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Related papers: EventADL: Open-Box Anomaly Detection and Localizat…

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Detecting rare events and anomalies in large-scale signals is essential in fields such as astronomy, physical simulations, and biomedical science. In many cases, this problem naturally decomposes into identifying common local patterns and…

Machine Learning · Computer Science 2026-04-30 Jad Yehya , Mansour Benbakoura , Cédric Allain , Benoît Malezieux , Matthieu Kowalski , Thomas Moreau

Cloud application services are distributed in nature and have components across the stack working together to deliver the experience to end users. The wide adoption of microservice architecture exacerbates failure management due to…

Performance · Computer Science 2025-09-09 Dhanya R Mathews , Mudit Verma , Pooja Aggarwal , J. Lakshmi

Performance and high availability have become increasingly important drivers, amongst other drivers, for user retention in the context of web services such as social networks, and web search. Exogenic and/or endogenic factors often give…

Machine Learning · Computer Science 2017-04-26 Jordan Hochenbaum , Owen S. Vallis , Arun Kejariwal

Anomaly detection in cloud environments remains both critical and challenging. Existing context-level benchmarks typically focus on either metrics or logs and often lack reliable annotation, while most detection methods emphasize point…

Artificial Intelligence · Computer Science 2025-10-07 Xinkai Zou , Xuan Jiang , Ruikai Huang , Haoze He , Parv Kapoor , Hongrui Wu , Yibo Wang , Jian Sha , Xiongbo Shi , Zixun Huang , Jinhua Zhao

Anomaly detection (AD) is a fundamental task of critical importance across numerous domains. Current systems increasingly operate in rapidly evolving environments that generate diverse yet interconnected data modalities -- such as time…

Machine Learning · Computer Science 2025-12-02 Zhongyuan Wu , Jingyuan Wang , Zexuan Cheng , Yilong Zhou , Weizhi Wang , Juhua Pu , Chao Li , Changqing Ma

Cloud systems are complex, large, and dynamic systems whose behavior must be continuously analyzed to timely detect misbehaviors and failures. Although there are solutions to flexibly monitor cloud systems, cost-effectively controlling the…

Software Engineering · Computer Science 2019-09-19 Marco Mobilio , Matteo Orrù , Oliviero Riganelli , Alessandro Tundo , Leonardo Mariani

Software Log anomaly event detection with masked event prediction has various technical approaches with countless configurations and parameters. Our objective is to provide a baseline of settings for similar studies in the future. The…

Software Engineering · Computer Science 2022-08-04 Jesse Nyyssölä , Mika Mäntylä , Martín Varela

Due to the veracity and heterogeneity in network traffic, detecting anomalous events is challenging. The computational load on global servers is a significant challenge in terms of efficiency, accuracy, and scalability. Our primary…

Machine Learning · Computer Science 2023-03-15 William Marfo , Deepak K. Tosh , Shirley V. Moore

Video Anomaly Detection (VAD) automates the identification of unusual events, such as security threats in surveillance videos. In real-world applications, VAD models must effectively operate in cross-domain settings, identifying rare…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Yashika Jain , Ali Dabouei , Min Xu

Video Anomaly Detection (VAD) can play a key role in spotting unusual activities in video footage. VAD is difficult to use in real-world settings due to the dynamic nature of human actions, environmental variations, and domain shifts.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Shanle Yao , Ghazal Alinezhad Noghre , Armin Danesh Pazho , Hamed Tabkhi

Online unsupervised detection of anomalies is crucial to guarantee the correct operation of cyber-physical systems and the safety of humans interacting with them. State-of-the-art approaches based on deep learning via neural networks…

Machine Learning · Computer Science 2024-07-30 Daniele Meli

Anomaly detection in complex industrial environments poses unique challenges, particularly in contexts characterized by data sparsity and evolving operational conditions. Predictive maintenance (PdM) in such settings demands methodologies…

Machine Learning · Computer Science 2025-03-12 Alicia Russell-Gilbert , Sudip Mittal , Shahram Rahimi , Maria Seale , Joseph Jabour , Thomas Arnold , Joshua Church

Recently web applications have been widely used in enterprises to assist employees in providing effective and efficient business processes. Forecasting upcoming web events in enterprise web applications can be beneficial in many ways, such…

Cryptography and Security · Computer Science 2020-09-08 Xiaoyong Yuan , Lei Ding , Malek Ben Salem , Xiaolin Li , Dapeng Wu

In large IT systems, software deployment is a crucial process in online services as their code is regularly updated. However, a faulty code change may degrade the target service's performance and cause cascading outages in downstream…

Machine Learning · Computer Science 2024-06-07 Jingchao Ni , Gauthier Guinet , Peihong Jiang , Laurent Callot , Andrey Kan

As command-line interfaces remain integral to high-performance computing environments, the risk of exploitation through stealthy and complex command-line abuse grows. Conventional security solutions struggle to detect these anomalies due to…

Cryptography and Security · Computer Science 2024-12-10 Vaishali Vinay , Anjali Mangal

Logs play a crucial role in system monitoring and debugging by recording valuable system information, including events and states. Although various methods have been proposed to detect anomalies in log sequences, they often overlook the…

Machine Learning · Computer Science 2023-09-13 Yufei Li , Yanchi Liu , Haoyu Wang , Zhengzhang Chen , Wei Cheng , Yuncong Chen , Wenchao Yu , Haifeng Chen , Cong Liu

Log analysis is an important technique that engineers use for troubleshooting faults of large-scale service-oriented systems. In this study, we propose a novel semi-supervised log-based anomaly detection approach, LogDP, which utilizes the…

Software Engineering · Computer Science 2021-10-06 Yongzheng Xie , Hongyu Zhang , Bo Zhang , Muhammad Ali Babar , Sha Lu

An important tool grid operators use to safeguard against failures, whether naturally occurring or malicious, involves detecting anomalies in the power system SCADA data. In this paper, we aim to solve a real-time anomaly detection problem.…

Machine Learning · Computer Science 2024-04-12 SangWoo Park , Amritanshu Pandey

With their widespread popularity, web services have become the main targets of various cyberattacks. Existing traffic anomaly detection approaches focus on flow-level attacks, yet fail to recognize behavior-level attacks, which appear…

Cryptography and Security · Computer Science 2025-11-10 Zhibo Dong , Yong Huang , Shubao Sun , Wentao Cui , Zhihua Wang

In many real-world AD applications including computer security and fraud prevention, the anomaly detector must be configurable by the human analyst to minimize the effort on false positives. One important way to configure the detector is by…

Machine Learning · Computer Science 2024-05-15 Shubhomoy Das , Md Rakibul Islam , Nitthilan Kannappan Jayakodi , Janardhan Rao Doppa