To Shred or Not to Shred: Victims’ Decisions to Engage in Protective Behaviors Following Identity Theft Victimization

There has been no research study to date in the United States (US) looking at how an individual’s immigration status and citizenship might affect their odds of becoming an identity theft victim. This study fills this gap by analyzing the relationship between immigration status and identity theft victimization risk with recently released data from the 2018 iteration of the US National Crime Victimization Survey’s Identity Theft Supplement. Descriptive analysis presents demographics, risky and protective behavior, and identity theft prevalence across US-born citizens, naturalized citizens, non-citizens, and individuals with an ambiguous citizenship status in the US. Logistic regression models explore the differences between these groups in their identity theft victimization risk controlling for other demographic factors and known correlates of identity theft. Results suggest that US-born citizens, naturalized citizens, and non-citizens are at the end of the spectrum with a higher risk of identity theft victimization, whereas individuals with an ambiguous immigration status are at the lower end. Implications of the study findings and future avenues for data collection and research are discussed.

Cases of identity theft are increasing, with incidents of child identity theft rising more quickly than other types of identity theft (Cullen, 2007). Identity theft can be financial, medical, and character-related, with parents being the most common perpetrators (Cullen, 2007; Schmidt & McCoy, 2005). There are two categories of child identity theft victims: child victims and adult/child victims. According to Foley and Nelson (2009), adult/child identity theft victims are those who were victimized while under the age of 18 but did not learn of the crime until they were 18 or older. The sample for this study included six adult/child identity theft victims. This study examined the experiences of adult/child identity theft victims using a phenomenological approach, with Bioecological Theory as a guide to data analysis. The experiences of adult/child identity theft victims are important because of the financial, physical and emotional consequences that may result from this crime. Three themes were identified: Negative Emotional Effects, Lack of Support, and Parent as Perpetrator. A variety of negative emotions were experienced by the participants, including anger and fear. Participants felt a lack of support from their families as well as law enforcement and other agencies from whom help was expected. Half of the participants had their identity stolen by a parent. The person component, context component, and time component of Bronfenbrenner's Bioecological theory helped explain these themes. The results of this research can be used to inform the development of counseling services programs to provide support for adult/child identity theft victims as well as the development of education and training programs for law enforcement and other agencies that interact with adult/child identity theft victims. These trainings need to go beyond how victims are affected financially, and include information about emotional consequences and information about victims' experiences when the perpetrator was a parent. The results of this research can also be used to inform the development of public policy specific to adult/child identity theft victims.

Risk and protective factors of identity theft victimization in the United States

Identity theft, the theft and misuse of another person’s identifying information, impacts approximately one-in-ten American adults annually. Despite its prevalence, low police reporting rates by victims means that the dark figure of identity theft remains substantial, with official statistics representing few cases. Instead, many identity theft victims report to credit card companies and banks, and some report to credit bureaus or other private institutions. Drawing on the 2016 National Crime Victimization Survey – Identity Theft Supplement, this paper investigates identity theft victims’ decisions to report to law enforcement, financial institutions, and credit bureaus. It finds that along with situational factors, measures of seriousness impact reporting to these institutions and most strongly predict reporting to law enforcement. Moreover, this paper tests for interaction effects between paying out of pocket for losses and the other measures of seriousness and finds that victims who pay out of pocket have distinct reporting patterns compared to those who are reimbursed. This paper thus contributes by improving our understanding of the nature of victimizations that come to the attention of identity theft’s various responding institutions.

This study considered whether experiencing cybervictimization is associated with increased recognition of cybervictimization intervention opportunities (i.e., witnessing others' cybervictimization), as well as greater engagement in self-protective (e.g., changing usernames and privacy settings) and other-protective cybervictimization bystander response behaviors. We collected cross-sectional self-report data from an age-diverse (M = 46.29 years, SD = 19.14, range = 15-93) national sample (n = 3002). We hypothesized that: (1) personal experiences with cybervictimization would be associated with increased reports of witnessing opportunities to intervene when others are cybervictimized, greater self-reported use of active bystander behaviors in witnessed situations, and greater use of self-protective strategies; (2) We also expected that engagement in self-protective behaviors would be positively associated with engagement in other-protective bystander behaviors in response to witnessed cybervictimization. To test our hypotheses, we estimated a structural equation model wherein four latent variables were constructed: cybervictimization experienced, witnessed opportunities to intervene, engagement in self-protective behaviors, and engagement in other-protective cybervictimization bystander behaviors. As hypothesized, cybervictimization was associated with witnessing more opportunities to intervene in other's cybervictimization, greater self-reported use of active cyber bystander behaviors, and greater engagement in self-protective strategies. However, the strength of two associations was moderated by age, with stronger relationships between cybervictimization and witnessing opportunities to intervene as well as engaging in bystander behavior for older as compared to younger participants. Contrary to hypothesis, there were no significant associations between use of self and other protective behaviors. Furthermore, greater witnessing of cybervictimization was associated with less engagement in bystander behavior in the final model. The implications for existing bystander intervention programs are described. Longitudinal studies of these associations in multiple age groups and among different cultural groups remain necessary.

Society’s growing reliance on technology to transfer and store private information has created more opportunities for identity thieves to access personal data. Prior work using data from the National Crime Victimization Survey (NCVS) Identity Theft Supplement (ITS) showed that baby boomers were significantly more likely than Millennials to be victims of identity theft and that older people and minorities experience more severe economic and psychological consequences. This study examines how socioeconomic status, demographic characteristics, and incident-specific factors relate to how much money is stolen during identity theft, the likelihood of experiencing out-of-pocket costs, and emotional distress among identity theft victims age 65 and older. Using combined data from the 2014 and 2016 NCVS-ITS, this study examines the correlates of financial and psychological consequences of identity theft among 2,307 victims age 65 and older. Older Black victims are more likely to have greater amounts of money stolen and are more likely feel distressed than older non-Latino white identity theft victims. The most disadvantaged older adults living at or below the federal poverty level are nearly five times as likely to suffer out-of-pocket costs. The length of time information is misused and the hours spent resolving identity theft are significantly associated with emotional distress. More than one-third of older victims experience moderate to severe emotional distress following identity theft, and those who can least afford it suffer out-of-pocket costs. Greater advocacy and psychological support are needed to help older adults recover, in addition to tools to protect their personal information from misuse.

Purpose The purpose of this study is to examine the effect of micro-level place on identity theft victimization. This study uses the 2016 Identity Theft Supplement (ITS) to investigate whether aspects of an individual’s residence affect their likelihood of becoming identity theft victims. Design/methodology/approach The authors conduct logistic regressions of whether a respondent was an identity theft victim in the past year using the following variables as key predictors: number of housing units in a residence, whether the respondent operates a business out of their residence and if residence access is restricted. Findings The results suggest that location influences the likelihood of identity theft to a modest degree though some aspects of location (possibly those related to rewards perceptions) may be more relevant than others. Meanwhile, though location may influence initial target selection, whether someone is victimized may be more dependent on factors such as personal behavior. Originality/value To the best of the authors’ knowledge, this manuscript represents one of the first investigations into the relationship between microlevel place and the incidence of identity theft. Furthermore, it provides evidence that one does exist which bears further inquiry.

Identity theft victims often experience negative financial, emotional, and physical consequences. Many cases of identity theft are perpetrated by family members, yet little is known about consequences familial identity theft victims experience and how they may differ from those who were victimized by a non-relative. The purpose of this study was to examine potential differences in consequences of identity theft victimization among familial and non-familial identity theft victims. Findings indicate younger identity theft victims are more likely to experience feelings of worry and anxiousness due to victimization, relative to older identity theft victims. No differences were found among familial and non-familial identity theft victims regarding physical consequences of victimization, nor were any differences found in the amount of financial losses incurred.

Researchers in criminology and criminal justice have been making increasing use of the machine learning approach to investigate questions involving large amounts of digital data. We make use here of survey data on over 220,000 respondents drawn from three waves of the National Crime Victimization Survey Identity Theft Supplement (NCVS-ITS) conducted by the Bureau of Justice Statistics (BJS) in 2012, 2014, and in 2016. We use three distinct machine learning algorithms to analyze these data: 1) logistic regression; 2) decision tree; and, 3) random forest. We assess the efficacy of these approaches against these evaluative criteria: the overall percentage of correct classification, receiver operating characteristics (ROC), the area under the ROC curve (AUC), and feature criticality. Our findings indicate that the logistic regression algorithm performs best in predicting overall identity theft victimization, misuse of credit cards, misuse of financial accounts of other types, and the opening of new accounts; the random forest algorithm performs best in predicting misuse of checking/saving accounts. Our findings suggest that the respondent’s age, educational level, and online shopping frequency are significantly related to identity theft victimization. Additionally, frequently checking credit reports and changing passwords of financial accounts are strong predictors of identity theft victimization. We draw out the implications of our work for our collective understanding of identity theft, and for informing our judgment as to the potential utility of the use of machine learning approaches in criminology and criminal justice.

Researchers in criminology and criminal justice have been making increasing use of the machine learning approach to investigate questions involving large amounts of digital data. We make use here of survey data on over 220,000 respondents drawn from three waves of the National Crime Victimization Survey Identity Theft Supplement (NCVS-ITS) conducted by the Bureau of Justice Statistics (BJS) in 2012, 2014, and in 2016. We use three distinct machine learning algorithms to analyze these data: 1) logistic regression; 2) decision tree; and, 3) random forest. We assess the efficacy of these approaches against these evaluative criteria: the overall percentage of correct classification, receiver operating characteristics (ROC), the area under the ROC curve (AUC), and feature criticality. Our findings indicate that the logistic regression algorithm performs best in predicting overall identity theft victimization, misuse of credit cards, misuse of financial accounts of other types, and the opening of new accounts; the random forest algorithm performs best in predicting misuse of checking/saving accounts. Our findings suggest that the respondent’s age, educational level, and online shopping frequency are significantly related to identity theft victimization. Additionally, frequently checking credit reports and changing passwords of financial accounts are strong predictors of identity theft victimization. We draw out the implications of our work for our collective understanding of identity theft, and for informing our judgment as to the potential utility of the use of machine learning approaches in criminology and criminal justice.

PurposeFamiliar identity theft, which occurs when an individual known to a victim steals his/her identity, is a common problem in the USA. The purpose of this study was to understand familiar identity theft victims’ reporting behaviors using Black's (1976) theory of law as a conceptual framework.Design/methodology/approachData were obtained from the 2012, 2014, 2016 and 2018 administrations of the National Crime Victimization Survey – Identity Theft Supplement. A series of cross-tabulations were conducted to examine the relationship between reporting behaviors and age, minority, gender, income, marital status and education. Fisher’s exact test was used to interpret the findings.FindingsKey findings include older familiar identity theft victims who personally lost greater sums of money because of identity theft victimization were more likely to report to law enforcement than younger familiar identity theft victims who personally lost less money. Married familiar identity theft victims were less likely to report to law enforcement than those who were not married.Originality/valueThis study extends the work of Golladay (2017) to explore the reporting behaviors of a population of identity theft victims that have been largely overlooked in empirical literature.

IntroductionThis study explored the formation mechanism of consumers’ self-protective behavior during the COVID-19 pandemic, which is very important for policy settings to regulate consumer behavior. Based on the basic framework of the Protective Action Decision Model (PADM), this study analyzed the formation mechanism of consumers’ self-protective willingness from the perspective of risk information, and explained the deviation between consumers’ self-protective willingness and behavior from the perspective of protective behavior attributes.MethodsBased on 1,265 consumer survey data during the COVID-19 pandemic, the empirical test was carried out.Results and DiscussionThe amount of risk information has a significant positive impact on the consumers’ self-protective willingness, where the credibility of risk information plays a positive moderating role between them. Risk perception plays a positive mediating role between the amount of risk information and the consumers’ self-protective willingness, and the positive mediating effect of risk perception is negatively moderated by the credibility of risk information. In the protective behavior attributes, hazard-related attributes play a positive moderating role between the consumers’ self-protective willingness and behavior, while resource-related attributes play the opposite role. Consumers pay more attention to hazard-related attributes than resource-related attributes, and they are willing to consume more resources to reduce risk.

The relationship between receiving phishing attempt and identity theft victimization in South Korea

The law of data breaches is new, dynamic, and evolving. The number and complexity of breaches increases each year and legal scholars, courts, and policymakers scramble to respond. In 2019, 14.4 million consumers became victims of identity theft, the most problematic consequence of data breaches for consumers. Indeed, one-third of all Americans have experienced identity theft at some point in their lives. Yet despite low-income groups comprising at least thirty percent of all identity theft victims, existing discourse and debate on the regulatory regime governing data breaches and identity theft primarily reflects the experiences and concerns of middle- and high-income groups. Debates remain uninformed by detailed analysis of how the use of illegally obtained data may uniquely harm low-income individuals and how these harms may be exacerbated for low-income victims who are Black. We lack careful theoretical assessment of the complex relationship between identity theft victimization and wider structures of inequality. This Article uses original data to fill these significant descriptive, theoretical, and normative gaps in the literature. It then turns toward exploring the common and understudied problem of aligning regulatory regimes with the needs of prototypical higher-income people, leaving those who are low-income to operate within a system that was not designed to help them—what I call plutocentric regulation. Finally, the Article proposes a new federal agency, the Data Privacy and Identity Recovery Agency (DPIRA), to streamline the process for identity theft victims and make the recovery process equitable for all victims, regardless of their income.

Identity theft commonly refers to the illegal theft and misuse of another person’s identity information, resulting in a benefit to the offender or harm to the victim. With the rise of technological payment systems, identity theft increased dramatically in the 1990s and 2000s and impacts almost 1 in 10 adults annually. Identity theft can be difficult to measure, in part because few victims report it to law enforcement and government agencies and because victims often have limited knowledge about how their information was obtained and misused. Identity theft can involve the misuse of existing bank, credit, or other accounts, the creation of new accounts, or other fraudulent misuses of personal information. Moreover, the methods of acquiring identity information vary and include hacking, phishing, and stealing physical documents. While identity theft’s rise results from increasing technological reliance, the relative prevalence of online and offline forms remains unknown. The limited research on identity theft offenders finds that their motives and techniques vary, but that committing identity theft is usually a rational choice and that offenders often use techniques to neutralize identity theft behaviors. More research exists on identity theft victims, due, in part, to identity theft victimization surveys, which find that victims face a range of consequences and reporting options. Globally, both criminal and consumer protection laws have been implemented or modified to respond to identity theft, although victims must typically advocate for themselves to resolve identity theft’s consequences.