Generalized out-of-distribution detection: A survey

J Yang, K Zhou, Y Li, Z Liu - International Journal of Computer Vision, 2024 - Springer
Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …

Alleviating the inconsistency problem of applying graph neural network to fraud detection

Z Liu, Y Dou, PS Yu, Y Deng, H Peng - Proceedings of the 43rd …, 2020 - dl.acm.org
Graph-based models have been widely used to fraud detection tasks. Owing to the
development of Graph Neural Networks~(GNNs), recent works have proposed many GNN …

[HTML][HTML] Machine learning algorithms for fraud prediction in property insurance: Empirical evidence using real-world microdata

MK Severino, Y Peng - Machine Learning with Applications, 2021 - Elsevier
This paper evaluated fraud prediction in property insurance claims using various machine
learning models based on real-world data from a major Brazilian insurance company. The …

Contradiction in text review and apps rating: prediction using textual features and transfer learning

T Aljrees, M Umer, O Saidani, L Almuqren… - PeerJ Computer …, 2024 - peerj.com
Mobile app stores, such as Google Play, have become famous platforms for practically all
types of software and services for mobile phone users. Users may browse and download …

Understanding incentivized mobile app installs on google play store

S Farooqi, Á Feal, T Lauinger, D McCoy… - Proceedings of the …, 2020 - dl.acm.org
" Incentivized" advertising platforms allow mobile app developers to acquire new users by
directly paying users to install and engage with mobile apps (eg, create an account, make in …

Political leaders in the app ecosystem

R Quevedo-Redondo, N Navarro-Sierra… - Social sciences, 2021 - mdpi.com
This article analyzes the process of symbolic and critical-discursive construction of
applications developed for mobile devices for some of the world's most important heads of …

Botspot++: A hierarchical deep ensemble model for bots install fraud detection in mobile advertising

Y Zhu, X Wang, Q Li, T Yao, S Liang - ACM Transactions on Information …, 2021 - dl.acm.org
Mobile advertising has undoubtedly become one of the fastest-growing industries in the
world. The influx of capital attracts increasing fraudsters to defraud money from advertisers …

Unveiling Collusion-Based Ad Attribution Laundering Fraud: Detection, Analysis, and Security Implications

T Zhu, C Shou, Z Huang, G Chen, X Zhang… - Proceedings of the …, 2024 - dl.acm.org
In recent years, the growth of mobile advertising has been driven by in-app programmatic
advertising and technologies like Real-Time Bidding (RTB). However, this growth has also …

No signal left to chance: driving browser extension analysis by download patterns

P Picazo-Sanchez, B Eriksson… - Proceedings of the 38th …, 2022 - dl.acm.org
Browser extensions are popular small applications that allow users to enrich their browsing
experience. Yet browser extensions pose security concerns because they can leak user …

BotSpot: A hybrid learning framework to uncover bot install fraud in mobile advertising

T Yao, Q Li, S Liang, Y Zhu - Proceedings of the 29th ACM International …, 2020 - dl.acm.org
Mobile advertising has become inarguably one of the fastest growing industries all over the
world. The influx of capital attracts increasing fraudsters to defraud money from advertisers …