Relevant bibliographies by topics / Online frauds

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Online frauds'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Online frauds"

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Dhanwani, Prof D. C. "Online Fraud Detection System." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 294–99. http://dx.doi.org/10.22214/ijraset.2024.59557.

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Abstract: Financial services are used everywhere and function with high complexity. With the increase in online transacting, frauds too are increasing alarmingly. An automated Fraud Detection System is thus required. With millions of transactions taking place, it is practically impossible to detect frauds manually with good speed and accuracy. We propose a system is that provides a robust, cost effective, efficient yet accurate solution to detect frauds in both online payment transactions and credit card payments. The proposed solution is a Machine Learning model that will serve the purpose of
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Banu, Muskan, and Prof Kavitha G. "Credit Card Fraud Detection Using Machine Learning Algorithms." International Journal for Research in Applied Science and Engineering Technology 10, no. 10 (2022): 1018–23. http://dx.doi.org/10.22214/ijraset.2022.47127.

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Abstract: Credit Card Fraud can be defined as a case where a person uses someone else’s credit card for personal reasons while the owner and the card-issuing authorities are unawareof the fact that the card is being used. Credit card frauds are easy and friendly targets. E-commerce and many other online sites have increased the online payment modes, increasing the risk for online frauds. In the era of digitalization, the need to identify credit card frauds is necessary. Fraud detection involves monitoring and analyzing the behaviour of various users to estimate, detect or avoid undesirable beh
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Gunjan, Sahoo, Manjula V. Dr, Anuradha Bhakta K, S. A. Poojashree, and D. Shenoy Divya. "Fraud Detection in Online Transaction." Journal of Network Security and Data Mining 3, no. 2 (2020): 1–8. https://doi.org/10.5281/zenodo.3989160.

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<em>Credit card fraud ranges from larceny and fraud committed involving a payment card, like a credit card or debit card, as a deceitful supply of funds during the payments. The aim may also be to get merchandise by not paying and also getting unauthorized funds from an account. These frauds are also an adjunct to identity theft. Though incidences of credit card fraud are restricted to about 0.1% of all card transactions, they have resulted in financial loss as the transactions have been large sum. In this present digital era there is increased demand for a secure online transaction and there
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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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Amos Kipngetich. "A review of online scams and financial frauds in the digital age." GSC Advanced Research and Reviews 22, no. 1 (2025): 302–29. https://doi.org/10.30574/gscarr.2025.22.1.0025.

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The rapid proliferation of digital technologies has revolutionized the global economy and transformed how individuals and businesses interact. However, this digital transformation has also given rise to a surge in online scams and financial frauds, posing significant threats to individuals, organizations, and financial institutions. This review paper explores the evolving landscape of online scams and financial frauds in the digital age, focusing on prevalent schemes such as phishing, identity theft, online payment fraud, cryptocurrency-related scams, and social engineering attacks. It examine
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G, Kavyasri, Keerthana D, Keerthi Reddy B, Keerthi K, KesavaAditya J, and Prof S. Ramesh Kumar. "Deep Learning based Credit Card Fraudulency Detection System." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 477–81. http://dx.doi.org/10.22214/ijraset.2024.61553.

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Abstract: Huge increase in the internet usage has been observed since last decade. It led to the emergence of services like ecommerce, tap and pay systems, online bill payment systems, etc. have proliferated and become more widely used. Due to various online payment options introduced by e- commerce and other numerous websites, the possibility of online fraud has risen drastically. Thus, due to an increase in fraud rates, research on analyzing and detecting fraud in online transactions has begun utilizing various machine learning techniques. The Deep Learning techniques viz., Convolutional Neu
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Ravi, S., J. Thanga Kumar, Dr Linda Joseph, Sumanth Raju Kunjeti, Nandu Vardhan Saniboina, and Sandeel Reddy Endela. "An Unique Methodology for Credit Card Fraud Detection based on Convolutional Neural Network." Alinteri Journal of Agriculture Sciences 36, no. 1 (2021): 277–80. http://dx.doi.org/10.47059/alinteri/v36i1/ajas21041.

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Internet based business, e-Services and numerous other web-based application have expanded the online payment modes, expanding the danger for online frauds. Expansion in fraud rates, analysts began utilizing distinctive machine learning strategies to identify and dissect frauds in online exchanges. The principle point of the paper is to plan and build up a novel fraud identification strategy for Streaming Transaction Data, with a target, to dissect the previous exchange subtleties of the clients and concentrate the personal conduct standards. This paper proposes a canny model for detecting fra
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N.A., Padmalatha. "E-Commerce Fraud Detection Tools." Shanlax International Journal of Management 7, S1 (2020): 24–32. https://doi.org/10.5281/zenodo.3737716.

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India is a cash based society. However, as per the reports of NASSCOM, India&nbsp; is expected to have Internet users base of about 730 million by the end of 2020.&nbsp; It has been noted that by 2020, Indian e-commerce industry is expected to reach $34 billion, with 200 million individuals transacting online, growing 3X over 2015. This spread of e-Commerce has led to the rise of several niche players who largely specialize their products around a specific theme including fraud detection tools. Experts predict online credit card fraud to increase to $32 billion by 2020. In order to combat tech
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Samidha, Samidha Walvekar. "Impact of Banking Fraud Awareness Booklet Among The Students of Satara." Mobile and Forensics 5, no. 2 (2023): 15–20. http://dx.doi.org/10.12928/mf.v5i2.7881.

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With the growth of information and communication technology, the structure and nature of financial services delivery has also changed. Online banking or internet banking has emerged as a new and convenient way for using financial services like funds transfer, viewing account statement, bill payment, use of e-wallets etc. An upsurge in the use of devices connected with the internet and the convenience of online financial services has increased the risk of our hard-earned money being duped by cybercriminals.&#x0D; The main aim of this study is to assess the impact of Banking fraud awareness Book
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Mr., Anurag Anil Ratnaparkhi, Neha Rakeshchandra Vishwakarma Ms., and Dr. Vijaykumar G. Wawle Prof. "A Study of Online Banking Scams / Frauds In India." Young Researcher S14, no. 1B (2025): 238–44. https://doi.org/10.5281/zenodo.14873742.

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<em>India has adopted the policy of digitalization in 2016. Since that the number of online bank frauds have grown with much higher rate. Especially the frauds like phishing, vishing, ATM frauds etc. The research asserts that such frauds in public sector banks are much higher than that of the private sector banks. The research has shown that even if the number of fraud is decreasing in both private and public sector banks; the amount of scams is much higher in the public sector bank than that of the private sector banks.</em> <em>F</em><em>raudulent activity has generally decreased across publ
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Dissertations / Theses on the topic "Online frauds"

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Åkerberg, Mathias, and Anders Tibbling. "Säker identitetshantering på internet : Att minimera bedrägerier och öka konsumentens säkerhet och inflytande vid e-handel." Thesis, KTH, Data- och elektroteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169434.

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Risken att en obehörig part kan komma över och använda en enskild konsuments identitets-handlingar är stor, samtidigt som individens möjlighet att kontrollera hur och när dess iden-titet används är liten. Problemformuleringen som skulle besvaras var hur identitetsstölder och bedrägerier på internet kunde minimeras samtidigt som konsumenten får ett ökat infly-tande över hanteringen av sin identitet. Målsättningen var att centralisera och skapa ett gemensamt förhållningssätt för identitets-hantering på internet till förmån för konsumenterna, och på så vis minimera spridning av egna lösningar för
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Alanezi, Faisal. "Perceptions of online fraud and the impact on the countermeasures for the control of online fraud in Saudi Arabian financial institutions." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12003.

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This study addresses the impact of countermeasures in the control and prevention of online fraud in Saudi Arabia and the influence of the environmental context. Combatting online fraud is facilitated when the public is fully educated and is aware of its types and of the prevention methods available. People are reliant on the Internet; the possibility of being breached by hackers and fraudsters is growing, especially as socialising, online shopping and banking are carried out through personal computers or mobile devices. Online fraud has been described as an epidemic that has spread to most onl
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Kävrestad, Joakim. "DEFINING, CATEGORIZING AND DEFENDING AGAINST ONLINE FRAUD." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9732.

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Frauds conducted online are crimes that are and has been increasing in numbers over the last years. Government reports shows that this is the case in Sweden as well as internationally. As of today the Swedish legal systems lacks a definition and categorization approach for online frauds. This thesis aims at developing such definition and a classification scheme that can be used to classify online frauds. Further, this thesis suggests and evaluates a defense mechanism for use in arenas were online frauds are executed. The results bring a definition and classification scheme that has been develo
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Rahman, Md Mizanur. "Search Rank Fraud Prevention in Online Systems." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3909.

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The survival of products in online services such as Google Play, Yelp, Facebook and Amazon, is contingent on their search rank. This, along with the social impact of such services, has also turned them into a lucrative medium for fraudulently influencing public opinion. Motivated by the need to aggressively promote products, communities that specialize in social network fraud (e.g., fake opinions and reviews, likes, followers, app installs) have emerged, to create a black market for fraudulent search optimization. Fraudulent product developers exploit these communities to hire teams of workers
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Eduardo, Ana Teresa Caldinhas. "Internet banking em Portugal: evolução e implicações de uma inovação radical." Master's thesis, Universidade de Évora, 2013. http://hdl.handle.net/10174/16091.

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A internet banking é uma importante inovação que surgiu no setor financeiro e que permite efetuar a maioria das operações bancárias através de uma plataforma ligada à internet, em qualquer lugar e a qualquer hora. Esta dissertação aborda a introdução e evolução da internet banking em Portugal, uma das inovações mais importantes do século XX no setor bancário, que transformou o modelo de negócio e a forma como os bancos interagem com os seus clientes. A sua análise empírica é feita por via da entrevista direta com algumas das principais instituições bancárias portuguesas. As principais conclusõ
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Aspvik, Daniel Weenås, and Preben Weenås Aspvik. "Contemporary Online Banking Fraud in Norway : A case study." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97710.

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Banks are currently battling rising of fraudulent activities as it damages their relationship with their customers. Online banking fraud is decreasing trust and confidence among the customers and decreasing operating performance and increasing cost for the banks. This paper looks at online banking fraud in Norway and answers the research questions (1). How are bank customers attacked through the internet? and (2). How are banks trying to prevent fraudulent attacks against their customers? Interviews and document collection were used for data gathering, and in total, four interviews were conduc
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Amaya, de la Pena Ignacio. "Fraud detection in online payments using Spark ML." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219916.

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Frauds in online payments cause billions of dollars in losses every year. To reduce them, traditional fraud detection systems can be enhanced with the latest advances in machine learning, which usually require distributed computing frameworks to handle the big size of the available data. Previous academic work has failed to address fraud detection in real-world environments. To fill this gap, this thesis focuses on building a fraud detection classifier on Spark ML using real-world payment data. Class imbalance and non-stationarity reduced the performance of our models, so experiments to tackle
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Maruatona, Omaru. "Internet banking fraud detection using prudent analysis." Thesis, University of Ballarat, 2013. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/59631.

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The threat posed by cybercrime to individuals, banks and other online financial service providers is real and serious. Through phishing, unsuspecting victims’ Internet banking usernames and passwords are stolen and their accounts robbed. In addressing this issue, commercial banks and other financial institutions use a generically similar approach in their Internet banking fraud detection systems. This common approach involves the use of a rule-based system combined with an Artificial Neural Network (ANN). The approach used by commercial banks has limitations that affect their efficiency in cur
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Dan, Gorton. "Aspects of Modeling Fraud Prevention of Online Financial Services." Doctoral thesis, KTH, Transportvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-176298.

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Banking and online financial services are part of our critical infrastructure. As such, they comprise an Achilles heel in society and need to be protected accordingly. The last ten years have seen a steady shift from traditional show-off hacking towards cybercrime with great economic consequences for society. The different threats against online services are getting worse, and risk management with respect to denial-of-service attacks, phishing, and banking Trojans is now part of the agenda of most financial institutions. This trend is overseen by responsible authorities who step up their minim
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Haq, Ikram. "Fraud detection for online banking for scalable and distributed data." Thesis, Federation University Australia, 2020. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171977.

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Online fraud causes billions of dollars in losses for banks. Therefore, online banking fraud detection is an important field of study. However, there are many challenges in conducting research in fraud detection. One of the constraints is due to unavailability of bank datasets for research or the required characteristics of the attributes of the data are not available. Numeric data usually provides better performance for machine learning algorithms. Most transaction data however have categorical, or nominal features as well. Moreover, some platforms such as Apache Spark only recognizes numeric
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Books on the topic "Online frauds"

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Zhu, Xingquan, Haicheng Tao, Zhiang Wu, Jie Cao, Kristopher Kalish, and Jeremy Kayne. Fraud Prevention in Online Digital Advertising. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56793-8.

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Zhu, Xingquan. Fraud Prevention in Online Digital Advertising. Springer International Publishing, 2017.

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Cole, Liz. Perfect prey: Surviving a cyber shark's romantic fraud. Manor House Pub., 2009.

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Shea, Therese. Avoiding online hoaxes. Gareth Stevens Pub., 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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Montague, David. Essentials of Online Payment Security and Fraud Prevention. John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9781118386750.

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Montague, David A. Essentials of online payment security and fraud prevention. Wiley, 2010.

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Shea, Therese. Avoiding online hoaxes. Gareth Stevens Pub., 2013.

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Book chapters on the topic "Online frauds"

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Sood, Raunak, Anurag Sood, Shilpi Sood, and Shubham Gajanan Kawalkar. "Preventing Online Financial Frauds." In AI and Emerging Technologies. CRC Press, 2024. http://dx.doi.org/10.1201/9781003501152-5.

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Zhang, Qinglei, and Wenying Feng. "Detecting Coalition Frauds in Online-Advertising." In Mathematical and Computational Approaches in Advancing Modern Science and Engineering. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30379-6_54.

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Mittal, Sanjay, Rahul Gupta, Mukesh Mohania, Shyam K. Gupta, Mizuho Iwaihara, and Tharam Dillon. "Detecting Frauds in Online Advertising Systems." In E-Commerce and Web Technologies. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11823865_23.

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Apte, Manoj, Girish Keshav Palshikar, and Sriram Baskaran. "Frauds in Online Social Networks: A Review." In Lecture Notes in Social Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78256-0_1.

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Bharne, Smita, and Pawan Bhaladhare. "Comprehensive Analysis of Online Social Network Frauds." In Advances in Data-Driven Computing and Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3250-4_3.

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Whittaker, Jack Mark, Matthew Edwards, Cassandra Cross, and Mark Button. "Open Access: “I Have Only Checked after the Event”: Consumer Approaches to Safe Online Shopping." In Scams, Cons, Frauds, and Deceptions. Routledge, 2024. http://dx.doi.org/10.4324/9781003474982-5.

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Srivastav, Anurag, and Laxmi Ahuja. "An Exhaustive Review on Detecting Online Click-Ad Frauds." In Innovations in Computer Science and Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2043-3_27.

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Sadaoui, Samira, Xuegang Wang, and Dongzhi Qi. "A Real-Time Monitoring Framework for Online Auctions Frauds." In Current Approaches in Applied Artificial Intelligence. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19066-2_10.

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Thimonier, Hugo, Fabrice Popineau, Arpad Rimmel, Bich-Liên Doan, and Fabrice Daniel. "Comparative Evaluation of Anomaly Detection Methods for Fraud Detection in Online Credit Card Payments." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4581-4_4.

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AbstractThis study explores the application of anomaly detection (AD) methods in imbalanced learning tasks, focusing on fraud detection using real online credit card payment data. We assess the performance of several recent AD methods and compare their effectiveness against standard supervised learning methods. Offering evidence of distribution shift within our dataset, we analyze its impact on the tested models’ performances. Our findings reveal that LightGBM exhibits significantly superior performance across all evaluated metrics but suffers more from distribution shifts than AD methods. Fur
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Jayathunga, N. S. M., P. A. D. R. Rupasinghe, K. G. G. S. Karunathilaka, and G. S. Dissanayake. "Resolving Online Banking Frauds of an Emerging Economy in Contributing Towards Sustaining International Business." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-9324-2_4.

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Conference papers on the topic "Online frauds"

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Karnatak, Vijay, Amit Kumar Mishra, Neha Tripathi, Ashish Gupta, Ankur Dumka, and Hemendra Shanker Sharma. "A Cybercrime Detection and Mitigation Framework for Online Credit Card Frauds." In 2024 International Conference on Computer, Electronics, Electrical Engineering & their Applications (IC2E3). IEEE, 2024. https://doi.org/10.1109/ic2e362166.2024.10827097.

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Pinjarkar, Latika, Pawan Rajendra Hete, Mahantesh Mattada, Santosh Nejakar, Poorva Agrawal, and Gagandeep Kaur. "An Examination of Prevalent Online Scams: Phishing Attacks, Banking Frauds, and E-Commerce Deceptions." In 2024 Second International Conference on Advances in Information Technology (ICAIT). IEEE, 2024. http://dx.doi.org/10.1109/icait61638.2024.10690377.

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Allam, Mohan, Vandana Chintala, V. Gayatri Akshaya, Varshitha Appikonda, and Ruchitha Gandi. "Comprehensive Detection of Fake Job Postings: Applying Advanced Data Balancing and Machine Learning Techniques to Combat Online Frauds." In 2025 6th International Conference on Recent Advances in Information Technology (RAIT). IEEE, 2025. https://doi.org/10.1109/rait65068.2025.11089425.

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Pandey, Nitin, Sofia Singh, and Archana Singh. "Online Transaction Fraud Detection Using Deep Learning." In 2024 International Conference on Innovations and Challenges in Emerging Technologies (ICICET). IEEE, 2024. http://dx.doi.org/10.1109/icicet59348.2024.10616357.

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P, Jayabharathi, Vinoth Kumar S, and Vijay Rajasimman R. "Online Exam Fraud Detection using Different Techniques." In 2025 International Conference on Frontier Technologies and Solutions (ICFTS). IEEE, 2025. https://doi.org/10.1109/icfts62006.2025.11031964.

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Atia, Hend Abdelbakey, Magdy Aboul-Ela, Christina Albert Reyad, and Nancy Awadallah Awad. "Online Payments Fraud Detection Using Machine Learning Techniques." In 2024 Intelligent Methods, Systems, and Applications (IMSA). IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652834.

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Deo, Sakshi, Mohammad Adnan, Manjay Raj, Ali Imam Abidi, and Nidhi Bansal. "Online Payment Fraud Transaction Detection using Machine Learning." In 2024 3rd Edition of IEEE Delhi Section Flagship Conference (DELCON). IEEE, 2024. https://doi.org/10.1109/delcon64804.2024.10866604.

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Rathore, Rachna, Narayan Singh, Dilip Prajapat, Arti Yadav, Manisha Vashisht, and P. Priya Dharshini. "Fraud Detection in Online Transactions Using Machine Learning." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10895130.

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Singh, Renuka, Janarthanan Sekar, Parvez Ahmad, and Viqar Ahmad. "Online Payments Fraud Detection with Machine Learning Algorithm." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10894819.

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Sai, C. C. Dhanush, Chaluvadi Naga Amaresh, and S. Jancy. "Online Payment Fraud Detection Using Exploratory Data Analysis." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968090.

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Reports on the topic "Online frauds"

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Aruguete, Natalia, Flavia Batista, Ernesto Calvo, Matías Guizzo Altube, Carlos Scartascini, and Tiago Ventura. Research Insights: How Do Confirmation Frames Reduce Misinformation in Fact-Checking? Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013008.

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Confirmation frames lead to higher engagement rates than refutation frames across four countries. Confirmation frames are also associated with reduced negative emotions and affective polarization, which is vital for policy interventions targeting health misinformation and harmful speech. By reducing negative emotions and fostering positive ones, confirmation frames could contribute to a more constructive and less polarized online environment.
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Aruguete, Natalia, Flavia Batista, Ernesto Calvo, Matías Guizzo Altube, Carlos Scartascini, and Tiago Ventura. Reducing Misinformation: The Role of Confirmation Frames in Fact-Checking Interventions. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005035.

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Previous research has extensively investigated why users spread misinformation online, while less attention has been given to the motivations behind sharing fact-checks. This paper reports a four-country survey experiment assessing the influence of confirmation and refutation frames on engagement with online fact-checks. Respondents randomly received semantically identical content, either affirming accurate information (“It is TRUE that p”) or refuting misinformation (“It is FALSE that not p”). Despite semantic equivalence, confirmation frames elicit higher engagement rates than refutation fra
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Tao, Yang, Amos Mizrach, Victor Alchanatis, Nachshon Shamir, and Tom Porter. Automated imaging broiler chicksexing for gender-specific and efficient production. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7594391.bard.

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Extending the previous two years of research results (Mizarch, et al, 2012, Tao, 2011, 2012), the third year’s efforts in both Maryland and Israel were directed towards the engineering of the system. The activities included the robust chick handling and its conveyor system development, optical system improvement, online dynamic motion imaging of chicks, multi-image sequence optimal feather extraction and detection, and pattern recognition. Mechanical System Engineering The third model of the mechanical chick handling system with high-speed imaging system was built as shown in Fig. 1. This syst
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