Related papers: Automatically Dismantling Online Dating Fraud
Mobile network operators implement firewalls to stop illicit messages, but scammers find ways to evade detection. Previous work has looked into SMS texts that are blocked by these firewalls. However, there is little insight into SMS texts…
The deception in the text can be of different forms in different domains, including fake news, rumor tweets, and spam emails. Irrespective of the domain, the main intent of the deceptive text is to deceit the reader. Although…
Advertising is a primary means for revenue generation for millions of websites and smartphone apps (publishers). Naturally, a fraction of publishers abuse the ad-network to systematically defraud advertisers of their money. Defenses have…
In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles. Financial transactions, customer reviews, social…
A method to produce personalized classification models to automatically review online dating profiles on Tinder is proposed, based on the user's historical preference. The method takes advantage of a FaceNet facial classification model to…
With the booming popularity of smartphones, threats related to these devices are increasingly on the rise. Smishing, a combination of SMS (Short Message Service) and phishing has emerged as a treacherous cyber threat used by malicious…
Due to the increasing trend of performing spamming activities (e.g., Web spam, deceptive reviews, fake followers, etc.) on various online platforms to gain undeserved benefits, spam detection has emerged as a hot research issue. Previous…
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…
Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money…
Deceptive patterns are design practices embedded in digital platforms to manipulate users, representing a widespread and long-standing issue in the web and mobile software development industry. Legislative actions highlight the urgency of…
As organizations increasingly rely on professionally oriented networks such as LinkedIn (the largest such social network) for building business connections, there is increasing value in having one's profile noticed within the network. As…
Over the years, online scams have grown dramatically, with nearly 50% of global consumers encountering scam attempts each week. These scams cause not only significant financial losses to individuals and businesses, but also lasting…
As online fraud becomes more sophisticated and pervasive, traditional fraud detection methods are struggling to keep pace with the evolving tactics employed by fraudsters. This paper explores the transformative role of machine learning in…
Fraud continues to proliferate online, from phishing and ransomware to impersonation scams. Yet automated prevention approaches adapt slowly and may not reliably protect users from falling prey to new scams. To better combat online scams,…
In this paper, we present a novel method for detecting fake and Large Language Model (LLM)-generated profiles in the LinkedIn Online Social Network immediately upon registration and before establishing connections. Early fake profile…
We provide an automated graph theoretic method for identifying individual users' trusted networks of friends in cyberspace. We routinely use our social networks to judge the trustworthiness of outsiders, i.e., to decide where to buy our…
This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines the professional fraudster, formalises the main types and…
The publication of fake reviews by parties with vested interests has become a severe problem for consumers who use online product reviews in their decision making. To counter this problem a number of methods for detecting these fake…
Various problems of any credit card fraud detection based on machine learning come from the imbalanced aspect of transaction datasets. Indeed, the number of frauds compared to the number of regular transactions is tiny and has been shown to…
Automatic scam-baiting is an online fraud countermeasure that involves automated systems responding to online fraudsters in order to waste their time and deplete their resources, diverting attackers away from real potential victims.…