Papers Group Anomaly Detection
“Group Anomaly Detection” 태그가 달린 논문 13편 · 필터 해제
GADformer: A Transparent Transformer Model for Group Anomaly Detection on Trajectories
Group Anomaly Detection (GAD) identifies unusual pattern in groups where individual members might not be anomalous. This task is of major importance across multiple disciplines, in which also sequences like trajectories …
Anomaly DetectionGroup Anomaly DetectionOutlier DetectionNew Methods and Datasets for Group Anomaly Detection From Fundamental Physics
The identification of anomalous overdensities in data - group or collective anomaly detection - is a rich problem with a large number of real world applications. However, it has received relatively little attention in th…
Anomaly DetectionGroup Anomaly DetectionIsolation Distributional Kernel: A New Tool for Point & Group Anomaly Detection
We introduce Isolation Distributional Kernel as a new way to measure the similarity between two distributions. Existing approaches based on kernel mean embedding, which convert a point kernel to a distributional kernel, …
Anomaly DetectionGroup Anomaly DetectionMSTREAM: Fast Anomaly Detection in Multi-Aspect Streams
Given a stream of entries in a multi-aspect data setting i.e., entries having multiple dimensions, how can we detect anomalous activities in an unsupervised manner? For example, in the intrusion detection setting, existi…
Anomaly DetectionGroup Anomaly DetectionIntrusion DetectionKullback-Leibler Divergence-Based Out-of-Distribution Detection with Flow-Based Generative Models
Recent research has revealed that deep generative models including flow-based models and Variational Autoencoders may assign higher likelihoods to out-of-distribution (OOD) data than in-distribution (ID) data. However, w…
Anomaly DetectionGroup Anomaly DetectionOut-of-Distribution DetectionFinding Rats in Cats: Detecting Stealthy Attacks using Group Anomaly Detection
Advanced attack campaigns span across multiple stages and stay stealthy for long time periods. There is a growing trend of attackers using off-the-shelf tools and pre-installed system applications (such as \emph{powershe…
Anomaly DetectionAttributeGroup Anomaly DetectionSentence+2Correlated Anomaly Detection from Large Streaming Data
Correlated anomaly detection (CAD) from streaming data is a type of group anomaly detection and an essential task in useful real-time data mining applications like botnet detection, financial event detection, industrial …
Anomaly DetectionEvent DetectionGroup Anomaly DetectionGroup Anomaly Detection using Deep Generative Models
Unlike conventional anomaly detection research that focuses on point anomalies, our goal is to detect anomalous collections of individual data points. In particular, we perform group anomaly detection (GAD) with an empha…
Anomaly DetectionGroup Anomaly DetectionDetecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data
In a variety of applications, one desires to detect groups of anomalous data samples, with a group potentially manifesting its atypicality (relative to a reference model) on a low-dimensional subset of the full measured …
Anomaly DetectionGroup Anomaly DetectionIntrusion DetectionNetwork Intrusion DetectionGLAD: Group Anomaly Detection in Social Media Analysis- Extended Abstract
Traditional anomaly detection on social media mostly focuses on individual point anomalies while anomalous phenomena usually occur in groups. Therefore it is valuable to study the collective behavior of individuals and d…
Anomaly DetectionGroup Anomaly DetectionOne-Class Support Measure Machines for Group Anomaly Detection
We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class support vector machine…
Anomaly DetectionGroup Anomaly DetectionOne-Class Support Measure Machines for Group Anomaly Detection
We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class support vector machine…
Anomaly DetectionGroup Anomaly DetectionGroup Anomaly Detection using Flexible Genre Models
An important task in exploring and analyzing real-world data sets is to detect unusual and interesting phenomena. In this paper, we study the group anomaly detection problem. Unlike traditional anomaly detection research…
Anomaly DetectionGroup Anomaly Detection