AnomalydetectionData augmentationMulti-viewGraph attention networkAs the default protocol for exchanging routing reachability information on the Internet, the abnormal behavior in traffic of Border Gateway Prot
Detecting credit card fraud in real-time has become increasingly important with the rise of electronic transactions. However, existing methods often fail to deliver high accuracy and robustness due to class imbalance and overlapping features. To address these issues, Anomaly Detection in Online Credit ...
We propose a nonparametric Bayesian probabilistic latent variable model for multi-view anomaly detection, which is the task of finding instances that have inconsistent views. With the proposed model, all views of a non-anomalous instance are assumed to be generated from a single latent vector. On...
Anomaly Evaluation Module Experiments Keywords:Contrastive Learning,Anomaly Detection Introduction 什么是Graph Anomaly Detection(GAD)? GAD的重点是识别在属性或结构上与大多数节点有显著不同的异常节点。在社交网络的背景下,它有助于检测虚假账户、恶意活动和网络攻击。同样,它在识别信用卡欺诈和金融网络内的洗钱活动...
our selection contains many gene promoters). We do not fixate on a single type of error, nor do we emit a definitive judgement on peak quality, as it is impossible without supervision. This is made possible by using high-quality ReMap data; indeed, unsupervised anomaly detection presupposes ...
例子来源: Liu, A., & Lam, D. (2012). Using Consensus Clustering for Multi-view Anomaly Detection. In 2012 IEEE Symposium on Security and Privacy Workshops (pp. 117–124). IEEE. https://doi.org/10.1109/SPW.2012.18) 多视图学习同时也能做半监督学习(semi-supervised learning)来节约人工成本,...
Lian J, Wang X, Lin X, Wu Z, Wang S, Guo W (2024) Graph anomaly detection via multi-view discriminative awareness learning. IEEE Trans Netw Sci Eng 11:6623–6635 Liang W, Liu X, Zhou S, et al (2022) Robust graph-based multi-view clustering. In: Proceedings of the 36th AAAI conf...
Zhang et al. propose a method for multi-dimensional video anomaly detection, which uses the Object-meta instead of video frames as the input, and the Memory Search Guided Autoencoder with Memory Pools (MSGAE-MP) to reconstruct. The multi-dimensional information carried by the input can be str...
Deep learning architec- tures, which perform feature engineering by establishing relationships between features through defined hidden layers and also have the capacity to learn from errors, are used in various fields, including but not limited to malware detec- tion, intrusion and anomaly detection. ...
Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid development. However, the recent development of IAD approach has encountered certain difficulties due to dataset limitations. On the one hand, most of the state-of-the-art methods have achieved saturation (over...