-
Thông tin
-
Quiz
Psychiatry, Psychology and Law - Tài liệu tham khảo | Đại học Hoa Sen
Psychiatry, Psychology and Law - Tài liệu tham khảo | Đại học Hoa Sen và thông tin bổ ích giúp sinh viên tham khảo, ôn luyện và phục vụ nhu cầu học tập của mình cụ thể là có định hướng, ôn tập, nắm vững kiến thức môn học và làm bài tốt trong những bài kiểm tra, bài tiểu luận, bài tập kết thúc học phần, từ đó học tập tốt và có kết quả
Môn: Nghiên cứu Marketing (MKT20001) 21 tài liệu
Trường: Đại học Hoa Sen 4.8 K tài liệu
Thông tin:
Tác giả:
Preview text:
This article was downloaded by: [York University Libraries] On: 03 January 2015, At: 15:30 Publisher: Routledge
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered
office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Psychiatry, Psychology and Law
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/tppl20
Fear of Cyber-Identity Theft and Related Fraudulent Activity
Lynne D. Roberts a , David Indermaur b & Caroline Spiranovic b
a School of Psychology and Speech Pathology, Curtin Health
Innovation Research Institute, Curtin University , Perth , Australia
b Crime Research Centre, University of Western Australia , Crawley , Australia Published online: 01 May 2012.
To cite this article: Lynne D. Roberts , David Indermaur & Caroline Spiranovic (2013) Fear of Cyber-
Identity Theft and Related Fraudulent Activity, Psychiatry, Psychology and Law, 20:3, 315-328, DOI: 10.1080/13218719.2012.672275
To link to this article: http://dx.doi.org/10.1080/13218719.2012.672275 PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the
“Content”) contained in the publications on our platform. However, Taylor & Francis,
our agents, and our licensors make no representations or warranties whatsoever as to
the accuracy, completeness, or suitability for any purpose of the Content. Any opinions
and views expressed in this publication are the opinions and views of the authors,
and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content
should not be relied upon and should be independently verified with primary sources
of information. Taylor and Francis shall not be liable for any losses, actions, claims,
proceedings, demands, costs, expenses, damages, and other liabilities whatsoever
or howsoever caused arising directly or indirectly in connection with, in relation to or
arising out of the use of the Content.
This article may be used for research, teaching, and private study purposes. Any
substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,
systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &
Conditions of access and use can be found at http://www.tandfonline.com/page/terms- and-conditions
Psychiatry, Psychology and Law, 2013
Vol. 20, No. 3, 315–328, http://dx.doi.org/10.1080/13218719.2012.672275
Fear of Cyber-Identity Theft and Related Fraudulent Activity
Lynne D. Robertsa, David Indermaurb and Caroline Spiranovicb
a School of Psychology and Speech Pathology, Curtin Health Innovation Research Institute, Curtin
University, Perth, Australia; bCrime Research Centre, University of Western Australia, Crawley, Australia
Identity theft and related fraudulent activities affect approximately one in twenty-five
adults each year across western societies. The Internet provides a new avenue for
obtaining identity tokens and identifying information and increases the scale on which
identity theft can be perpetrated. Recent research has suggested that fear of these types of
crimes now matches or exceeds the fear of traditional place-based crimes, and has the
potential to curtail online activities and hinder the further development of e-commerce
applications. In this article, we conduct exploratory research identifying predictors of
fear of cyber-identity theft and related fraudulent activities, based on the analysis of
items included in the Australian Survey of Social Attitudes (2007). Fear was predicted by
a generalized fear of crime component and a specific Internet exposure component.
Traditional predictors of fear of crime were insignificant or weak predictors, highlighting the need for further research.
Key words: cyber-identity theft; cyber-victimization; fear of crime; fraud; identity theft.
The Internet provides new opportunities
location) of data acquisition. Further, the
for criminal activities. It may be used to
Internet provides the means for conducting
ork University Libraries] at 15:30 03 January 2015
support existing criminal activities, provide
fraudulent activity with the stolen identity
new ways of conducting existing criminal
tokens, including online banking and e-
activities, extend the geographic reach of commerce.
criminal activities or create new types of
In this article, we first examine what is
criminal activity (Savona & Mignone,
currently known about cyber-identity theft.
2004). One type of cyber-criminal activity
Information on the incidence of identity
that is frequently featured in the media is
theft and related fraudulent activity across Downloaded by [Y
cyber-identity theft and related fraudulent
three countries, the United States of Amer-
activity. The Internet enables an extension
ica (USA), United Kingdom (UK) and
from ‘‘traditional’’ identity theft (the mis-
Australia is presented. This analysis high-
appropriation of identity tokens such as
lights the difficulty of determining the
credit cards through non-technical means
percentage of this activity that is cyber-
such as mail theft) to the online harvesting
related. We then examine fear of cyber-
of identity tokens, potentially on a larger
identity theft and related fraudulent activ-
scale due to information and communica-
ity, situating our discussion within the body
tion technologies increasing the ease and
of literature concerning fear of traditional
reducing the costs (time, financial and
place-based crimes. In the body of this
Correspondence: Lynne.Roberts@curtin.edu.au
© 2013 The Australian and New Zealand Association of Psychiatry, Psychology and Law
316 L. D. Roberts et al.
article we examine possible predictors of
Solutions for 40 million credit card custo-
fear of cyber-identity theft and related
mers (Haygood & Hensley, 2006). The ease
fraudulent activity. Three categories of
of obtaining identity tokens and identifying
predictors are considered. The first relates
information online changes the scale on
to demographic variables, the second to
which identity theft can be perpetrated,
fear of traditional crime and the third to
expanding the range of potential victims
levels of access and activity on the Internet.
(Finch, 2007; Marshall & Tompsett, 2005).
It appears that traditional demographic
The number of individuals directly
predictors of fear of crime victimization,
affected by cyber-identity theft remains
such as age and gender, are poor predictors
difficult to estimate, partly because most
of fear of cyber-identity theft victimization.
victims of identity theft and related frau-
By contrast, fear of physical place-based
dulent activity are unaware of how the
crime and Internet use variables were
perpetrator obtained their identity tokens
relatively stronger predictors of fear of
or identifying information. Whilst the
cyber-identity theft. These results suggest
individual knows they have been the victim
that to understand the nature of the fear of
of a fraud, they remain unaware of whether
cyber-identity theft and related fraudulent
this was as a result of an online breach or
activity comprehensively, a research pro-
through some offline means. For example,
gramme incorporating investigations at
Synovate (2007) reported that the majority
both quantitative and qualitative levels is
(56%) of identity fraud victims did not needed.
know how their identity information was
obtained. In 2001, a United States Federal
Trade Commission director claimed that Cyber-Identity Theft
fewer than 1% of reported cases of identity
Cyber-identity theft1 involves the online
fraud could be linked to the Internet
misappropriation of identity tokens. Com-
(Verton, 2001). Similarly, the results from
mon online identity tokens include email
the Pew Internet Tracking Report (Fox,
addresses, web pages and the combination
2001) indicated that only 8% of identity
of username and password used to access
theft victims indicated the Internet might
ork University Libraries] at 15:30 03 January 2015
systems such as online banking. Traditional
have been involved. Despite the technolo-
identity tokens can also be harvested online
gical and personal factors conducive to
and include name, contact details (address,
cyber-identity theft, at present offline iden-
telephone number), tax file numbers and
tity theft appears to be the most commonly
social security numbers. These identifiers
utilized form, although this may change in
are sufficient for an individual to obtain a the future. Downloaded by [Y
credit card in the victim’s name (Sweeney,
Although the proportion of identity 2006).
theft and related fraudulent activity attri-
Cyber-identity theft typically combines
butable to the Internet is unknown, popu-
the affordances of new information and
lation surveys conducted over the last
communication technologies (ICTs) with
decade are providing estimates of the
social engineering and includes methods
proportion of the population affected by
such as hacking, phishing, pharming, traffic
identity theft and related fraudulent activity
redirectors, advance-fee frauds, fake taxa-
of all types. Available estimates from the
tion forms, keyloggers and password stea-
USA, UK and Australia are reviewed
lers (Paget, 2007). Hacking has been
below. While these prevalence statistics
employed successfully to obtain mass iden-
provide an indication of the extent of the
tifying information, including the account
problem of identity theft, White and Fisher information held by Card Systems
(2008) caution that our knowledge of
Fear of Cyber-Identity Theft and Related Fraudulent Activity 317
identity theft is hampered by variations in
households in the USA had at least one
definitions used and reporting practices.
household member who was a victim of
In the USA, major population surveys
identity theft in the previous six months
on identity theft have been conducted by
(Baum, 2006). The results obtained from
two organizations, Synovate (for the Fed-
these population surveys are reasonably
eral Trade Commission) and Javelin Strat-
consistent. They suggest that identity theft
egy and Research. Questions on identity
affects about 1 in 25 adults in the USA each
theft have also been included in the
year. However, for the majority of victims,
National Crime Victimization Survey. Ja-
the financial impact of victimization is
velin Strategy and Research conducted
small and only limited time is required to
population-based telephone surveys to es-
resolve problems associated with the theft
timate the number of identity fraud victims. and resultant fraud.
Survey estimates suggest that the annual
The major report on identity fraud in
incidence of identity fraud victimizations
the UK, Identity fraud: A study (Cabinet
decreased over the period 2004 (4.25%) to
Office, 2002); estimated the cost of identity
2007 (3.58%), but increased in 2008 to
fraud was £1.3 billion, accounting for
4.32% (Javelin Strategy and Research,
approximately one tenth of all fraud in
2009). It was estimated that in 2009 in
the UK [updated in 2006 to £1.72 billion
excess of 11 million Americans had been the
(see http://www.ips.gov.uk/identity/down-
victim of identity fraud (Javelin Strategy
loads/FINAL-estimate-for-annual-cost-of-
and Research, 2010). The approximate
fraud-table-v1-2.pdf]. Questions relating
dollar value associated with the fraudulent
specifically to credit card fraud experienced
activity followed a similar trend, decreasing
by members of the public were included in
from $60 in 2004 to $45 in 2007, followed
the 2005/2006 British Crime Survey. Based
by an increase to $48 in 2008 and $3632 in
on survey results, it was estimated that 4%
2009 (Javelin Strategy and Research, 2009,
of UK credit card holders had been victim
2010). Based on a population telephone
of credit card fraud over the previous 12-
survey, Synovate (2007) estimated that
month period (Hoare & Wood, 2007). Thus
3.7% of the adult US population were a
the estimates of prevalence are very similar
ork University Libraries] at 15:30 03 January 2015
victim of identity theft in 2005, a decline to those for the USA.
from the 2003 survey estimate provided by
In Australia, the most recent reliable
Synovate (2003) of 4.6%. Synovate esti-
estimates of the extent of identity fraud
mated that in 2005 the median ‘‘out of
come from the Australian Bureau of
pocket’’ expense to individual victims was
Statistics (2008) Personal Fraud survey
nil, and the median time spent resolving
conducted in the second half of 2007. Downloaded by [Y
identity theft problems was 4 hours. How-
Population estimates from the survey sug-
ever, some victims incurred considerably
gest that in the previous 12 months, 3.1% of
higher out of pocket expenses (95th per-
Australians over the age of 15 years were
centile $2,000) and spent longer periods
the victims of identity fraud. The majority
resolving their problems (95th percentile
(77%) were victims of bank card or credit
130 hours). Costs and hours were higher for
card fraud and spent less than 10 hours
victimizations where new accounts were
resolving the fraudulent activity. More than
established than where fraudulent activities
a third (36.3%) of credit and bank card
were restricted to existing credit and non-
fraud victims and more than a quarter
credit card accounts (Synovate, 2007). The
(26.8%) of other identity theft victims in
National Crime Victimization Survey in-
this Australian survey did not know the
cluded questions about identity theft in
method of fraud used. However, email or
2004, reporting that 3% (3.6 million) of
Internet was identified as the method of
318 L. D. Roberts et al.
fraud in 19.8% of incidents of credit or
may be some cross-cultural variability with
bank card fraud and 21.2% of other
respect to the relationship between identity
identity theft incidents (Australian Bureau
fraud and victim demographics such as age
of Statistics, 2008). Despite this, almost half
and gender. However, the Australian data
(45%) of respondents in a further popula-
mirror those of the USA in indicating
tion-based survey conducted in Australia
that affluence is associated with identity
thought the Internet was the most likely fraud.
method of identity fraud, with 60% of
Typically, individuals are not regarded
respondents concerned about becoming a
by law enforcement or legal agencies as the
victim of identity fraud (Wallis Consulting
primary victims of identity theft-related
Group, 2007). These results indicate that
fraud. Instead, the status of primary victim
the public perceive cyber-identity theft to be
is assigned to defrauded creditors: typically
a more commonly used form of identity
banks and other financial organizations
theft than the statistics indicate is likely to
which incur the financial cost of identity- be the case.
related fraud (LoPucki, 2001). As pre-
Recent research has begun to analyse
viously outlined, for most individual vic-
the risk of victimization at state, commu-
tims of identity theft, there are minimal
nity and individual levels. At a macro level,
financial and time costs involved in dealing
Higgins, Hughes, Ricketts, and Wolfe
with identity-related fraud. However, some
(2008) examined state-level correlates of
victims can incur financial costs associated
identity theft victimization in the USA,
with lost wages, medical expenses and
utilizing Federal Trade Commission re-
expenses incurred in restoring the integrity
ports and census data. Identity theft com-
of identity (Identity Theft Resource Centre,
plaints were higher in states with lower
2003, 2005; Jefferson, 2004; LoPucki, 2001).
ratios of males, but higher ratios of African
The cost to the individual is partially
Americans, residential mobility, public as-
dependent upon the time interval from the
sistance and recreation and entertainment
theft to discovery, such that costs increase
venues. At a micro level, Anderson (2006)
with longer intervals (Synovate, 2003).
reanalysed the data from the Federal Trade
Secondary victimization in the form of
ork University Libraries] at 15:30 03 January 2015
Commission’s 2003 survey to examine the
denial of credit, increased insurance and
demographic characteristics of identity
credit card interest rates, cancellation of
theft victims. Age, gender and income
credit cards, denial of services (phone,
were predictors of identity theft victimiza-
utilities) and continued contact by collec-
tion, with younger adults, women and the
tion agencies may result from impaired
more affluent more likely to be victims.
credit rating (Baum, 2006; Identity Theft Downloaded by [Y
In Australia, data regarding the char-
Resource Centre, 2005; Synovate 2003).
acteristics of victims of identify fraud
The psychological, emotional and physical
(including both identity theft and credit or
impact of identity theft also increases for
bank card fraud) are provided through the
those who are unable to easily resolve
Australian Bureau of Statistics (2008)
problems associated with the identity theft
Personal Fraud survey. In the 12 months
(Sharp, Shreve-Neiger, Fremouw, Kane, &
prior to the survey, identity fraud victimi- Hutton, 2004).
zation was more frequently reported by
While it is possible that the psychologi-
males, those aged between 25 and 44 years,
cal impact of identity theft is not affected by
those with higher educational qualifica-
the actual method of its completion (cyber
tions, and those with the highest weekly
versus traditional), there may be important
incomes. Contrasting these results with
differences. Our current inability to differ-
those from the USA, it appears that there
entiate fraudulent activity by the source of
Fear of Cyber-Identity Theft and Related Fraudulent Activity 319
identity theft means that we are not able to
despite their lower risk of victimization
study the effects with accuracy. However,
(see, e.g., Ziersch, Putland, Palmer, Mac-
we are able to investigate the fear indivi-
Dougall, & Baum, 2007), providing support
duals have of these two forms of identity
for the vulnerability thesis. The vulnerabil- theft.
ity hypothesis is also supported by a range
of findings which have shown that unfami-
liarity is linked to the fear of crime. Perhaps Fear of Crime
not surprisingly, people tend to be more
While criminal activities can have direct
aware of situations and places with which
impacts on individual, organizational and
they are less familiar. Even those who live in
community victims, they also have a wider
relatively high crime neighbourhoods re-
indirect impact on individuals and society
port feeling safer in those areas closer to
through fear of crime. Fear of crime,
home compared with other areas of the city
whether or not it has a basis in the
even though those other areas may, on an
likelihood of crime victimization, can nega- objective level, be safer.
tively impact on an individual’s physical
Fear of crime has consistently been
and mental wellbeing and social function-
shown to be out of proportion with the
ing through the curtailment of physical and
actual risk of victimization (Chadee, Aus-
social activities (Stafford, Chandola, &
ten, & Ditton, 2007). Research from Cana- Marmot, 2007).
da suggests that about 12% of the variance
Fear of crime is a concept that has been
in fear of crime can be directly attributed to
defined and measured in a variety of ways
differences in neighbourhood context (Fitz-
including concern about crime, perceived
gerald, 2008), providing modest support for
risk of victimization, perceived threat and
the instrumental hypothesis that fear of
behavioural responses to fear (Skogan,
crime simply reflects actual crime rates, at
1999). Doubt has been cast over whether least at a local level.
the much discussed concept of ‘‘fear of
Previous research has supported the
crime’’ does indeed represent a fear, or is
proposed relationship between perceptions
more accurately defined in terms of a
of incivilities and fear of crime – those that
ork University Libraries] at 15:30 03 January 2015
general anxiety about crime (Warr, 2000).
experience or perceive a higher level of
There are also questions about the best way
incivilities also experience higher levels of
to measure, reflect or tap in to the
fear of crime (Borooah & Carcach, 1997;
experience of fear (see Ditton & Farrell
Carcach, Frampton, Thomas, & Cranich, 2007).
1995; Kanan & Pruitt, 2002; McCrea, Shyy,
A range of theories has been developed
Western, & Stimson, 2005; Roberts & Downloaded by [Y
to make sense of what we know about the
Indermaur, forthcoming; Wyant, 2008).
fear of crime. Briefly, these can be classified
However, these findings may also be inter-
as relating to the vulnerability of the victim
preted as being consistent with the vulner-
(the ‘‘vulnerability thesis’’); the (perceived) ability hypothesis as perceptions of
risk of victimization (the ‘‘instrumental
incivilities contribute to a heightened
thesis’’); (perceived) incivilities within the awareness of vulnerability.
environment (the ‘‘incivilities thesis’’); and
psychological factors (Hale, 1996).
Demographic factors have been ex- Fear of Cyber-Identity Theft
plored as predictors of fear of crime with
While fear of crime has received substantial
relatively consistent findings that women
research attention, limited research has
and the elderly experience higher levels of
been conducted on fear of cyber-crime, or
fear of crime than men or younger adults,
more specifically fear of cyber-identity theft
320 L. D. Roberts et al.
and related fraudulent activity. Qualitative
forthcoming) we analysed the AuSSA
research has suggested that fear of cyber-
survey data to compare worry about tradi-
identity theft incorporates fear of financial
tional place-based crime with worry about
losses, damage to reputation and loss of
emerging forms of criminal activity enabled
online privacy (Hille, Walsh, Brach, &
by the rapid development of ICTs, particu-
Dose, 2011). Some researchers (e.g., Wall,
larly the Internet. A major finding of this
2008a, 2008b) have argued that fear of
research was that worry about identity-
cyber-crime is largely driven by myth
related crime is now matching, and for
perpetuated by the media, and may not be
some offences exceeding, worry about more
in proportion to the objective reality of
traditional place-based crime. The illegal
cyber-crime. The results from those studies
use of credit cards over the Internet was one
that have included measures relevant to the
of the crimes included in this survey that
fear of cyber-identity theft and related
generated the highest levels of worry (23%
fraud in the USA, UK and Australia are
‘‘very worried’’, 27.9% ‘‘fairly worried’’). summarized below.
Fear of having identity stolen via the
In an early study by the Pew Internet
Internet was also a source of worry
and American Life Project (Fox, 2001) the
(15.9% ‘‘very worried’’, 24.4% ‘‘worried’’).
majority of Americans surveyed (87%)
These two items were combined with
were concerned about credit card theft
worry about having a credit card stolen to
online, with 69% ‘‘very concerned’’. Fe-
produce a fear of identity-theft-related
males, older adults and African Americans
crime scale. Then analyses of predictors of
were more likely to be ‘‘very concerned’’
fear as measured by this scale were under-
than males, younger adults, Caucasians and
taken. Traditional predictors of fear of Hispanics respectively.
crime (gender, age, years of education,
Although not directly asking about
location) were found to be poor predictors
online fraudulent activity, the British Crime
of worry about identity-theft-related crime.
Survey in 2005/2006 included questions on
Fear of identity-theft-related crime was
fear of credit card fraud. More than half
lower for males than females, but ac-
(57%) of the respondents who owned credit
counted for less than 1% of the variation
ork University Libraries] at 15:30 03 January 2015
cards reported that they were ‘‘fairly’’ or
in fear of identity-related crime scores. Age
‘‘very’’ worried about being a victim of card
was not a significant predictor. Location
fraud. Notably, this percentage was higher
(metro/rural) and perceptions of incivilities
than worry about any of the traditional
were significant predictors, accounting for
crimes also asked about in the survey.
5.3% of variance (Roberts & Indermaur,
Respondents who had been the victim of forthcoming). Downloaded by [Y
credit card fraud in the previous year were
In this article, we build on this previous
more likely to be worried than those who
research to specifically examine fear of
had not (Hoare & Wood, 2007).
cyber-identity theft and related fraudulent
The Australian Survey of Social Atti-
activity, using two items from the AuSSA
tudes (AuSSA) has been conducted four
survey that specified the Internet in relation
times between 2003 and 2009. The 2007
to fear of crime. Given the poor predictive
sweep of the survey included, for the first
ability of traditional predictors of fear of
time, items related to worry about a range
crime to predict fear of cyber-identity theft
of crimes. Extending on our primary
and related fraudulent activity, we were
analysis of the crime and justice items
interested in exploring a range of other included in the AuSSA 2007 survey possible predictors.
(Roberts & Indermaur, 2009), in our
First, a finding from the Australian
recent research (Roberts & Indermaur,
Bureau of Statistics (2008) Personal Fraud
Fear of Cyber-Identity Theft and Related Fraudulent Activity 321
survey was that individuals on higher
from the Australian electoral roll. Pre-
incomes were at higher risk of victimiza-
survey invitation letters were sent to the
tion. We hypothesized that if fear of crime
randomly selected individuals and were
has some basis in risk of victimization (the
followed by the survey package and three
‘‘instrumental hypothesis’’), then fear of
reminders. The final set of respondents
cyber-identity theft and related fraudulent
consisted of 8,133 adults from all states
activity will be higher for those with high
and territories in Australia. Final response
incomes than those on lower incomes.
rates for the three questionnaires ranged
Second, Roberts and Indermaur (forth-
from 39 to 42%. Further details of the
coming) suggested there may be a general-
survey, methodology and weighting of the
ized fear component underlying both fear
sample are provided in Roberts and In-
of traditional crime and fear of identity-
dermaur (2009). The data set analysed was
related crime. We hypothesized that fear of
provided by the Australian National Uni-
place-based crime will significantly predict
versity (Phillips, Mitchell, Tranter, Clark,
fear of cyber-identity theft and related & Reed, 2008).
fraudulent activity. Positive results here
would suggest the operation of a general-
ized fear of crime component. The failure to Participants
find a significant relationship might suggest
The subset of AuSSA 2007 survey respon-
that fear of place-based crime and fear of
dents included in this research is 1,550
cyber-crime are distinct concepts.
respondents who completed Form C of the
Third, we were interested in whether
survey and answered each of the questions
Internet use variables could add explana-
of interest for this analysis. Exactly half of
tory power in predicting fear of cyber-
the sample (50%) was female. The mean age
identity theft and related fraudulent activ-
of respondents was 47 years (SD ¼ 15 years).
ity. We hypothesized that Internet use will
The majority of respondents (74%) lived
significantly predict fear of cyber-identity
within a metropolitan area of Australia and
theft and related fraudulent activity (sug-
had completed a mean of 14 years of
gesting a level of exposure component).
education (SD ¼ 4 years). The majority of
ork University Libraries] at 15:30 03 January 2015
Positive results here would suggest that fear
the sample had access to the Internet.
may be related to the level of exposure; a
Seventy-four per cent of the sample used
finding in line with the instrumental hy-
the Internet at home, with 56% of the
pothesis in regard to fear of crime. A
sample using the Internet at work.
significant but inverse relationship might
suggest that fear is related to unfamiliarity; Downloaded by [Y
a finding in line with the vulnerability Measures hypothesis.
The AuSSA 2007 survey covered 35 cate-
gories of attitudes and behaviours. The full
questionnaires are available at http://aus- Method
sa.anu.edu.au/questionnaires.php. A range
The AuSSA is a biennial mail-out survey
of crime and justice items in the AuSSA
that measures Australians’ social attitudes
2007 survey were commissioned by the
and behaviours (Gibson, Wilson, Meagher,
Australian Institute of Criminology and
Denemark, & Western, 2005). The third
were included in two versions of the survey.
biennial survey, AuSSA 2007, was a cross-
Two of the crime and justice items were
sectional mail-out survey, consisting of
used together to produce the measure of
three questionnaire versions. A random
fear of cyber-identity theft and related
selection of 20,000 individuals was obtained
fraudulent activity. These items were:
322 L. D. Roberts et al.
How worried are you that the following
ranging from ‘‘several times a day’’ to ‘‘do will occur to you?
not use the Internet’’. The final item asked
respondents: ‘‘How important are the
. having your identity stolen via the
following in informing your views of crime Internet;
trends and the criminal justice system?’’ and
. having your credit card details used
respondents rated the extent to which the illegally via the Internet.
Internet was important in this regard.
Single item measures of age (years),
These items were selected as covering
gender, years of education, location and
the two dimensions of definitions of cyber-
gross household annual income were also
identity theft, the stealing of identity and
retained for the analysis. Gross household
the use of the stolen identity in a fraudulent
income was recoded into three categories:
act (Grover, Berghel, & Cobb, 2011). Each
low ($0 to $31,199 per annum), medium
item was measured on a 4-point response
($31,200 to $77,999 per annum) and high
scale ranging from ‘‘not worried at all’’ to ($78,000 plus per annum).
‘‘very worried’’. The two items were com-
puted into a scale with good internal consistency (Cronbach’s alpha ¼ .86). Results
Data were recoded so that higher scores
Scores were computed for each individual
on the scale reflects higher levels of fear of
on the fear of crime scales. The mean scale
crime. Possible scale scores thus range from
score on the fear of cyber-identity theft and 2 to 8.
related fraudulent activity scale was 4.97
A further four items were used as a
(SD ¼ 1.9) of a possible scale score range of
measure of fear of traditional place-based
2 to 8. The mean scale score on the fear of
crime. Using the same question stem (How
physical crime scale was 8.47 (SD ¼ 2.68)
worried are you that the following will
out of a possible scale score range of 4 to 16.
occur to you?) respondents were asked
To test the hypotheses that income, fear
about being physically attacked at home,
of traditional place-based crime and Inter-
being physically attacked on the street or
net use would be significant predictors of
ork University Libraries] at 15:30 03 January 2015
other public space, being sexually assaulted
cyber-identity theft and related fraudulent
and having their home/place of residence
activity a hierarchical multiple regression
broken into. Each item was measured on a analysis was conducted.
4-point response scale ranging from ‘‘not
In the first step of the multiple regres-
worried at all’’ to ‘‘very worried’’. The four
sion analysis, traditional predictors of fear
items from the questionnaire were com-
of crime; age, gender, years of education Downloaded by [Y
bined to produce a scale with good internal
and location (metropolitan or non-metro-
consistency (Cronbach’s alpha ¼ .86). Data
politan), along with income, were entered
were recoded so that higher scores on the
into the analysis. Combined, these demo-
scale reflect higher levels of fear of crime.
graphic variables accounted for a small, but
Possible scale scores range from 4 to 16.
significant 0.9% of the variance in fear
Four items were used to provide mea-
of cyber-identity theft and related fraudu-
sures of Internet use. Using the question
lent activity (R2 ¼ .009, F(6,1543) ¼ 2.34,
stem ‘‘Please tell us if you use the Internet at
p 5 .05). Gender was the only significant
any of the following?’’, two items related to
demographic predictor of cyber-identity
the site of Internet use (at home and/or at
theft and related fraudulent activity.
work). A third item asked respondents: ‘‘In
In the second step, fear of physical crime
general, how often do you use the Inter-
was entered into the analysis. This ac-
net?’’ and was measured on a 7-point scale
counted for a significant additional 15.7%
Fear of Cyber-Identity Theft and Related Fraudulent Activity 323
of variance in fear of cyber-identity theft and Table 1.
Unstandardized (B) and standardised
related fraudulent activity (DR2
(b) regression coefficients, and squared semi- ¼ .157,
partial correlations (sr2) for each step of the
DF(1,1542) ¼ 289.23, p 5 .001). In the third
hierarchical multiple regression predicting fear
and final step, the Internet use variables were
of cyber-identity theft and related fraudulent
entered into the analysis, and accounted for activity.
a significant additional 7.8% of variance in
fear of cyber-identity theft and related Variable B b sr2
fraudulent activity (DR2 ¼ .078, DF(4,1538) Step 1
39.78, p 5 .001). Combined, the predicting Age 7.002 7.013 .000 Sex (female) .209* .055 .003
variables accounted for almost a quarter of Education (years) .042 .081 .001
the variance in fear of cyber-identity theft Location (metro) .181 .043 .002
and related fraudulent activity (R2 ¼ .24.4, Income (medium) .085 .019 .000
F(11,1538) ¼ 45.07, p 5 .001). Income (high) .124 .032 .001
Table 1 provides the unstandardized Step 2
and standardized regression coefficients Age .000 7.007 .000 Sex (female) 7.182 7.048 .002
and squared semipartial correlations for Education (years) .042** .081 .006
each predictor variable in each step of the Location (metro) 7.028 7.007 .000
multiple regression analysis. In the final Income (medium) .195 .043 .001
regression model (Step 3), the five signifi- Income (high) .276 .071 .003 Fear traditional crime .297** .416 .157
cant predictors were age (accounting for
less than 1% of the unique variance), fear of Step 3 Age .014** .107 .008
traditional crime (accounting for 14.8% of Sex (female) 7.126 7.033 .001
the unique variance), the importance of the Education (years) .003 .006 .000
Internet for informing views of crime trends Location (metro) 7.111 7.026 .001
and the criminal justice system (accounting Income (medium) .107 .024 .000 Income (high) 7.009 .002 .000
for 1.4% of the unique variance), using the Fear traditional crime .294** .411 .148
Internet at home (accounting for less than Internet views crime .248** .132 .014
1% of the unique variance) and Internet use Use Internet at home .583** .133 .008
frequency (accounting for less than 1% of Use Internet at work .113 .029 .000
ork University Libraries] at 15:30 03 January 2015 Internet use frequency .119** .140 .006 the unique variance). *p 5 .05; **p 5 .01. Discussion
prevent the criminal exploitation. In this
Fear of cyber-victimization, and in parti-
process the period of greatest fear is likely
cular the fear of identity theft over the
to be the period when the form of commu- Downloaded by [Y
Internet, represents a significant threat to
nication is unfamiliar and potential users
the free movement and quality of life of
are alerted to the dangers represented by
citizens in the 21st century. Indeed, identity
criminal opportunists. Arguably, we are at
theft over the Internet could be likened to
that stage now and understanding the
highway robbery of earlier times when
dynamics of fear of identity theft over the
roads and highways began to be used on a
Internet represents a significant obstacle to
regular basis. Just as in these earlier times
the development of this new facility that is
there is a predictable progression. First, a
of benefit to citizens and their legitimate
new avenue of communication is estab- activities everywhere.
lished, it slowly begins to be used, it is
Worry about cyber-identity theft and
quickly discovered as a criminal opportu-
related fraudulent activity is now greater
nity and then exploited. Eventually me-
than worry about many traditional place-
chanisms are developed to address and
based crimes. This is despite findings that
324 L. D. Roberts et al.
the majority of individual victims of cyber-
predict fear of cyber-identity theft and
identity theft and related fraudulent activity
related fraudulent activity, was supported.
experience either no or minimal financial
This finding that fear of traditional place-
and time losses. Most costs are borne by
based crime is a significant predictor of fear
financial institutions providing credit or
of cyber-identity theft and related fraudu-
access facilities. Indeed, Monahan (2009, p.
lent activity suggests that this ‘‘new’’ fear is
157) labels fear of cyber-identity theft a
partially driven by an existing generalized
‘‘moral panic’’ as ‘‘fear of being a victim of
fear component towards all types of crime.
identity theft far outstrips its actual occur-
Indeed, fear of traditional place-based crime
rence, and because extreme actions are
was the strongest predictor of cyber-identity
taken to mitigate it’’. One potential societal
theft and related fraudulent activity in this
impact of an exaggerated fear of cyber-
study. This means that once we know that an
identity theft is decreasing consumer trust
individual scores high on general fear of
and confidence in using the Internet to
crime we can predict that he/she will also
conduct business (Lynch, 2005). This has
score high on fear of cyber-identity theft.
major implications for the future of e-
This finding supports the view that fear of
commerce. Australian research (Australian
crime is a general dispositional factor and
Bureau of Statistics, 2005) suggests that this
not something that is highly discriminatory
may already be impacting on consumer
or dependent on risk. Put another way, an
behaviour, with security concerns prevent-
observed fear of cyber-identity theft prob-
ing more than a quarter of Australians with
ably tells us more about the person than it
Internet access from engaging in online
does about the real risks of identity theft, or
purchasing and transactions. Similarly,
indeed any situational contexts or cues
Reisig, Pratt, and Holtfreter (2009) re-
related to cyber-identity theft. This general-
ported that as the perceived risk of Internet
ized fear of crime has been discussed widely
theft victimization increased, online pur-
in the literature and the findings of the
chasing decreased. Other service and gov-
present study support the robustness of this
ernment organizations may also be affected
construct. One implication of this observa-
as fear and lack of trust mean that
tion is that in addressing fear of crime we
ork University Libraries] at 15:30 03 January 2015
organizations increasingly need to adopt
should focus more on individual, psycholo-
offline methods for customer communica-
gical or dispositional factors related to fear tion (Lynch, 2005).
and focus rather less on the object of the fear. We found mixed support for our
Our third hypothesis, that Internet use
hypotheses regarding potential predictors
would significantly predict fear of cyber-
of fear of cyber-identity theft and related
identity theft and related fraudulent activ- Downloaded by [Y
fraudulent activity. Our first prediction,
ity, was also supported. Three of the four
based on the instrumental hypothesis, that
Internet-use-related variables had a signifi-
fear of cyber-identity theft and related
cant positive association with fear of cyber-
fraudulent activity would be greater for
identity theft and related fraudulent activ-
those with high incomes, was not sup-
ity. The strongest Internet use predictor was
ported. Fear of cyber-identity theft and
how important the Internet was in inform-
related fraudulent activity appears to be a
ing views of crime trends and the criminal
fear common across all socio-economic
justice system. This variable was moder-
groups, even though victim surveys suggest
ately associated with frequency of Internet
that is those on higher incomes who are the
use. In turn, frequency of Internet use and most likely to be victimized.
use of the Internet at home were both
Our second hypothesis, that fear of
significant predictors of fear of cyber- place-based crime would significantly identity theft and related fraudulent
Fear of Cyber-Identity Theft and Related Fraudulent Activity 325
activity. Taken together, these findings sug-
While the findings from this study
gest an ‘‘exposure effect’’, whereby the
provide some interesting insights into the
predictive power of Internet use variables
fear of cyber-identity theft and related
relates to a rational evaluation process in
fraudulent activity, a limitation of the study
which a person may reason that they use the
is the way in which the constructs of interest
Internet frequently and hence would have a
were operationalized. The analysis was
higher likelihood of being the victim of a
based on an existing data set confining the
cyber-related offence. Alternatively, it could
selection of variables. Future research
be the case that frequent Internet users are
would benefit from the development of an
more ‘‘savvy’’ users and understand the ease
expanded measure of fear of cyber-identity
with which an offender could commit cyber-
theft and related fraudulent activity. As
crimes and hence conclude that they could
previously mentioned, specific measures of
unwittingly become a victim of such crimes.
virtual location and the type of activities
Nonetheless, further research is needed to
engaged in online could be included in
ascertain the basis for the predictive power of
future research. Other measures for con-
Internet use variables in the context of cyber-
sideration for inclusion in future research crime-related fear.
include previous victimization, perceptions
Most traditional predictors of fear of
of likelihood of victimization and a mea-
crime included in this research – gender,
sure of the extent to which the individual
education and location – were poor pre-
employs technical and social precautions to
dictors of fear of cyber-identity theft and
reduce their risk of cyber-identity theft and
related fraudulent activity. These findings related fraudulent activity.
suggest that variables traditionally linked
In summary, this research contributes
with fear of crime, such as gender, may not
towards an understanding of the basis of
be relevant in the non-contact online
fear of cyber-identity theft and related
environments. The lack of physicality of
fraudulent activity. Based on the analysis
participants in cyberspace changes some of
of a survey of the Australian population,
the fundamental relations and dynamics
predictors of this fear were identified. The
that underlie the study of traditional forms
strongest predictor was fear of traditional
ork University Libraries] at 15:30 03 January 2015
of crime and by extension the fear of crime.
crime, accounting for approximately 15% of
Similarly, ‘‘physical location’’ is also irrele-
the unique variance in fear scores, suggesting
vant when it comes to cyber-identity theft.
a generalized fear of crime component
One possible area for further research is
underlying the fear of cyber-identity theft
investigation of the possible role of ‘‘virtual
and related fraudulent activity. Internet use
location’’ (the types of virtual environments
variables also significantly contributed to the Downloaded by [Y
an individual uses) as a predictor of fear of
prediction of fear of cyber-identity theft and
cyber-identity theft and related fraudulent
related fraudulent activity, with fear increas- activity.
ing as use increased, and those using the
The only ‘‘traditional’’ significant fear
Internet at home experiencing higher levels
of crime predictor in this study was age,
of fear than those who did not. Traditional
accounting for less than 1% of the unique
predictors of fear of crime were insignificant
variance in fear of cyber-identity theft and
or weak predictors of fear of cyber-identity
related fraudulent activity. Across the three
theft and related fraudulent activity. To
models the contribution of age varied in
understand the nature of the fear of cyber-
both significance and direction, leaving us
identity theft and related fraudulent activity
with little confidence that it is a meaningful
comprehensively a research programme in-
predictor of cyber-identity theft and related
corporating investigations at both quantita- fraudulent activity.
tive and qualitative levels is needed.
326 L. D. Roberts et al.
To conclude, the findings from our study
Australian Bureau of Statistics. (2005). House-
contribute towards an understanding of the
hold use of information technology 2004–05,
Cat. no. 8146.0. Canberra: Author.
fear of cyber-identity theft and related
Australian Bureau of Statistics. (2008). Personal
fraudulent activity. This is an under-re- fraud 2007. Canberra: Author.
searched area within criminology, yet the
Baum, K. (2006, April). Identity theft, 2004:
impact of fear of cyber-crime may be large.
First estimates from the National Crime
This study was important in analysing fear
Victimization Survey. Bureau of Justice
Statistics Bulletin. Retrieved May 27, 2007
of an acquisitive crime that is not in any way
from www.ojp.gov/bjs/pub/pdf/it04.pdf
related to physicality. The findings reflect a
Best, J. (1999). Random violence: How we talk
central irony of our times: advances in
about new crimes and new victims. Berkeley:
technology and communication are accom-
University of California Press.
panied by, or co-occur with, a generalized
Borooah, V. K., & Carcach, C. A. (1997). Crime
and fear: Evidence from Australia. British
fear, aversion to risk and erosion of personal
Journal of Criminology, 37, 635–657.
confidence. Some scholars (e.g., Furedi,
Cabinet Office. (2002). Identity fraud: A study.
1997, 2006) have focused on the culture of
Retrieved May 27, 2007 from http://www.
fear which is exacerbated by media exposes
identitycards.gov.uk/downloads/id_fraud-
of victims. Best (1999) discussed how in this report.pdf
Carcach, C., Frampton, P., Thomas, K., &
regard media imperatives dictate a continu-
Cranich, M. (1995). Explaining fear of crime
ing focus on ‘‘new’’ crimes and ‘‘new’’
in Queensland. Journal of Quantitative dangers. Internet-related identity theft Criminology, 11, 271–287.
clearly fits into these categories and provides
Chadee, D., Austen, L., & Ditton, J. (2007). The
ready grist for the media mill, with a content
relationship between likelihood and fear of
criminal victimization. British Journal of
analysis of media reports on identity theft Criminology, 47, 133–153.
identifying themes of identity theft as ‘‘un-
Ditton, J., & Farrell, S. (2007). The British
stoppable’’ and driven by new technologies
Crime Survey and fear of crime. In M.
(Morris & Gilbert, 2008). The likelihood is
Hough, & M. Maxfield (Eds.), Surveying
crime in the 21st century (pp. 223–243).
that as time passes the use of identity tokens
Monsey, NY: Criminal Justice Press.
will be less novel and people will become
Finch, E. (2007). The problem of stolen identity
more familiar with them and their utility.
and the Internet. In Y. Jewkes (Ed.), Crime
ork University Libraries] at 15:30 03 January 2015
Better safety precautions and mechanisms to
on-line (pp. 29–43). Cullompton, UK: Willan.
prevent and reduce fraud will be developed.
Fitzgerald, R. (2008). Fear of crime and the
However, the general erosion of trust and
neighbourhood context in Canadian cities.
Crime and Justice Research Paper Series.
feelings of impotence are less easily remedied
Ottawa, Ontario: Canadian Centre for
and belong to a much wider social project. Justice Statistics.
Fox, S. (2001). Fear of online crime. Pew Internet Tracking Report. Washington, Downloaded by [Y
DC: Pew Internet & American Life Project. Notes
Furedi F. (1997). Culture of fear: Risk-tasking 1.
A detailed exploration of cyber-identity
and the morality of low expectation. London:
theft is beyond the scope of this article. Cassell.
For a review see Roberts (2008).
Furedi, F. (2006). Culture of fear revisited: Risk- 2.
This is the 2009 figure based on only those
taking and the morality of low expectation. who incurred costs. London: Continuum.
Gibson, R., Wilson, S., Meagher, G., Dene-
mark, D., & Western, M. (2005). Introduc- References
tion. In S. Wilson, G. Meagher, R. Gibson,
Anderson, K. B. (2006). Who are the victims of
D. Denemark, & M. Western (Eds.), Aus-
identity theft? The effect of demographics.
tralian social attitudes: The first report (pp.
Journal of Public Policy & Marketing, 25,
1–11). Sydney: University of New South 160–171. Wales Press.
Fear of Cyber-Identity Theft and Related Fraudulent Activity 327
Grover, A., Berghel, H., & Cobb, D. (2011).
LoPucki, L. M. (2001). Human identification
The state of the art in identity theft.
theory and the identity theft problem. Texas
Advances in Computers, 83, 1–50. Law Review, 80, 89–135.
Hale, C. (1996). Fear of crime: A review of the
Lynch, J. (2005). Identity theft in cyberspace:
literature. International Review of Victimol-
Crime control methods and their effective- ogy, 4, 79–150.
ness in combating phishing attacks. Berke-
Haygood, R., & Hensley, R. (2006). Preventing
ley Technology Journal, 20, 259–300.
identity theft: New legal obligations for
Marshall, A. M., & Tompsett, B. C. (2005).
businesses. Employment Relations Today,
Identity theft in an online world. Computer 33(3), 71–83.
Law & Security Report, 21, 128–137.
Higgins, G. E., Hughes, T., Ricketts, M. L., &
McCrea, R., Shyy, T-K., Western, J., &
Wolfe, S. E. (2008). Identity theft com-
Stimson, R. J. (2005). Fear of crime in
plaints: Exploring the state-level correlates.
Brisbane: Individual, social and neighbour-
Journal of Financial Crime, 15, 295–307.
hood factors in perspective. Journal of
Hille, P., Walsh, G., Brach, S., & Dose, D. Sociology, 41, 7–27.
(2011). Why online identity theft poses a
Monahan, T. (2009). Identity theft vulnerability:
major threat to e-business. In: Proceedings
Neoliberal governance through crime con-
of the ACM WebSci’11 (pp. 1–2). Retrieved
struction. Theoretical Criminology, 13, 155–
August 20, 2011 from http://journal.web 176. science.org/518/.
Morris, R. G., & Longmire, D. R. (2008). Media
Hoare, J., & Wood C. (2007). Plastic card and
constructions of identity theft. The Journal of
identity fraud. In J. Fkatekley (Ed.), Mobile
Criminal Justice and Popular Culture, 15, 76–
phone theft, plastic card and identity fraud: 93.
Findings from the 2005/06 British Crime
Paget, F. (2007). Identity theft. McAfee Avert
Survey (Supplementary Volume 2). Retrieved
Labs technical white paper No 1. Retrieved
February 21, 2009 from http://rds.home
May 27, 2007 from http://www.mcafee.com/
office.gov.uk/rds/pdfs07/hosb1007.pdf
us/local_content/white_papers/wp_id_theft_
Identity Theft Resource Centre. (2003). Identity en.pdf
theft: The aftermath 2003. Retrieved March
Phillips, T., Mitchell, D., Tranter, B., Clark, J.,
2, 2007 from http://www.idtheftcenter.org/
& Reed, K. (2008). The Australian Survey of idaftermath.pdf
Social Attitudes, 2007. Canberra: Australian
Identity Theft Resource Centre. (2005). Identity
Social Science Data Archive, The Austra-
theft: The aftermath 2004. Retrieved March lian National University.
2, 2007 from http://www.idtheftcenter.org/
Reisig, M. D., Pratt, T. C., & Holtfreter, K. idaftermath2004.pdf
(2009). Risk of internet theft victimization:
ork University Libraries] at 15:30 03 January 2015
Javelin Strategy and Research. (2009). 2009 iden-
Examining the effects of social vulnerability
tity fraud survey report: Identity fraud on the
and financial impulsivity. Criminal Justice
rise but consumer costs plummet as protections and Behavior, 36, 369–384.
increase. Pleasanton, CA: Author. Report
Roberts, L., & Indermaur, D. (2009). What
preview retrieved February 21, 2009 from
Australians think about crime and criminal
http://javelinstrategy.com/research
justice: Results from the 2007 Australian
Javelin Strategy and Research. (2010). 2010
Survey of Social Attitudes. Canberra: Aus- Downloaded by [Y
identity fraud survey report: Consumer ver-
tralian Institute of Criminology.
sion. Pleasanton, CA: Author. Report pre-
Roberts, L., & Indermaur, D. (forthcoming).
view retrieved August 16, 2011 from https://
Are neighbourhood incivilities associated
www.javelinstrategy.com/uploads/files/1004.
with fear of crime? In A. Evans (Ed.),
R_2010IdentityFraudSurveyConsumer.pdf
Australian social attitudes, Vol. 3.
Jefferson, J. (2004). Police and identity theft
Roberts, L. D., (2008). Cyber identity theft. In
victims – Preventing further victimisation.
R. Luppicini, & R. Adell (Eds.), Handbook
Australasian Centre for Policing Research, No
of research on technoethics (pp. 542–557).
7. Retrieved March 2, 2007 from http://www. Hershey, PA: Information Science
gov.au/publications2.asp?Report_ID¼154. Reference.
Kanan, J. W., & Pruitt, M. V. (2002). Savona, E. U., & Mignone, M. (2004). Modeling fear of crime and perceived
The fox and the hunters: How IC tech-
victimization risk: The (in)significance of
nologies change the crime race. European
neighborhood integration. Sociological In-
Journal on Criminal Policy and Research, quiry, 72, 527–548. 10, 3–26.
328 L. D. Roberts et al.
Sharp, T., Shreve-Neiger, A., Fremouw, W.,
Wall, D. S. (2008a). Cybercrime and the culture
Kane, J., & Hutton, S. (2004). Exploring the
of fear. Information, Communication and
psychological and somatic impact of iden- Society, 11, 861–884.
tity theft. Journal of Forensic Sciences, 49(1),
Wall, D. S. (2008b). Cybercrime, media and 131–136.
insecurity: The shaping of public percep-
Skogan, W. (1999)Measuring what matters:
tions of cybercrime. International Review of
Crime, disorder and fear. In R. Langworthy
Law, Computers and Technology, 22, 45–63.
(Ed.), Measuring what matters (pp. 37–53).
Wallis Consulting Group. (2007). Community
Washington, DC: U.S. Department of
attitudes to privacy 2007. Report prepared
Justice, National Institute of Justice and
for the Office of the Privacy Commissioner,
Office of Community Oriented Policing
Australia. Retrieved from http://www.privacy. Services.
gov.au/publications/rcommunity07.pdf
Stafford, M., Chandola, T., & Marmot, M.
Warr, M. (2000). Fear of crime in the United
(2007). Association between fear of crime
States: Avenues for research and policy.
and mental health and physical functioning.
Criminal Justice, 4, 451–489.
American Journal of Public Health, 97,
White, M. D., & Fisher, C. (2008). Assessing 2076–2081.
our knowledge of identity theft: The chal-
Sweeney, L. (2006). Protecting job seekers from
lenges to effective prevention and control
identity theft. IEEE Internet Computing,
efforts. Criminal Justice Policy Review, 19, 10(2), 74–78. 3–24.
Synovate. (2003). Federal Trade Commission –
Wyant, B. R. (2008). Multilevel impacts of per-
Identity theft survey report. Report prepared
ceived incivilities and perceptions of crime
for Federal Trade Commission. Retrieved
risk on fear of crime. Journal of Research in
May 20, 2007 from http://www.ftc.gov/os/
Crime and Delinquency, 45, 39–64. 2003/09/synovatereport.pdf
Ziersch, A., Putland, C., Palmer, C., MacDou-
Synovate. (2007). Federal Trade Commission –
gall, C., & Baum, F. (2007). Neighbourhood
2006 identity theft survey report. Report
life, social capital and perceptions of safety
prepared for Federal Trade Commission.
in the western suburbs of Adelaide. Aus-
Verton, D. (2001). Identity thefts skyrocket, but
tralian Journal of Social Issues, 42, 549–562.
less than 1% occur online. Computerworld, 35(7), 7.
ork University Libraries] at 15:30 03 January 2015 Downloaded by [Y