Identity theft

About: Identity theft is a research topic. Over the lifetime, 2284 publications have been published within this topic receiving 31700 citations.

Juvenile Hybrid White-Collar Delinquency: An Empirical Examination of Various Frauds

Abstract: With recent technological advances, juveniles now have more opportunities to engage in certain types of hybrid white-collar crime such as credit card fraud, identity theft, general fraud, intellectual property crimes, and financial/bank fraud, yet they are largely ignored in white-collar crime research due to offender- and opportunity-based definitions of the phenomenon. Using data from the Florida Department of Juvenile Justice, the current paper examines various aspects of this recently acknowledged variety of offending behavior among juveniles. Results indicate that significant differences exist between hybrid white-collar delinquents and conventional crime delinquents in various factors identified in the literature relating to deviant/criminal behavior. Theoretical implications and future research directions are also discussed.

Internet: An Overview of Six Key Policy Issues Affecting Its Use and Growth

Abstract: This report summarizes six key issues that could affect the growth and use of the Internet from a technology policy perspective: encryption and digital signatures; computer security; computer privacy (including consumer identity theft, protecting children from unsuitable material, and privacy of information in government databases), intellectual property rights, unsolicited electronic mail (“junk e-mail” or “spamming”), and Internet domain names. Identification of related legislation and other CRS reports that provide more detail on the issues is included. This report will be updated if necessary. Internet: An Overview of Six Key Policy Issues Affecting Its Use and Growth

PHISHING WEBSITE DETECTION SYSTEM BASED ON ENHANCED iTREE CLASSIFIER

Abstract: Nowadays, a lot of attacks have cropped up for phishing of emails and password of users. In order to get one’s confidential information like passwords, bank details such as debit or credit card numbers illegally, phishing act can be done. For doing an identity theft or financial gain or some fraudulent activities, an individual or group of persons gets confidential information from unsuspecting victims via email. This study proposes data mining techniques to classify phishing data’s and then attempts to rectify phishing. A decision classifier tree model is used for detecting phishing datasets and another hybrid session based model is also developed to escape from such phishing attacks. The use of the session based unique password is scrutinized to protect the privacy of the users which is not revealed by attacks or infected systems. The proposed model generates a novel minimum spanning tree called iTree which takes only a minimum time to construct it. The proposed iTree model classifies the inputs which are resistant to a number of phishing attacks and is also resilient to keyboard logging as well, thus ensuring reliability. The tree classifier model will be able to identify any types of attacks in the future. The proposed models of session based authentication and data mining based decision tree classification are much more accurate in the usage of the antiphishing than the existing method.

An Empirical Assessment of Senior Citizens’ Cybersecurity Awareness, Computer Self-Efficacy, Perceived Risk of Identity Theft, Attitude, and Motivation to Acquire Cybersecurity Skills

Abstract: ii Acknowledgements iv Dedication vi List of Tables x List of Figures xi