Inicio  /  Algorithms  /  Vol: 16 Par: 1 (2023)  /  Artículo
ARTÍCULO
TITULO

Improved Anomaly Detection by Using the Attention-Based Isolation Forest

Lev Utkin    
Andrey Ageev    
Andrei Konstantinov and Vladimir Muliukha    

Resumen

A new modification of the isolation forest called the attention-based isolation forest (ABIForest) is proposed for solving the anomaly detection problem. It incorporates an attention mechanism in the form of Nadaraya?Watson regression into the isolation forest to improve the solution of the anomaly detection problem. The main idea underlying the modification is the assignment of attention weights to each path of trees with learnable parameters depending on the instances and trees themselves. Huber?s contamination model is proposed to be used to define the attention weights and their parameters. As a result, the attention weights are linearly dependent on learnable attention parameters that are trained by solving a standard linear or quadratic optimization problem. ABIForest can be viewed as the first modification of the isolation forest to incorporate an attention mechanism in a simple way without applying gradient-based algorithms. Numerical experiments with synthetic and real datasets illustrate that the results of ABIForest outperform those of other methods. The code of the proposed algorithms has been made available.

 Artículos similares

       
 
Yuanfeng Lian, Yueyao Geng and Tian Tian    
Due to the complexity of the oil and gas station system, the operational data, with various temporal dependencies and inter-metric dependencies, has the characteristics of diverse patterns, variable working conditions and imbalance, which brings great ch... ver más
Revista: Applied Sciences

 
Jiewen Huang and Ying Yang    
Inlight of the extensive utilization of automated machining centers, the operation and maintenance level and efficiency of machining centers require further enhancement. In our work, an anomaly detection model is proposed to detect the operation executio... ver más
Revista: Applied Sciences

 
Marie Bieber, Wim J. C. Verhagen, Fabrice Cosson and Bruno F. Santos    
Spacecraft systems collect health-related data continuously, which can give an indication of the systems? health status. While they rarely occur, the repercussions of such system anomalies, faults, or failures can be severe, safety-critical and costly. T... ver más
Revista: Aerospace

 
Abrar Alamr and Abdelmonim Artoli    
Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis models ... ver más
Revista: Algorithms

 
Sizhe Luo, Weiming Zeng and Bowen Sun    
With the increasing popularity of automatic identification system AIS devices, mining latent vessel motion patterns from AIS data has become a hot topic in water transportation research. Trajectory similarity computation is a fundamental issue to many ma... ver más