitude

Subjective Norm .326**

Perc. Behavior Control .212** -.139*

Device Security .326** .333** -.015

Password Generation .275** .038 .346** .037

Proactive Awareness -.191* .131* -.492** -.001 -.218**

Software Updating .321** .381** .073 .151* .061 -.160*

Correlations Coefficients

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

Results: RQ2 – Influential TPB factors

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Results: RQ3 – Significant differences

0

10

20

30

40

Device Security** Password generation Proactive Awareness Software updating

Differences in means between Dutch and Korean students

Netherlands Korea

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0

10

20

30

40

Attitude Subjective Norm Perceived Behavior Control SeBIS

Differences in means between Dutch and Korean students

Netherlands Korea

Results: RQ3 – Significant differences

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Results: Conclusion and Discussion

• Dutch and Korean students score average on SeBIS

• High score on securing their Cloud Access Devices

• Average score on Software Updating and Proactive Awareness

• Low score on Password Generation

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• Relationships between SeBIS and TPB constructs are found

• High correlation between Perceived Behavior Control and

Password Generation and Proactive Awareness

• PBC requires attention in order to increase security intentions

Results: Conclusion and Discussion

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Results: Conclusion and Discussion

• Cultural differences (6D) seem to have no effect on

students’ security intention

• No significant differences between the two groups

• To improve Proactive Awareness and Password Generation

Perceived Behavior Control should be addressed

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Mahalo