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All content in this area was uploaded by Jo-Pei Tan on Aug 01, 2016
Content may be subject to copyright.
Young People and Smart Phones: An Empirical Study on Information
Security
Balbir S. Barn
Middlesex University
b.barn@mdx.ac.uk
Ravinder Barn
Royal Holloway, University of
London
r.barn@rhul.ac.uk
Jo-Pei Tan
Universiti Putra Malaysia
jopei@putra.upm.edu.my
Abstract
This paper reports on a study of mobile phone
usage by young people in the UK tertiary education
sector. Responses from 397 respondents were
analysed to explore the attitudes of young people
towards data security issues for mobile devices.
Results from the comparative analysis found that
there were significant differences in data security risk
concerns across ethnic groups. Those who reported
extrovert personalities tend to take more risk in data
security issues. In addition, young people who were
’technology savvy’ were less likely to expose
themselves to risk to data security issues through the
use of free wifi and access of installed applications.
The research reported here is part of a wider study
looking at the overall communications and mobile
phone usage of young people and taken as a whole,
the paper contributes to this increasingly important
area of Information Technology.
1. Introduction
In the last decade, there has been a rise in mobile
phone ownership in the United Kingdom, particularly
among young people. In the year 2000, it was found
that 17% primary school children and 58% of
secondary school children have their own mobile
phones (Office of National Statistics, 2002). More
recently the OFCOM Communications Market
Report for 2012 reported 66% of those aged 16-24
possessed a smart phone. The same group also
reported that they are most likely to choose the
mobile phone as the medium they would miss most
(40%).
The value of mobile phones can partly be
explained by how mobile phone based
communication has become embedded in youth
culture bringing out new spaces for social interaction
among young people [1, 2]. Accompanying these
changes, mobile phones have also begun the process
of modifying behaviour towards risk taking, and in
particular the risks associated with a possible lack of
understanding towards data security implications
associated with mobile phones.
This paper reports on a research study that
examined young peoples’ adoption of mobile
technology, particularly smart phones (those with
internet access), to support their communication
needs. The research focuses on the use of mobile
technology in the everyday lives of young people
studying at Universities in the United Kingdom.
While the research had a range of research questions
reflecting the broadness of the original brief, this
paper reports on the following:
To determine linkages between mobile
communications, risk-taking and at-risk
behavior among young people.
In this paper, risk-taking is broadly interpreted as
risk taking concerned with information security. For
the purposes of this paper we define information (and
data) security as: “The safeguarding of an individual's
data from unauthorised access or modification to
ensure its availability, confidentiality and integrity”
(http://ishandbook.bsewall.com/risk/Methodology/IS.
html ). We deliberately narrow this definition of risk
to focus on information security. The wider use of
risk referred to range of risk taking behavior such as
the sending of offensive texts, driving whilst texting
which are not relevant to this paper. Thus the paper
will present findings on the attitudes of young people
towards issues of information security related to their
communications based activities on mobile devices.
Research reporting on mobile phone usage
amongst young people is now widely available.
There have been studies conducted in Australia
exploring models of technology adoption [3], East
Asia [4] and the USA for example [5]. The latter is an
example that specifically explored issues around data
/ information security.
Research that explores behaviour of young people
in their use of mobile technology continues to
increase in importance. Thus this study contributes
current data on the use of the mobile phones in the
context of Internet related activity and presents
findings that note significant differences towards
information security between different demographic
groups. These distinctions have potential marketing,
technical and policy implications to those involved in
2014 47th Hawaii International Conference on System Science
978-1-4799-2504-9/14 $31.00 © 2014 IEEE
DOI 10.1109/HICSS.2014.554
4504
the eco-systems around mobile technology.
The remainder of the paper is organised as
follows. Section 2 briefly reviews previous work that
has explored how young people utilise mobile
technology. In particular, the issue of data or
information security is considered within the context
of established theoretical models such as the
Technology Acceptance Model [6] [7]. Section 3
develops the research methods utilised to explore the
question above. Section 4 presents both our
descriptive statistics and an analysis using
correlations for understanding the relationship of
young people, their behaviours and awareness
towards data security. The paper is concluded with
final remarks.
2. Related Work
The young people surveyed in this research
represent the so-called 'digital natives' [8], that
generation of young people born after 1980 and
possessing sophisticated knowledge of information
technology having grown up surrounded by
electronic gadgets and the Internet. Importantly,
despite the wide availability of a preponderance of
electronic devices, the smart mobile phone providing
access to a range of services (voice, text, email, social
networks, rich media) and ubiquity of network
connectivity means that it has become the device of
choice for young people [5].
The wider literature into the relationship between
technology and society has consistently highlighted
the rapid embedding of mobile phones
communication into youth cultures and its effects on
altering the social and geographical aspects of their
everyday life. Specifically, mobile phone
communications have opened up new spaces for
social interaction among the youth: talk to friends,
arrange to meet and for parents and young people to
stay in touch [1, 2]. The availability of mobile
communications has also expanded young people’s
private spheres and, allowed them to have more
control over their own communication channels and
geographies [9] [10, 11]. Thus, this type of
communication has created a ‘private setting’ for
young people and serve as means for integration in
their peer group.
Mobile phones, due to their physical
characteristics, are more vulnerable to threats of
accidental loss or theft. And while the device itself
may represent the target, the increasing use of the
phone for a range of activities leading to increasing
amounts of personal information stored in the phone
suggests that data/information security will become
increasingly important. In 2005, a study of 297
mobile phone users [12] found that a third did not
use PIN technology, however 83% were willing to
accept some form of biometric authentication. PIN
based security was again the subject of further study
by Kurkovsky and Syta and reported similar results
[5]. However as our results will show, in 2013 young
peoples' awareness to the importance of PINs has
increased.
The phenomena of social network sites (SNS)
dominated the year of 2007 [13] and show no signs
of losing impetus as SNSs have moved to mobile
devices. Their relationship to data security in general
is significant as a typical Facebook user profile
frequently includes large amounts of personal and
sensitive personal data as defined by the European
Data Protection Directive (DPD). When this is
coupled with the inherent vulnerability of mobile
phones the security of personal and sensitive data and
associated risk is further exacerbated.
The rate at which advances in mobile technology
are being made requires that a young person’s
willingness in risking an adoption of new technology
may depend upon their disposition to engaging with
innovation and their general technology savviness.
Although psychological and personality metrics
exist for measurement of domain-specific individual
innovativeness in the adoption of IT in general such
as that by Agarwal [14], as our research was broader
than the topic addressed in this paper, we utilised the
widely deployed personality Eysenck scale as a
potential predictor for risk taking activities in relation
to information security [15].
Previous research suggests that personality of an
individual will predict types of mobile phone use (see
[16] . For example, extraversion is associated with
traits such as assertiveness, activity-oriented,
excitement-seeking and positive emotions [17] .Thus,
personality of individuals should also predict the
types of interactions and activities in which people
are prepared to engage using mobile phone
technology. Also, problematic mobile phone users or
addictive users are more likely to be extraverted [16].
As extroverts are more likely to take risks, they have
a higher likelihood to engage in risk-taking behaviour
that could compromise the security of data stored on
a mobile device or expose sensitive data/information
to misuses. While psychological theory, in particular
personality traits, can explain patterns of and
behavior in mobile phone use [18], there is
comparatively little information available on the
relationship between personality traits and perception
of data security/information privacy among mobile
phone users. Therefore, the present study makes an
important contribution in addressing the
4505
psychological predispositions that might underpin
mobile phone use.
Huang et al [19] reported on a study to investigate
people's perception of information security with the
aim to unveil the factors that influence peoples'
perception of different threats to information security.
Given that perception is a critical cognitive function
by which individuals assess external input in order to
generate a behavioural response, the work by Huang
et al is significant. Following a survey of 602
respondents and an exploratory factor analysis, a six-
factor structure characterising people’s perception of
different threats to information security was
developed. This model contains factors of knowledge
(K), impact (I), severity (S), controllability (C),
awareness (A) and possibility (P). The study did not
however, consider people-related features such as
cultural style, personality and risk sensitivity. For
young people and mobile phones such omissions may
be of relevance.
While research on mobile phone security exists
(see [20] and [21]) it has not explored the experiences
of young people in depth and in particular the
questions of security and how digital natives differ
has not been addressed. Some studies have compared
perceptions and the use of mobile phone across
cultures, age groups and gender. For example,
Campbell [22] (2007) in his survey of 231 students
from diverse cultural groups (i.e. US, Hawaii, Japan,
Taiwan and Sweden) found that various types of
cultural characteristics among these students are
associated with the mobile communication practices
and perception towards mobile technology, ranging
from psychological or relational tendencies to socio-
economic and political conditions.
Younger/adolescent users perceived mobile phone
technology as a tool for expressive purposes or
fashion statement [23] [24]; while older/adult users
associate it with instrumental purposes and
safety/security [25]. For gender comparison, males
emphasised the technical functions of mobile phones,
while females appreciate social and physical
appearance aspects, such as casing, design and ring
tone [9].
Recent research work suggest that although
technology is embedded in young people’s lives,
their use and degree of fluency in technology are not
uniform, particularly in aspects above and beyond
computer games and emails that require a deeper
understanding of the technology and its possible
impacts [26]. Kennedy and colleagues’ (2007) survey
on young people usage of Web 2.0 tools revealed that
only a relatively small proportion of students are
capable of utilising the newer technologies such as
blogs, wikis and social bookmarking which enable
students to collaborate and to produce and publish
material online [27]. Others indicated that college
students have very basic technological skills and do
not resognise the enhanced functionality of the
applications they own and use [28]. This lack of
knowledge on information technology may have
pertinent implications on young people’s attitudes
towards vulnerability of mobile phone data security.
The most widely used methods of authentitication
on moble phones are PINs and passwords. While,
study on IT professionals provides evidence on the
relationship between general awareness or concern of
data security and security measures/actions that
individuals take to protect their mobile phones and
sensitive data stored on them (see [29]), other studies
on young people indicate that many mobile users are
either unaware or do not use the security features
available on their mobile phones (i.e. did not use any
PIN or password security) [5] [12]. Kurkosky and
Syta (2010) have argued that the lack of knowledge is
not the reason why young people choose to leave
their mobile device unprotected. They asserted that
majority of the young people in their survey are
aware of phone-level (80%) and SIM-level PINs
(67%) but less than a third use PINs to lock phones
and Sim cards.
Mobile phones/devices have a particular set of
risks and vulnerabilities associated with them,
especially risk factors related to youth populations.
The mainstream media has highlighted the concern
about young people being targeted by bullies and
pedophiles through mobile phones and other media
technologies [30] [31]. For example, Valentine and
Holloway who explored young people’s use of
cyberspace noted parental concerns about young
people’s vulnerability, and their high level of
technological competence, which exposed them to
pornography and pedophiles while using the internet
[32] .
To understand perceptions of young people
towards issues of data security on their mobile
phones, theoretical models from IS/IT research
literature were also contemplated. Key theories such
as the Technology Acceptance Model (TAM) [6] and
The Diffusion of Innovation Theory [33] were
considered but discounted as they did not appear to
satisfactorily address the perceived dichotomy
between convenience and security (that is, the
likelihood that users behave less securely in the
presence of free services). Issues of rapid
development and diffusion of smart-phones and
mobile technologies in general also prevents adoption
of these theoretical models.
4506
In the context of this paper, the existing literature
presents limited evidence on correlational factors
leading to awareness of data security amongst this
target group 18-25 year old young people especially
since the large-scale adoption of smart phones. Thus
the primary contribution of this paper is to present
findings on factors that influence behaviour that has
impact on information security for users of mobile
smart phones and how such factors are correlated.
This study hypothesized the following: (a) Young
people’s perception of risks of data security would be
associated to their socio-demographic characteristics;
(b) Young people’s personality would be
significantly related to their perception on mobile
phone security; (c) Young people IT/information
literacy and data privacy/security measures would be
associated to their perception on mobile phone data
security. The findings have potential for policy and
design implications for mobile phone manufacturers.
3. Research Method
This research was conducted at four tertiary
(higher education) institutions in the UK with the
population from which the sample was obtained
studying a range of courses such as computer science,
sociology, psychology, criminology and business
studies at both undergraduate and postgraduate
levels.
An on-line approach to survey design was chosen
because of the clear advantages offered: storage of
data, flexibility and accuracy; targeting different
segments and the lower cost.
Students were recruited through university
courses, primarily through a web link sent via email.
The survey was a standardised instrument and
developed to elicit demographic details from the
young people (i.e. personal, social and family
background characteristics). Participation was strictly
voluntary. Other standardised instruments and open-
ended questions were used to gather information on
the usage and experience of mobile technology as
well as the role of mobile communication in the
wider social world of young people. In addition to the
survey, focus group discussions with 40 students
were also held during the piloting of the on-line
questionnaire and at the end of the survey. Data were
collected over a period of November 2012 through to
end of January 2013.
The lead institution obtained ethics approval and
the questionnaire design was subject to validation and
pilot testing to ensure readability, consistency and
error correction. The focus groups served as
important consultations to cross check with the
student views and experiences that were captured by
our research instruments. The focus groups also
provided additional qualitative data on mobile phone
usage.
While the survey addressed a range of areas, those
related to the research question under evaluation in
this paper included:
1. Information Literacy
2. Data Security
3. Experience towards Mobile Phone Usage
4. Communication & Personality
5. Demographic Details.
As noted in the introduction earlier, this paper
reports on the linkages between mobile phone usage
and risk-taking behavior. In this paper, risk taking is
broadly conceptualised as risks associated with
concern and management of data/information
security. Drilling down, for this exploration of
attitudes towards data security, the following survey-
derived items were determined to be potential factors
that may influence young people towards data
security issues on mobile phones (see Table 5). The
factors are discussed in section 4. Note that each
predictor variable group reported a minimum of 0.71
on the Cronbach Reliability Scale.
The wider scope of the research was exploratory in
nature. The five areas listed above were deemed as
predictors of perceptions towards (information
security) risk taking behaviour. It would be of value
to replicate this study in other country contexts.
Sample questions are shown in Table 7 and the full
research instrument is available from the authors.
4. Results and analysis
This section presents the results and analysis
focusing on the exploration of attitudes and practices
of young adults towards data security on mobile
phones. We first introduce descriptive statistics that
outline the demographic data. The descriptive
analysis section explores responses to key questions
related to the factors influencing information
security. This is followed by relevant correlation
analysis performed on the data.
At the end of the survey, base line data included:
397 respondents who started the survey with 291
respondents completing all questions. The socio-
demographic profile of young people and family is
presented in Table 1. The sample was 47.4% (n=137)
male and 52.6% (n=152) female; and average age is
23 years old (SD=6.15) with the majority (89.3%,
n=258) between 16 to 30 years old during the time of
the study. In terms of age for first mobile phone, the
average age is 15 years old (SD=5.94). A majority
4507
(72.6%, n=226) of the respondents reported that they
first had a mobile phone at age 15 or below.
Table 1 Descriptive Data
Variable N Mean or %
Male 137 47.4
Female 152 52.6
Age (years) 289 23.12
White British 74 25.8
White Other 63 22.0
Mixed 22 7.7
Black/ African/ Caribbean/
Black British
41 14.3
Asian/ Asian British 78 27.2
Home/EU Student 219 75.8
Overseas Student 70 24.2
Living away from family
home
170 58.9
Living at home with family 119 41.2
The current sample comprised young people from
different ethnic backgrounds. Almost half (47.8%,
n=137) of the youth were White with 25.8% (n=74)
White British and 22% (n=63) other White ethnic
background, while the rest were of black and
minority ethnic background (52.2%, n=150). This
includes those of Black British/African/Caribbean
(14.3%, n=41), Asian/British Asian (27.2%, n=78)
mixed-parentage (7.7%, n=22) and other ethnic
groups such as Arabs (2.3%, n=9). The ethnic
categories used in this research are based on the
widely used categories in the UK census
(http://www.ons.gov.uk/ons/guide-
method/census/2011/uk-census/index.html). The
majority (75.8%, n=219) of young people were
Home/EU students while the rest were overseas
students (24.2%, n=70).
There were almost similar numbers of students
living away from family home (58.8%, n=170) and
those living at home with family during the time of
the study (41.2%, n=119). Table 1 provides some of
the relevant overview descriptive statistics from the
sample.
Mobile phones present inherent security risks
concerning issues of data and privacy. Some of the
background to the nature of associated risks has
already been noted in section 2 earlier. Further
descriptive statistics explored the general concerns of
young people towards aspects of data security. Here
we report on the responses to questions by our
respondents that provide some insight into how issues
of data and privacy security are of concern to our
demographic. Table 2 shows that almost half of our
sample were concerned about the security of data
stored in their mobile phone. Moreover, From the
table, it is clear that young people recognise that there
are risks associated with securing data on mobile
phones with almost 50% reporting some concern
about infiltration by viruses or worms; and a similar
proportion expressing concern about wireless attacks
using Bluetooth or wifi connection.
At odds with this are the relatively small numbers
who are concerned about the risks of using free wifi
in public spaces (only 33%).
Table 3 and 4 also illustrate young people's
perceptions on privacy and security measures in
relations to mobile phone technology. Items on
password security measures were derived from
Kurkovsky and Syta [5] to examine mobile phone
data security and privacy measures among young
people. Our data show that half of our sample report
that they do not allow applications to access their
contacts; whilst two-fifths do not allow applications
to access any information. Only 1 in 10 regularly
allow apps access to information and their contacts.
The ‘sometimes’ response suggests that young people
are rather discerning in which applications they allow
to access their personal information and contacts (See
Table 3). This finding is consistent with a recent
PEW report [34].
The majority of the young people had indicated
that their mobile-phone (71.7%, n=230) and sim-card
(39.8%, n=127) are password protected while almost
75% of the young people rarely/never change their
password on their mobile phone (See Table 4). About
one third (30.7%, n=98) tend to change their
password as a security measure on a regular basis
(frequently or occasionally).
Slightly more than half of the young people
(53.8%, n=172) reported that no other people are
aware of their password; while the rest indicated one
(22.5%, n=72), two to three (16.6%, n=53) and four
or more (7.2%, n=23) people are aware of their
mobile phone password.
4.1 Descriptive Analysis
Table 5 shows the descriptive statistics of the
measures for personality, IT/information literacy,
data security and risk taking behaviour. The Eysenck
Personality Questionnaire (Extraversion vs
Introversion) [15] was used in the present study. This
12-item measure assesses a young person’s
personality on an extraversion/introversion
continuum (i.e. outgoing, talkative, high on positive
affect (feeling good), and in need of external
stimulation). Higher scores on the Personality
Questionnaire reflect greater tendency towards
extraversion personality. Based on the group median,
4508
more than half (60.3%, n=179) of the young people
reported low levels of extraversion personality. while
the remaining 40% (n=118) tend to have high
tendency of extraversion personality.
Table 2 Concern about data security
In relation to IT literacy, information related to
overall information literacy, self-assessed technology
savviness and online activities were collected (see
Table 5). A 5-point Likert scale was developed to
measure the frequency of mobile usage on various
life aspects related to the youths: advanced
communication, entertainment, blogging, information
searching and other online activities ([35, 36]). Three
items were used to measure the knowledge and
literacy of information technology among youth in
relations to online journal or blogging, online sharing
or use material online for own artistic creation.
Higher composite score reflect higher level of
IT/information literacy. Based on the group median,
result showed that there were slightly more (56%,
n=188) young people who have a low level of
information literacy than those with a high level
(44%, n=148). Majority of the young people
perceived themselves to have a high level of
technology savviness. Almost two thirds of our
sample (61.4%, n=197) rated their technical skills
and general technology savviness as at least
intermediate or advanced with 35.5%
advanced/intermediate level and 25.9% advanced
level. A quarter of the sample (25.8%, n=99) rate
themselves at intermediate level and only a minority
(7.8%, n=25) perceived low or intermediate/low level
of technology savviness. More young people reported
‘rarely’ (19.2%, n=65) or ‘never’ (37.9%, n=128)
engaging in online shopping compared to those who
did engage in such activity (42.9%, n=145). It should
be noted that there were almost a quarter (23.1%,
n=78) who do online shopping using their mobile
phone on a ‘frequently’ or ‘all the time’ basis.
Similarly, there is a high percentage of young people
(44.7%, n=141) who use free wifi in public areas on a
regular basis (i.e. frequently or all the time) compared
to those who rarely or never (27%, n=85).
Table 3 Application access on mobile phone
Table 4 Privacy and security measures on mobile
phone
Password Security
Measures
N %
Mobile password
protected (n=321)
230 71.7
Sim-card password
protected (n=319)
127 39.8
Set password yourself
(n=308)
229 74.7
How often do you change
your password? (n=319)
Once after purchase 16 5.0
Frequently 31 9.7
Occasionally 67 21
4.2. Correlation Analysis
The following section presents inferential
statistics, that include comparative and correlational
analyses to further explore and examine the
distribution and relationship between the main
variables in the study.
We now present the results and analysis focusing
on the exploration of attitudes of young people
towards data security on mobile phones.
Here we were particularly interested in
investigating how the perceived risks of data security,
security measures and frequency of online activities
are related to ethnicity, gender and student status
(Table 6). Both Analysis of Variance (ANOVA)
(more than 2 groups) and Independent Sample t-test
(2 groups) were used to examine the group
differences across ethnic groups, gender and student
status. Result from comparative analyses indicated
that there were significant differences in the
perception on mobile phone data security among
young people across ethnic background and student
status. It was found that young people of Non-White
ethnic background tend to have higher awareness of
Security
of data
Risk of
using free
wifi
A virus
of Worm
attack
A wireless
attach
(Bluetooth
or wifi
)
Absolutely
unconcerned/
Somewhat
concerned
80
(24.5%)
114
(35.5%)
106
(32.2%)
103
(32.2%)
Neutral 85
(
26.5%
)
100
(
30.3%
)
63
(
19.7%
)
62
(
19.4%
)
Somewhat
concerned/
Absolutely
concerned
156
(48.6%)
107
(33.3%)
150
(47.1%)
155
(48.4%)
Total 321
(
100%
)
321
(
100%
)
319
(
100%
)
320
(
100%
)
Yes Some-
times
No Total
Allow
applications to
access info
38
(11.9%)
157
(49.1%)
125
(39.1%)
320
(100%)
Allow
applications to
access
contacts
39
(12.4%)
114
(36.2%)
162
(51.4%)
305
(100%)
4509
mobile phone data security than those of White ethnic
background (t=-.3.38, p<.001). Specifically, post-hoc
analysis showed that young people of Black and
Asian ethnic background reported greater awareness
of mobile phone data security than young people of
White ethnic background (F=5.06, p<.001).
Similarly, overseas students also demonstrated higher
level of awareness towards mobile phone data
security compared to Home/EU students (t=4.10,
p.<.001).
In terms of gender differences, young men were
found to be more likely to allow applications to
access their personal information and contact details
on phone and do online shopping than young women.
However, it should be noted that these differences
were only marginally significant, p<.10.
Table 8 presents results of the correlational
analysis between socio-demographic characteristics
with youth perception on mobile phone data security,
personality, IT/Information literacy and online
activities. Person Product Moment Correlation was
used to determine the magnitude and direction of the
relationship between these variables. It was found
that older students reported significantly greater
awareness of security threats on mobile phone than
younger students (r=19, p<.001). Young people of
White ethnicity background (r=-.20, p<.0001) and
those who are Home/EU students (r=.24, p<.0001)
tended to report lower level of concern on the
vulnerability of mobile phone security. Results in
Table 8 also showed that not only White (r=.13,
p<.05) and Home/EU students (r=-.12, p<.05) were
more likely to report a more extroversion personality,
they were also less information/IT literate (Ethnicity:
r=-.21, p<.0001; Student status: r=.22, p<.0001).
Surprisingly, females tend to score higher in
extroversion personality as compared to males in the
present study (r=-.17,p<.001).
Table 9 presents the result of the correlations
between perception on mobile phone data security,
personality, IT literacy and online activities among
young people. It was found that young people who
are more concerned about the threats on their mobile
phone security were more literate in information
technology (r=.15, p<.001), less likely to allow
applications to access their personal details (r=-.14,
p<.05) and more regular in using password security
measures on mobile phones (r=.14, p<.05). Besides,
young people who have higher awareness towards
mobile phone security threats are also less likely to
have an extrovert personality (r=-.12, p<.0001).
In addition, young people who are more
extroverted not only experienced higher tendency to
use free wifi in public area (r=.17, p<.001) but also
allow applications to access personal information
(r=.12,p<.05). Young people with extroverted
personality were also more IT literate (r=.14, p<.05)
and regularly use password as security measures on
mobile phone (r=.12, p<.05). Those who are more IT
literate tend to be more likely to use their mobile
phone for activities such as online shopping (r=.34,
p<.0001), free wifi in public areas (r=.14, p<.05) and
allow applications to access to information in their
mobile phones (r=.17, p<.001).
5. Conclusion
For young adults, the importance of mobile phones
as the device of choice coupled with continuous
network connectivity raises key issues of risk-taking
behaviours. The attitudes of young people towards
data/information security are particularly important.
Further, the gamut of communications styles and the
range of activities that can be performed on a phone
increases considerable risk arising from data security
and privacy concerns. Our research with students
from four UK universities has shown factors related
to IT literacy, data security measures and
online/application activities are correlated with
different demographic groups. Of note, are the
comparative analyses that indicate significant
differences on the risks associated with data security
with respect to ethnic groups, gender and student
status (Overseas versus Home/EU). The level of IT
literacy also determined the extent to which apps are
allowed to access data from the phone or the extent to
which the use of free public wifi is adopted. Another
key finding of this study is that young people’s
personality is also significantly related to their use of
mobile phone technology and perceptions of data
security.
We acknowledge limitations of the findings
reported here. Specifically, we accept that the young
people participating in this project are from the
tertiary education sector and hence generalisations to
the wider younger population should be treated with
caution. Further, sensitive data such as financial
personal data and how young people handle it on
mobile phones needs further research.
Given the move towards mobile devices, research
that explores behaviour of young people in their use
of mobile technology continues to increase in
importance. Thus, this study contributes current
findings on the use of smart phones in the context of
internet related activity and presents findings that
note significant differences towards information
security between different demographic groups.
These distinctions have potential marketing, technical
4510
and policy implications to those involved in the eco-
systems around mobile technology.
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4511
Table 5 Factors influencing data/information security
Variable n (%) Mean (SD) Median Min Max
Personality (Extraversion) (n=297) 7.89 (3.22) 9.00 0 12
Low 179 (60.3)
High 118 (39.7)
Information & IT literacy measures
Information Literacy (n=336) 6.55 (3.11) 6.00 3 15
Low 188 (56.0)
High 148 (44.0)
Self-assessed ‘Tech Savviness’ (n=336) 3.77 (0.97) 4.00 1 5
Low 7 (2.2)
Intermediate/Low 18 (5.6)
Intermediate 99 (25.8)
Advanced/Intermediate 114 (35.5)
Advanced 83 (25.9)
Frequency of Online Shopping (n=336) 2.35 (1.33) 2.00 1 5
Never 128 (37.9)
Rarely 65 (19.2)
Occasionally 67 (19.8)
Frequently 52 (15.4)
All the time 26 (7.7)
Free wifi use at public places (n=336) 3.24 (1.26) 3.00 1 5
Never 38 (12.1)
Rarely 47 (14.9)
Occasionally 89 (23.2)
Frequently 81 (25.7)
All the time 60 (19.0)
Data security and Privacy
Perception of data security (n=311) 39.47 (8.05) 40.00 16 55
Low 166 (53.4)
High 145 (46.6)
Password security (n=306) 2.20 (1.34) 2.00 0 4
Low 159 (52.0)
High 147 (48.0)
Application Accessibility (n=315) 3.35 (1.20) 3.00 2 6
Low 170 (54.0)
High 145 (46.0)
4512
Table 6 Description of Data Security Measures across Ethnicity, Gender and Student Status
Perception on
Mobile Phone Data
Security
Password
security
measures
Applications
Accessibility
Frequency of
Online
Shopping
Usage of free
wifi at public
places
N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD)
Ethnicity
White British
(WB)
72 36.44 (6.95) 74 3.34 (1.41) 71 2.18 (1.41) 74 2.45 (1.37) 71 3.25 (1.23)
Other White
(OW)
63 39.52 (7.93) 62 3.27 (1.16) 62 2.16 (1.46) 63 2.17 (1.31) 63 3.21 (1.22)
Black (B) 40 42.00 (7.71) 39 3.15 (0.99) 36 1.67 (1.39) 40 2.63 (1.39) 41 2.97 (1.42)
Asian/Asian
British (AB)
75 40.97 (7.83) 76 3.35 (1.01) 75 2.34 (1.19) 77 2.30 (1.31) 76 3.30 (1.29)
Mixed (M) 20 41.85 (9.24) 21 3.67 (1.32) 21 2.57 (1.33) 21 2.24 (1.14) 21 3.71 (0.90)
Others (O) 9 39.88 (9.86) 9 3.00 (1.12) 9 2.13 (1.25) 9 2.67 (1.22) 9 3.67 (1.11)
F-value# 5.06**
WB<B,AC,
n.s. 2.14+
n.s. n.s.
White 129 38.16 (7.54) 12
8
2.17 (1.44) 130 3.31 (1.32) 13
1
2.33 (1.24) 12
8
3.24 (1.44)
Non-White 135 41.42 (8.14) 13
2
2.14 (1.31) 136 3.31 (1.08) 13
8
2.41 (1.30) 13
2
2.14 (1.31)
t-value -3.38*** n.s. n.s. n.s. n.s.
Gender
Male 134 39.67 (7.95) 13
0
214 (1.38) 134 3.46 (1.22) 13
7
2.51 (1.26) 13
6
3.33 (1.21)
Female 151 39.50 (8.18) 14
4
2.24 (1.35) 149 3.21 (1.15) 14
9
2.23 (1.39) 14
7
3.18 (1.30)
t-value n.s. n.s. 1.81+ 1.85+ n.s.
Student status
Overseas 67 43.01 (7.39) 67 2.06 (1.39) 68 3.47 (1.18) 70 2.39 (1.25) 69 3.34 (1.34)
Home/EU 213 38.51 (7.97) 20
7
2.23 (1.35) 215 3.28 (1.19) 21
6
2.36 (1.35) 21
4
3.21 (1.23)
t-value 4.10*** n.s. n.s. n.s. n.s.
Note. +p<.10 *p < .05. **p < .01. ***p < .001 # Mixed and Other ethnic groups were excluded for ANOVA due to
small sample size.
Table 7 Sample questions
Sample Questions
Information & IT literacy measures:
a) Do you use FREE WIFI in public places? (Yes, No)
b) How do you rate your technical skills and general ‘tech’ savviness? (Advanced, Intermediate, Low)
Password security and data privacy:
a) Is your mobile phone password protected? (Yes, No)
b) Is your simcard password protected? (Yes, No)
c) How often do you change your password? (once after purchase, frequently, occasionally, rarely, never)
d) Do you allow application to access your contact? (Yes, Sometimes, No)
e) Do you allow applications to access your personal information? (Yes, Sometimes, No)
Perception of data security:
a) In general, to what degree are you concerned about the risk of using any FREE WIFI in public places?
b) To what degree are you concerned about the security of data in your mobile phone being compromised by A virus or worm
somehow getting into your mobile phone?
The full research instrument is available from the authors (b.barn@mdx.ac.uk)
4513
Table 8 Correlational Analysis of Socio-demographic Characteristics with youth perception on mobile phone data
security, Personality IT Literacy and Online Activities
Socio-
Demographic
Characteristics
r-value
Perception
on Mobile
Phone
Data
Security
Extraversion
Personality
Frequency
of Online
Shopping
Usage of
free wifi at
public
places
Information
Literacy
Applications
Accessibility
Password
security
measures
1. Age (years) .19*** -.11+ .03 -.03 -.20 -.10 -.08
2. Gender
(1=Male,0=Fe
male)
.01 -.17** .11+ .06 .08 .11+ -.04
3. Ethnicity
(1=White,0=N
W)
-
.20***
.13* -.03 -.02 -.21*** .00 .01
4. Overseas
students
(1=Yes,0=No)
.24*** -.12* .01 .04 .22*** .07 -.05
5. Intact family
(1=Yes,0=No)
.07 -.01 -.03 .03 .08 -.03 -.01
6. Living away
from Home
(1,0)
-.01 .06 -.06 -.04 .00 .06 -.10+
7. Father
Education level
.00 .12+ -.13* -.12+ .05 .16* -.01
8. Mother
Education level
-.10 .07 -.08 .03 .03 .08 .04
Note. +p<.10 *p < .05. **p < .01. ***p < .001
Table 9 Correlational Analysis of youth perception on mobile phone data security, Personality, IT Literacy and
Online Activities
Variables
r-value
Perception
on Mobile
Phone Data
Security
Extraversion
Personality
Frequency of
Online
Shopping
Usage of
free wifi at
public
places
Information
Literacy
Applications
Accessibility
Password
security
measures
1. Perception on
Mobile Phone
Data Security
-
2. Extraversion
Personality
-.12* -
3. Frequency of
Online
Shopping
.07 .00 -
4. Usage of free
wifi at public
places
-.07 .17** -.11+ -
5. Information
Literacy
.15** .14* .34*** .14* -
6. Applications
Accessibility
-.14* .12* .05 .01 .17** -
7. Password
security
measures
.14* .12* .10+ .06 .13* .02 -
Note. +p<.10 *p < .05. **p < .01. ***p < .001
4514