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With the rapid growth of financial services, fraud detection has been a very important problem to guarantee a healthy environment for both users and providers. Conventional solutions for fraud detection mainly use some rule-based methods or…

Social and Information Networks · Computer Science 2020-03-05 Daixin Wang , Jianbin Lin , Peng Cui , Quanhui Jia , Zhen Wang , Yanming Fang , Quan Yu , Jun Zhou , Shuang Yang , Yuan Qi

Hacks are one of the most damaging types of cryptocurrency related crime, accounting for billions of dollars in stolen funds since 2009. Professional investigators at Chainalysis have traced these stolen funds from the initial breach on an…

Physics and Society · Physics 2019-10-30 Daniel Goldsmith , Kim Grauer , Yonah Shmalo

Fraud detection aims to discover fraudsters deceiving other users by, for example, leaving fake reviews or making abnormal transactions. Graph-based fraud detection methods consider this task as a classification problem with two classes:…

Machine Learning · Computer Science 2024-01-04 Heehyeon Kim , Jinhyeok Choi , Joyce Jiyoung Whang

Card payment fraud is a serious problem, and a roadblock for an optimally functioning digital economy, with cards (Debits and Credit) being the most popular digital payment method across the globe. Despite the occurrence of fraud could be…

Cryptography and Security · Computer Science 2020-12-01 Bemali Wickramanayake , Dakshi Kapugama Geeganage , Chun Ouyang , Yue Xu

Fraudulent activity in the financial industry costs billions annually. Detecting fraud, therefore, is an essential yet technically challenging task that requires carefully analyzing large volumes of data. While machine learning (ML)…

Statistical Finance · Quantitative Finance 2025-07-04 Linh Nguyen , Marcel Boersma , Erman Acar

Credit card fraud has emerged as major problem in the electronic payment sector. In this survey, we study data-driven credit card fraud detection particularities and several machine learning methods to address each of its intricate…

Machine Learning · Computer Science 2020-10-14 Yvan Lucas , Johannes Jurgovsky

Insurance fraud occurs when policyholders file claims that are exaggerated or based on intentional damages. This contribution develops a fraud detection strategy by extracting insightful information from the social network of a claim.…

Social and Information Networks · Computer Science 2020-09-18 María Óskarsdóttir , Waqas Ahmed , Katrien Antonio , Bart Baesens , Rémi Dendievel , Tom Donas , Tom Reynkens

We employ network embedding to detect money laundering in financial transaction networks. Using real anonymized banking data, we model over one million accounts as a directed graph and use it to refine previously detected suspicious cycles…

Social and Information Networks · Computer Science 2025-09-16 Anthony Bonato , Adam Szava

The proliferation of misinformation and disinformation on social media networks has become increasingly concerning. With a significant portion of the population using social media on a regular basis, there are growing efforts by malicious…

Social and Information Networks · Computer Science 2024-07-17 Isura Manchanayaka , Zainab Zaidi , Shanika Karunasekera , Christopher Leckie

Monero, the leading privacy-focused cryptocurrency, relies on a peer-to-peer (P2P) network to propagate transactions and blocks. Growing evidence suggests that non-standard nodes exist in the network, posing as honest nodes but are perhaps…

Networking and Internet Architecture · Computer Science 2025-09-15 Yannik Kopyciok , Stefan Schmid , Friedhelm Victor

Financial institutions face escalating challenges in identifying high-risk customer behaviors within massive transaction networks, where fraudulent activities exploit market fragmentation and institutional boundaries. We address three…

Computational Engineering, Finance, and Science · Computer Science 2026-01-01 Lecheng Zheng , Jian Ni , Chris Zobel , John R Birge

This research investigated how online criminal activities can be better understood and connected using data-driven machine learning methods. Many illegal activities, such as human trafficking and illicit trade, have moved to online…

Computation and Language · Computer Science 2026-05-07 Vageesh Kumar Saxena

Bots constitute a significant portion of Internet traffic and are a source of various issues across multiple domains. Modern bots often become indistinguishable from real users, as they employ similar methods to browse the web, including…

Machine Learning · Computer Science 2024-12-04 Jan Kadel , August See , Ritwik Sinha , Mathias Fischer

Blockchain technology has been successfully exploited for deploying new economic applications. However, it has started arousing the interest of malicious actors who deliver scams to deceive honest users and to gain economic advantages.…

Cryptography and Security · Computer Science 2024-04-19 Letterio Galletta , Fabio Pinelli

This paper is motivated by the task of detecting anomalies in networks of financial transactions, with accounts as nodes and a directed weighted edge between two nodes denoting a money transfer. The weight of the edge is the transaction…

Applications · Statistics 2019-05-28 Andrew Elliott , Mihai Cucuringu , Milton Martinez Luaces , Paul Reidy , Gesine Reinert

The popularity of Twitter has fostered the emergence of various fraudulent user activities - one such activity is to artificially bolster the social reputation of Twitter profiles by gaining a large number of followers within a short time…

Social and Information Networks · Computer Science 2021-07-27 Hridoy Sankar Dutta , Kartik Aggarwal , Tanmoy Chakraborty

With the explosive growth of the e-commerce industry, detecting online transaction fraud in real-world applications has become increasingly important to the development of e-commerce platforms. The sequential behavior history of users…

Machine Learning · Computer Science 2022-01-05 Yongchun Zhu , Dongbo Xi , Bowen Song , Fuzhen Zhuang , Shuai Chen , Xi Gu , Qing He

With online payment platforms being ubiquitous and important, fraud transaction detection has become the key for such platforms, to ensure user account safety and platform security. In this work, we present a novel method for detecting…

Machine Learning · Computer Science 2020-03-30 Longfei Li , Ziqi Liu , Chaochao Chen , Ya-Lin Zhang , Jun Zhou , Xiaolong Li

The dark web has emerged as the state-of-the-art solution for enhanced anonymity. Just like a double-edged sword, it also inadvertently becomes the safety net and breeding ground for illicit activities. Among them, cryptocurrencies have…

Cryptography and Security · Computer Science 2024-04-09 Pengcheng Xia , Zhou Yu , Kailong Wang , Kai Ma , Shuo Chen , Xiapu Luo , Yajin Zhou , Lei Wu , Guangdong Bai

While most organizations continue to invest in traditional network defences, a formidable security challenge has been brewing within their own boundaries. Malicious insiders with privileged access in the guise of a trusted source have…

Cryptography and Security · Computer Science 2018-09-10 Anagi Gamachchi , Serdar Boztas
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