[HTML][HTML] Fraud detection: A systematic literature review of graph-based anomaly detection approaches
Graph-based anomaly detection (GBAD) approaches are among the most popular
techniques used to analyze connectivity patterns in communication networks and identify …
techniques used to analyze connectivity patterns in communication networks and identify …
Detection of malicious social bots: A survey and a refined taxonomy
M Latah - Expert Systems with Applications, 2020 - Elsevier
Social bots represent a new generation of bots that make use of online social networks
(OSNs) as command and control (C&C) channels. Malicious social bots have been used as …
(OSNs) as command and control (C&C) channels. Malicious social bots have been used as …
Collective opinion spam detection: Bridging review networks and metadata
Online reviews capture the testimonials of" real" people and help shape the decisions of
other consumers. Due to the financial gains associated with positive reviews, however …
other consumers. Due to the financial gains associated with positive reviews, however …
Rev2: Fraudulent user prediction in rating platforms
Rating platforms enable large-scale collection of user opinion about items (eg, products or
other users). However, untrustworthy users give fraudulent ratings for excessive monetary …
other users). However, untrustworthy users give fraudulent ratings for excessive monetary …
Fraudar: Bounding graph fraud in the face of camouflage
Given a bipartite graph of users and the products that they review, or followers and
followees, how can we detect fake reviews or follows? Existing fraud detection methods …
followees, how can we detect fake reviews or follows? Existing fraud detection methods …
Rumor gauge: Predicting the veracity of rumors on Twitter
The spread of malicious or accidental misinformation in social media, especially in time-
sensitive situations, such as real-world emergencies, can have harmful effects on individuals …
sensitive situations, such as real-world emergencies, can have harmful effects on individuals …
One-class adversarial nets for fraud detection
Many online applications, such as online social networks or knowledge bases, are often
attacked by malicious users who commit different types of actions such as vandalism on …
attacked by malicious users who commit different types of actions such as vandalism on …
Discovering opinion spammer groups by network footprints
Online reviews are an important source for consumers to evaluate products/services on the
Internet (eg Amazon, Yelp, etc.). However, more and more fraudulent reviewers write fake …
Internet (eg Amazon, Yelp, etc.). However, more and more fraudulent reviewers write fake …
A synergistic approach for graph anomaly detection with pattern mining and feature learning
Detecting anomalies on graph data has two types of methods. One is pattern mining that
discovers strange structures globally such as quasi-cliques, bipartite cores, or dense blocks …
discovers strange structures globally such as quasi-cliques, bipartite cores, or dense blocks …
Suspicious behavior detection: Current trends and future directions
Suspicious Behavior Detection: Current Trends and Future Directions Page 1 january/february
2016 1541-1672/16/$33.00 © 2016 IEEE 31 Published by the IEEE Computer Society …
2016 1541-1672/16/$33.00 © 2016 IEEE 31 Published by the IEEE Computer Society …