Bibliografías temáticas / Online identity theft $x Prevention

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Literatura académica sobre el tema "Online identity theft $x Prevention"

Autor: Grafiati
Publicado: 26 de julio de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Online identity theft $x Prevention"

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D Mitchell, Charles, and Samuel Sambasivam. "Predictive Modeling for Identity Theft Detection: A Design Science Approach Using Machine Learning and Historical Data." Issues in Informing Science and Information Technology 22 (2025): 003. https://doi.org/10.28945/5506.

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Aim/Purpose The proliferation of online banking has led to a significant increase in identity theft and cybercrimes, creating an urgent need to develop more effective predictive models to detect and prevent such fraudulent activities using advanced technological approaches. Background This study addresses the critical gap in the existing literature by exploring how historical identity theft victim data can be leveraged through supervised ma-chine learning to create a comprehensive prediction model for identifying and preventing future identity theft incidents. Methodology A design science quan
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Chohan, Dr Rozina, Engr Murk Chohan, Irfan Mir Chohan, and Farhana Mir Chohan. "Overcoming Trusting Barriers in Inter-organizational Identity Theft Prevention in Knowledge Sharing: A Case of UK Retailing Industry." Revista Gestão Inovação e Tecnologias 11, no. 4 (2021): 4946–74. http://dx.doi.org/10.47059/revistageintec.v11i4.2515.

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Inter-organizational knowledge sharing basically connects two or more firms with one another in exchange relationship for skills, expertise and knowledgeable personnel. Knowledge plays a key role in organizational performance but it is given a very little attention in terms of information security and requires addressing security concerns due to following reasons: First, because retailing is the most victimized channel due to online trade. Second, if organizational criminal wings can compromise the information system of one firm, they can attack other firms too. Hence, identity theft is a coll
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Shah, Mahmood, Abdullah Maitlo, Paul Jones, and Yahaya Yusuf. "An investigation into agile learning processes and knowledge sharing practices to prevent identity theft in the online retail organisations." Journal of Knowledge Management 23, no. 9 (2019): 1857–84. http://dx.doi.org/10.1108/jkm-06-2018-0370.

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Purpose Lack of individual awareness of knowledge sharing practices to prevent identity theft is a significant issue for online retail organisations (OROs). Agile learning processes and sharing of knowledge is essential, but the lack of relevant training inhibits these processes within the online industry. This study aims to identify the inhibiting factors in agile learning and knowledge sharing process with recommendations for best practice for organisations and staff to effectively share knowledge on identity theft prevention. Design/methodology/approach Three qualitative case studies were u
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Amalan Fernando, Ms Rodryl, and Jayesh Shinde. "Strengthening Cybersecurity in Modern Finance: Safeguarding Online Banking and Beyond." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43088.

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The growing use of internet banking has escalated cybersecurity risks, creating problems for both customers and banking institutions. This research investigates the cyber risk scope that covers phishing, malware, identity theft, and data theft. It also considers mobile banking and insider abuse issues while looking at regulatory issues and how new technologies can enhance financial security. In reviewing what is already available, this paper describes key barriers to overcome such as multi-factor authentication (MFA), artificial intelligence (AI) security systems, blockchain-based systems, and
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Malik, Aftab Ahmad. "Online shopping, Cyber frauds and Fraud prevention Strategies." International Journal for Electronic Crime Investigation 8, no. 1 (2024): 49–56. http://dx.doi.org/10.54692/ijeci.2024.0801186.

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Online shopping is increasingly being targeted by hackers and cyber criminals, who exploit the anonymity of the internet to deceive unsuspecting shoppers. These scams involve fake websites or ads, posing as legitimate sellers, damaging innocent citizens' bank accounts and databases, and causing damage to customers. Online shopping fraud involves using stolen credit or debit cards for purchases, while identity theft involves stealing personal information for fraudulent purposes like credit or illegal purchases. We discuss, the safety tips to avoid online shopping scams, using these safety tips
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DeLiema, Marguerite, Lynn Langton, and David Burnes. "Identity Theft Among Older Adults: Risk and Protective Factors." Innovation in Aging 4, Supplement_1 (2020): 31. http://dx.doi.org/10.1093/geroni/igaa057.100.

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Abstract Although financial exploitation and fraud targeting older adults have been the focus of increasing academic attention, research on identity theft among older adults is virtually nonexistent. Identity theft refers to an intentional, unauthorized transfer or use of a person’s identifying information for unlawful purposes (Federal Trade Commission 1998). Society’s growing reliance on technology to transfer and store private information has created increased opportunities for financial predators to access and misuse personal data. Results from the most recent Bureau of Justice Statistics’
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Marit, Alexandru. "Legal framework for combating information fraud and prevention strategies." National Law Journal, no. 1(251) (December 2024): 78–91. https://doi.org/10.52388/1811-0770.2024.1(251).08.

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Computers crimes are a relatively new and specific type of crime, their research requires the development of new methods, the use of forensic tactics specific to this type of crime. In the literature we find several strategies developed by doctrinaires, several tactical-methodical recommendations to be met by prosecuting officers, and the specifics of digital evidence. In turn, cybercrime represents various criminal activities that involve computers and computer systems either as a main tool or as a main target. These activities include: classic crimes (such as fraud, forgery and identity thef
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Sharma, Manju. "Cyber Bullying Prevention in Learning Institutions: Systematic Approach." International Journal of Engineering and Computer Science 13, no. 09 (2024): 26455–58. http://dx.doi.org/10.18535/ijecs/v13i09.4898.

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Cyberbullying has been identified as a biggest problem for the last decade. In this paper we will discuss some recent findings and focus on general concepts within the area. This paper covers issues like repetition and power imbalance, types of cyberbullying, age, cyberbullying and traditional bullying, motives for and impact of cyber victimization, coping strategies, and prevention/intervention possibilities. Understanding the characteristics and methods of typical cybercrimes can help us better arm ourselves with the information and resources needed to reduce risks, improve cyber-security, a
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Hole, Prof K. R. "Fraud Detection and Prevention in E-commerce using Decision Tree Algorithm." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 2187–96. http://dx.doi.org/10.22214/ijraset.2024.60307.

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Abstract: Fraud detection is an important part of e-commerce because it helps prevent fraud such as illegal transactions, identity theft, and money laundering. Recently, there has been a lot of literature on the application of machine learning algorithms to identify e-commerce fraud. These algorithms work by learning patterns in data that indicate fraud. Pattern checking deals with discovering differences in data, such as unusual products, locations, or behavior outside the norm for certain users, through machine learning. In this project, we propose a decision tree algorithm to detect fraud i
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Kartheek Dokka1 and Dr. Tushar Mehrotra. "AI-Powered Fintech Solutions for Travel: Combating Identity and Payment Fraud." Universal Research Reports 12, no. 1 (2025): 228–45. https://doi.org/10.36676/urr.v12.i1.1476.

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The tourism industry has witnessed a huge rise in online payments, which, in turn, has left it vulnerable to payment fraud and identity theft. Despite the widespread application of traditional fraud detection systems, including rule-based systems, these systems are likely to struggle to keep up with the ever-evolving fraudsters' tactics. Financial technology-based fraud prevention mechanisms using Artificial Intelligence (AI) have been an effective means of overcoming such limitations. AI techniques, including machine learning, deep learning, behavioral analytics, and biometric authentication,
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Tesis sobre el tema "Online identity theft $x Prevention"

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Abdullah. "Knowledge sharing processes for identity theft prevention within online retail organisations." Thesis, University of Central Lancashire, 2017. http://clok.uclan.ac.uk/23998/.

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The occurrence of identity theft has increased dramatically in recent times, becoming one of the fastest-growing crimes in the world. Major challenges associated with identity theft related offences include problems of consumers with credit, such as: aggravation by debt collectors; rejection of loans; disturbance in normal lives such as reputation damage; and the psychological disruption of providing personal data to organisations and banks during the investigation. For these reasons, and with the ready access of identity thieves to the retail industry, this problem is acute in the online reta
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2

Okeke, Romanus Izuchukwu. "The prevention of internal identity theft-related crimes : a case study research of the UK online retail companies." Thesis, University of Central Lancashire, 2015. http://clok.uclan.ac.uk/12124/.

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Ranked the third biggest cyber security threats of 2013 by Forbes, Internal Identity Theft-Related Crimes (IIDTRC) leave countless victims in their wake, including online retail companies and consumers. With the rapid growth in the use of credit and debit cards in e-commerce, the online retail has been a key target for the IIDTRC perpetrators. IIDTRC involve the misuse of information systems (IS) by the dishonest employees to steal victims’ personal identifiable data. The crimes pose significant socio-economic impact and data security risks. In the context of online retail, relatively little r
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Utakrit, Nattakant. "Security awareness by online banking users in Western Australian of phishing attacks." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2012. https://ro.ecu.edu.au/theses/503.

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Phishing involves sending e-mails pretending to be from the legitimate financial institutions to recipients and asking for personal information such as username and password. It also redirects network traffic to malicious sites, deny network traffic to web services, and modify protection mechanisms in the targeted computer systems. Consequences of successful attacks can include identity and financial losses, and unauthorised information disclosure. The purpose of this study was to investigate the experiences of Western Australian bank users in using online banking. The study considered the rel
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4

Abdelhalim, Amany. "New method for learning decision trees from rules and its illustration for online identity application fraud detection." Thesis, 2009. http://hdl.handle.net/1828/3084.

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A decision tree is a graph or model for representing all the alternatives in a decision making process. Most of the methods that generate decision trees for a specific problem use examples of data instances in the decision tree generation process. We propose a new method called "RBDT-1"- rule based decision tree -for learning a decision tree from a set of decision rules that cover the data instances. RBDT-l method uses a set of declarative rules as an input for generating a decision tree. The method's goal is to create on-demand a short and accurate decision tree from a stable or dynamically c
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Libros sobre el tema "Online identity theft $x Prevention"

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Daybell, Jeremiah S. The delete button will not save you. National University, 2013.

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Organisation for Economic Co-operation and Development., ed. Online identity theft. OECD, 2009.

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Organisation for Economic Co-operation and Development., ed. Online identity theft. OECD, 2009.

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Organisation for Economic Co-operation and Development., ed. Online identity theft. OECD, 2009.

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5

Kiesbye, Stefan. Identity theft. Greenhaven Press, 2011.

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Kiesbye, Stefan. Identity theft. Greenhaven Press, 2011.

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7

Moore, Alexis. Cyber self-defense: Expert advice to avoid online predators, identity theft, and cyberbullying. Lyons Press, 2014.

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8

Boyer, Allison. The Online Identity Theft Prevention Kit: Stop Scammers, Hackers, and Identity Thieves from Ruining Your Life. Atlantic Publishing Company (FL), 2008.

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The online identity theft prevention kit: Stop scammers, hackers, and identity thieves from ruining your life. Atlantic Pub. Group, 2008.

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author, Payton Theresa 1966, ed. Protecting your internet identity: Are you naked online? Rowman & Littlefield, 2017.

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Capítulos de libros sobre el tema "Online identity theft $x Prevention"

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"Appendix A: Protecting Yourself from Identity Theft." In Essentials of Online Payment Security and Fraud Prevention. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118386750.app1.

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Katkar, Kanya J., Monica Anna Fernandes, Falak Prajapati, Kiran R. Dodiya, Akash Khunt, and Divya Patel. "Cyber Security for Preserving Mental Wellness and Preventing Abuse." In Exploiting Machine Learning for Robust Security. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7758-1.ch013.

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This chapter examines the crucial intersection of cybersecurity and mental wellness in today's digital world. It explores how cybersecurity practices can protect cognitive health and prevent abuse, addressing issues like cyberbullying, harassment, stalking, identity theft, and data breaches—all of which affect mental health. Through research and case studies, it stresses the importance of digital literacy, mental health awareness, and safe online behavior. A collaborative model is proposed, involving mental health professionals, technologists, educators, and cybersecurity experts, to create se
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Pereira, Filipa da Silva, Marlene Alexandra Veloso de Matos, and Álvaro Miguel do Céu Gramaxo Olivei Sampaio. "Cyber-Crimes against Adolescents." In Advances in Digital Crime, Forensics, and Cyber Terrorism. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6324-4.ch014.

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At young ages there is an increase in reports of intimidation, harassment, intrusion, fear, and violence experienced through Information Technologies (IT). Hacking, spamming, identity theft, child pornography, cyber bullying, and cyber stalking are just few examples of cyber-crimes. This chapter aims to contribute, from a psychological and design perspective, to an integrative viewpoint about this complex field of cyber-crime. In this chapter, the most common types of cyber-crimes, epidemiological data, and the profiles of cyber victims and aggressors' are approached. The studies that identify
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Actas de conferencias sobre el tema "Online identity theft $x Prevention"

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D Mitchell, Charles, and Samuel Sambasivam. "Predictive Modeling for Identity Theft Detection: A Design Science Approach Using Machine Learning and Historical Data." In InSITE 2025: Informing Science + IT Education Conferences: Hiroshima. Informing Science Institute, 2025. https://doi.org/10.28945/5528.

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Aim/Purpose The proliferation of online banking has led to a significant increase in identity theft and cybercrimes, creating an urgent need to develop more effective predictive models to detect and prevent such fraudulent activities using advanced technological approaches. Background This study addresses the critical gap in the existing literature by exploring how historical identity theft victim data can be leveraged through supervised ma-chine learning to create a comprehensive prediction model for identifying and preventing future identity theft incidents. Methodology A design science quan
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