相关论文: Detecting problematic transactions in a consumer-t…
While human factors in fraud have been studied by the HCI and security communities, most research has been directed to understanding either the victims' perspectives or prevention strategies, and not on fraudsters, their motivations and…
The darknet markets are notorious black markets in cyberspace, which involve selling or brokering drugs, weapons, stolen credit cards, and other illicit goods. To combat illicit transactions in the cyberspace, it is important to analyze the…
This work presents a fraud and abuse detection framework for streaming services by modeling user streaming behavior. The goal is to discover anomalous and suspicious incidents and scale the investigation efforts by creating models that…
Market segmentation of an online auction site is studied by analyzing the users' bidding behavior. The distribution of user activity is investigated and a network of bidders connected by common interest in individual articles is…
Rapid growth of modern technologies such as internet and mobile computing are bringing dramatically increased e-commerce payments, as well as the explosion in transaction fraud. Meanwhile, fraudsters are continually refining their tricks,…
Advertising click fraud detection plays one of the vital roles in current E-commerce websites as advertising is an essential component of its business model. It aims at, given a set of corresponding features, e.g., demographic information…
Online retail, eCommerce, frequently falls victim to fraud conducted by malicious customers (fraudsters) who obtain goods or services through deception. Fraud coordinated by groups of professional fraudsters that place several fraudulent…
In the age of social computing, finding interesting network patterns or motifs is significant and critical for various areas such as decision intelligence, intrusion detection, medical diagnosis, social network analysis, fake news…
With growing credit card transaction volumes, the fraud percentages are also rising, including overhead costs for institutions to combat and compensate victims. The use of machine learning into the financial sector permits more effective…
Card transaction fraud is a growing problem affecting card holders worldwide. Financial institutions increasingly rely upon data-driven methods for developing fraud detection systems, which are able to automatically detect and block…
Credit card fraud is an ongoing problem for almost all industries in the world, and it raises millions of dollars to the global economy each year. Therefore, there is a number of research either completed or proceeding in order to detect…
Financial transaction fraud prevention faces challenges such as complex relationship structures, concealed behavioral patterns, and dynamically changing data distribution. Discrimination models relying solely on independent sample features…
Due to the pseudo-anonymity of the Bitcoin network, users can hide behind their bitcoin addresses that can be generated in unlimited quantity, on the fly, without any formal links between them. Thus, it is being used for payment transfer by…
We present a prototype system developed in cooperation with a business organization that combines information visualization and pattern-matching techniques to detect fraudulent activity by employees. The system is built upon common fraud…
This research explores the opportunities for the application of network analytic techniques to prevent money laundering. We worked on real world data by analyzing the central database of a factoring company, mainly operating in Italy, over…
Cryptocurrencies are rapidly expanding and becoming vital in digital financial markets. However, the rise in cryptocurrency-related illicit activities has led to significant losses for users. To protect the security of these platforms, it…
The UK anti-fraud charity Fraud Advisory Panel (FAP) in their review of 2016 estimates business costs of fraud at 144 billion, and its individual counterpart at 9.7 billion. Banking, insurance, manufacturing, and government are the most…
Bitcoin is a cryptocurrency that features a distributed, decentralized and trustworthy mechanism, which has made Bitcoin a popular global transaction platform. The transaction efficiency among nations and the privacy benefiting from address…
As businesses increasingly rely on social networking sites to engage with their customers, it is crucial to understand and counter reputation manipulation activities, including fraudulently boosting the number of Facebook page likes using…
In shaping the Internet of Money, the application of blockchain and distributed ledger technologies (DLTs) to the financial sector triggered regulatory concerns. Notably, while the user anonymity enabled in this field may safeguard privacy…