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Identity theft

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


Papers
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Proceedings ArticleDOI
03 Jul 2020
TL;DR: Considering the importance of healthcare data, the use of blockchain technology can be promising to maintain the security, privacy, immutability, authentication, and reliability of the data to the intended users.
Abstract: Medical data contains sensitive information and can have big impact if stolen. The term medical identity theft is coined for such thefts. Medical records are collected from various sources like hospitals, diagnostic labs, physicians, pharmacy and health insurance companies and includes all details of patient including his demographic information, test reports like X – rays, CT scans, MRIs, etc. With the advent of digitization, these medical records are now stored in digital form to make access and sharing easier. However, storing and sharing these data electronically opens the threat of data theft and misuse. Health insurance companies often bear the brunt of fraudulent claims based on stolen medical data. So, the current need is to enable storing and sharing these data with security and make a prohibition on making copies of such data. Hence, considering the importance of healthcare data, the use of blockchain technology can be promising to maintain the security, privacy, immutability, authentication, and reliability of the data to the intended users. The aim of this paper is to investigate the current state of blockchain technology and its diverse applications. The paper also discusses the application of the blockchain technology in the domain of secure medical health record sharing.
Book ChapterDOI
06 Feb 2019
TL;DR: The paper proposes the hospital user awareness and user acceptance framework for multimodal access control in the medical information systems and shows that 76.7% of users lack knowledge in the security of information and that there is a lack of security awareness education and training in the hospital.
Abstract: Lack of user awareness and user acceptance of the importance of practising a good access-control approach, particularly in the healthcare sector of South Africa, is a challenging issue in the area of the security of information. The challenge results in breaches to information stored in medical information systems, fraud, and medical identity theft. The paper proposes the hospital user awareness and user acceptance framework for multimodal access control in the medical information systems. The survey results from participants in Charlotte Maxeke Academic hospital, based in Johannesburg showed a response rate of 86%. Focusing on the objectives of the study the results showed that 76.7% of users’ lack knowledge in the security of information and that there is a lack of security awareness education and training in the hospital. The results of the study are presented and analysed through IBM SPSS statistical software that is used for data analysis.
Journal ArticleDOI
TL;DR: In this paper , the isolation forest technique is used to classify data sets acquired from professional survey firms in order to detect fraud activities, and the results are quite accurate, however, it is difficult to track down a con artist who used a phone identity sim or made the call that utilized an internet provider.
Abstract: Abstract: The usage of internet banking and credit cards is growing at an exponential rate. As more people use credit cards, online banking, and debit cards, the probability of becoming a victim of fraud of various kinds also increases. In recent times, there have been a number of instances in which users of credit card companies have, as a result of a lack of understanding, given their card information, personal information, and one-time password to an unidentified fraudulent caller. As a direct consequence of this, fraudulent activity will occur on the account. Fraud is a problem for the same reason that it is tough to track down a con artist who used a phone identity sim or made the call that utilized an internet provider: it is difficult to find them. Therefore, in order to detect fraudulent activity, this research makes use of supervised methodologies and algorithms, and the results are quite accurate. Customers lose trust in an organization when it engages in activities that are fraudulent or illegal, which in turn has a huge negative impact on the organization. Additionally, it has an effect on the total income and turnover of the company. The isolation forest technique is used in this study to classify data sets acquired from professional survey firms in order to detect fraud activities.
Journal ArticleDOI
TL;DR: This project will discuss how the Naive Bayes machine learning algorithm is applied on data sets and how it has been selected for the email spam detection with the best precision and accuracy.
Abstract: Nowadays, Email spam is a major problem, with the increase usage of internet for product promotions, e-banking, e-loans, health related articles, movie news etc to users. Besides the people are practicing unwanted and unethical conduct as in phishing and mailing fraudulent information. Sending suspicious links through spam emails can harm our system and can also be sought after our system. Creating a fake user identity and email account is such easy for spammers. They pretend like a genuine entity in their spam emails and target those people who are not aware of these frauds. So, it is essential to identify those spam emails which are fraud. In this proposed work, we have applied machine learning algorithm to identify whether the incoming mail is spam or ham. This project will discuss how the Naive Bayes machine learning algorithm is applied on our data sets and how it has been selected for the email spam detection with the best precision and accuracy
Journal ArticleDOI
TL;DR: In this paper , the authors employ multilevel modeling on a sample of EU citizens (n = 26,735) to analyze the issues of fraud experiences among older generations in digital society.
Abstract: The European population is aging, which means more people aged sixty-five and over are at risk of financial exploitation. However, there is a lack of consensus regarding whether older persons are at greater risk of fraud than younger counterparts due to physical, economic, and social factors or, rather, whether they are slightly protected from fraud in the digital era due to less frequent online activity. Moreover, little is known about the financial, emotional, psychological, and physical impacts of fraud experiences amongst older generations in digital society. We employ multilevel modelling on a sample of EU citizens (n = 26,735) to analyze these issues. The results show that, holding other factors constant, older adults are more likely to suffer fraud in general, but not fraud via online channels. Identity theft in which the offender attempts to trick the victim by impersonating a reputable organization is found to be particularly relevant for citizens aged sixty-five and above. Older persons are less likely to suffer a financial impact but more likely to experience anger, irritation, embarrassment, and negative impacts on their physical health from fraud in general as well as from online fraud. Many organizations aim to help protect older adults from financial crime and its impacts; thus, the results emphasize the need to understand particular fraud categories suffered by older generations and to design support programs that fully take into account the non-financial impacts of this crime.

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202384
2022165
202178
2020107
2019108
2018112