Browsing by Subject "Identity theft"

Now showing 1 - 5 of 5

Essays on digital and physical channels and mitigation mechanisms of identity frauds
(2021-08-13) Qian, Junjie; Tanriverdi, Hüseyin; Agarwal, Ashish; Jarvenpaa, Sirkka L; Barber, Suzanne
This dissertation includes two essays on identity theft. we developed a modified routine activity theory (RAT) in the first essay to explain the channels of identity frauds occurrence. This study aims to understand the antecedents of identity theft victimization at the individual level, which is important for the law enforcement agency to understand how identity theft occur and design effective deterrence measures. Different from existing studies that examine the antecedents of identity theft using the online proximity approach, we propose the novel concept of recognitive proximity. Recognitive proximity measures how closely a criminal impersonates a victim’s identity by exploiting personal information in four identity dimensions, including symbolic representation, personal identity, role identity and social identity. We hypothesize that online proximity and physical proximity created by individual and organizational leakage of personal information in both digital and physical channels may result in different levels of recognitive proximity, thus generating distinct influence on the risk of identity fraud victimizations. We test our hypotheses using a representative sample of 12,376 U.S. citizens. Our hypotheses are supported by the empirical results. In the second essay, we develop a theory to explain whether, how, and when individuals can protect themselves against the heightened identity theft (IDT) risks following a data breach. We conceptualize IDT as a multi-stage process where criminals first unlawfully obtain a person’s identifying information (PII) through a data breach, then misuse the PII to assume the identity of the person, and ultimately, imposter as the person to commit the IDT crime. We distinguish if the person’s PII leaks to criminals through a personal data breach or an organizational data breach. We hypothesize that preventive protections can reduce the PII leakage through personal data breaches but they can increase the PII leakage through organizational data breaches. We further hypothesize that detective protections can mitigate the heightened IDT risks following a data breach. Finally, we hypothesize that proactive protections are likely to be more effective than reactive protections in reducing IDT. We find support for these ideas in a representative sample of 66,224 citizens in the U.S.A.
Essays on the role of institutions with persistent asymmetric information and imperfect commitment
(2008-05) Mishra, Shreemoy, 1977-; Wiseman, Thomas E., 1974-
This dissertation is a collection of three essays that study the market for consumer information. The first chapter studies the role of information intermediaries and their impact on consumer privacy. The second chapter presents an analysis of signaling in credit and insurance markets through default and repayment decisions. The third chapter studies some special topics such the manipulation of credit histories by fake borrowing or deletion of records. It also identifies a learning mechanism through which uninformed consumers can endogenously learn the link between credit market behavior and insurance market outcomes.
Mining of identity theft stories to model and assess identity threat behaviors
(2014-05) Yang, Yongpeng; Barber, Suzanne
Identity theft is an ever-present and ever-growing issue in our society. Identity theft, fraud and abuse are present and growing in every market sector. The data available to describe how these identity crimes are conducted and the consequences for victims is often recorded in stories and reports by the news press, fraud examiners and law enforcement. To translate and analyze these stories in this very unstructured format, this thesis first discusses the collection of identity theft data automatically using text mining techniques from the online news stories and reports on the topic of identity theft. The collected data are used to enrich the ITAP (Identity Threat Assessment and Prediction) Project repository under development at the Center for Identity at The University of Texas. Moreover, this thesis shows the statistics of common behaviors and resources used by identity thieves and fraudsters — identity attributes used to identify people, resources employed to conduct the identity crime, and patterns of identity criminal behavior. Analysis of these results should help researchers to better understand identity threat behaviors, offer people early warning signs and thwart future identity theft crimes.
NewsFerret : supporting identity risk identification and analysis through text mining of news stories
(2013-05) Golden, Ryan Christian; Barber, Suzanne
Individuals, organizations, and devices are now interconnected to an unprecedented degree. This has forced identity risk analysts to redefine what “identity” means in such a context, and to explore new techniques for analyzing an ever expanding threat context. Major hurdles to modeling in this field include the inherent lack of publicly available data due to privacy and safety concerns, as well as the unstructured nature of incident reports. To address this, this report develops a system for strengthening an identity risk model using the text mining of news stories. The system—called NewsFerret—collects and analyzes news stories on the topic of identity theft, establishes semantic relatedness measures between identity concept pairs, and supports analysis of those measures through reports, visualizations, and relevant news stories. Evaluating the resulting analytical models shows where the system is effective in assisting the risk analyst to expand and validate identity risk models.
One step ahead, not two steps behind: the fight to protect our identities
(2014-05) Brenner, Jennifer Tatiana; Barber, K. Suzanne
This thesis reviews different types of identity theft and conducts and in-depth review of the threats to our personally identifiable information (PII). There has been an alarming increase in the availability of industry applications that aggregate our PII with the promise of convenience. This paper deeply explores three data aggregators: Google Mobile Wallet, COIN and PayPal Beacon, to understand what they are, potential security implications and how widespread data aggregation may alter the identity landscape as a whole. Discussion of common technologies leveraged by these data aggregators help illustrate the vulnerability of the data consumers are willingly sharing. In an attempt to better understand the crimes that steal and fraudulently use PII, this thesis introduces the ITAP, the Identity Theft Assessment and Prediction tool to illustrate why it is important to study theft and fraud as a business process. The paper presents a small, independent study conducted to emphasize the validly of both the business process ideology and usefulness of the results. Closing thoughts are presented to speculate what the future of identity could look like and how consumers may need to use the information gathered from tools such as the ITAP to shape best practices. The goal is to be two steps ahead instead of one step behind.