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View article: Towards Foundation Auto-Encoders for Time-Series Anomaly Detection
Towards Foundation Auto-Encoders for Time-Series Anomaly Detection Open
We investigate a novel approach to time-series modeling, inspired by the successes of large pretrained foundation models. We introduce FAE (Foundation Auto-Encoders), a foundation generative-AI model for anomaly detection in time-series da…
View article: TSGFM - Towards a Graph Foundation Model for Time Series Analysis in Network Monitoring
TSGFM - Towards a Graph Foundation Model for Time Series Analysis in Network Monitoring Open
We present TSGFM, a Time Series Graph Foundation Model for network monitoring data analysis, based on spatiotemporal Graph Neural Networks (GNN). Inspired by the success of foundation models in achieving generalization and adaptation, TSGF…
View article: MOXAI – Manufacturing Optimization through Model-Agnostic Explainable AI and Data-Driven Process Tuning
MOXAI – Manufacturing Optimization through Model-Agnostic Explainable AI and Data-Driven Process Tuning Open
Modern manufacturing equipment offers numerous configurable parameters for optimization, yet operators often underutilize them. Recent advancements in machine learning (ML) have introduced data-driven models in industrial settings, integra…
View article: <i>Marina</i>: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale
<i>Marina</i>: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale Open
Network operators require real-time traffic monitoring insights to provide high performance and security to their customers. It has been shown that artificial intelligence and machine learning (ML) can improve the visibility of telemetry s…
View article: One Model to Find Them All Deep Learning for Multivariate Time-Series Anomaly Detection in Mobile Network Data
One Model to Find Them All Deep Learning for Multivariate Time-Series Anomaly Detection in Mobile Network Data Open
Transferencia tecnológica. Grupo de investigación Detección de anomalías en series de tiempo, Facultad de Ingeniería. Instituto de Ingeniería Eléctrica.
View article: GROWS
GROWS Open
Wireless networks have progressed exponentially over the last decade, and modern wireless networking is today a complex to manage tangle, serving an ever-growing number of end-devices through a plethora of technologies. The broad range of …
View article: Smart Active Sampling to enhance Quality Assurance Efficiency
Smart Active Sampling to enhance Quality Assurance Efficiency Open
We propose a new sampling strategy, called smart active sapling, for quality inspections outside the production line. Based on the principles of active learning a machine learning model decides which samples are sent to quality inspection.…
View article: Not all Web Pages are Born the Same Content Tailored Learning for Web QoE Inference
Not all Web Pages are Born the Same Content Tailored Learning for Web QoE Inference Open
Web Quality of Experience (QoE) monitoring is a critical task for Internet Service Providers (ISPs), especially due to the key role played by customer experience in churn management. Previously, we have tackled the problem of Web QoE infer…
View article: DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming
DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming Open
We introduce DeepCrypt, a deep-learning based approach to analyze YouTube adaptive video streaming Quality of Experience (QoE) from the Internet Service Provider (ISP) perspective, relying exclusively on the analysis of encrypted network t…
View article: Where is the Light(ning) in the Taproot Dawn? Unveiling the Bitcoin Lightning (IP) Network
Where is the Light(ning) in the Taproot Dawn? Unveiling the Bitcoin Lightning (IP) Network Open
peer reviewed
View article: How are your Apps Doing? QoE Inference and Analysis in Mobile Devices
How are your Apps Doing? QoE Inference and Analysis in Mobile Devices Open
Web browsing has become the most important application of the Internet for the end user. When it comes to mobile devices, web services are mainly accessed through apps. This paper tackles the problem of Web Quality of Experience (QoE) in m…
View article: Mobile Web and App QoE Monitoring for ISPs -from Encrypted Traffic to Speed Index through Machine Learning
Mobile Web and App QoE Monitoring for ISPs -from Encrypted Traffic to Speed Index through Machine Learning Open
International audience
View article: On the Usage of Generative Models for Network Anomaly Detection in Multivariate Time-Series
On the Usage of Generative Models for Network Anomaly Detection in Multivariate Time-Series Open
Despite the many attempts and approaches for anomaly de- tection explored over the years, the automatic detection of rare events in data communication networks remains a com- plex problem. In this paper we introduce Net-GAN, a novel approa…
View article: Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling
Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling Open
This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-…
View article: Content Matters: Clustering Web Pages for QoE Analysis With WebCLUST
Content Matters: Clustering Web Pages for QoE Analysis With WebCLUST Open
The properties of a web page have a strong impact on its overall loading process, including the download of its contents and their progressive rendering at the browser. As a consequence, web page content has a strong impact on the experien…
View article: Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis
Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis Open
Network-monitoring data commonly arrives in the form of fast and changing data streams. Continuous and dynamic learning is an effective learning strategy when dealing with such data, where concept drifts constantly occur. We propose differ…
View article: ViCrypt to the Rescue: Real-Time, Machine-Learning-Driven Video-QoE Monitoring for Encrypted Streaming Traffic
ViCrypt to the Rescue: Real-Time, Machine-Learning-Driven Video-QoE Monitoring for Encrypted Streaming Traffic Open
Video streaming is the killer application of the Internet today. In this article, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provide…
View article: Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild
Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild Open
Education Service Providers (ESPs) have a paramount role in the digitization of education, providing reliable devices for students and teachers and high quality Internet access at schools. In this paper, a large-scale, passive, in-device Q…
View article: On the Usage of Generative Models for Network Anomaly Detection in\n Multivariate Time-Series
On the Usage of Generative Models for Network Anomaly Detection in\n Multivariate Time-Series Open
Despite the many attempts and approaches for anomaly detection explored over\nthe years, the automatic detection of rare events in data communication\nnetworks remains a complex problem. In this paper we introduce Net-GAN, a novel\napproac…
View article: Scoring High
Scoring High Open
Large-scale events pose severe challenges to live video streaming service providers, who need to cope with high, peaking viewer numbers and the resulting fluctuating resource demands, keeping high levels of Quality of Experience (QoE) to a…
View article: RAL
RAL Open
Network-traffic data usually arrives in the form of a data stream. Online monitoring systems need to handle the incoming samples sequentially and quickly. These systems regularly need to get access to ground-truth data to understand the cu…
View article: How good is your mobile (web) surfing?
How good is your mobile (web) surfing? Open
We address the problem of Web QoE monitoring, in particular Speed Index (SI), from the Internet Service Provider (ISP) perspective, relying on in-network, passive measurements. Given the wide adoption of end-to-end encryption, we resort to…
View article: All that Glitters is not Bitcoin – Unveiling the Centralized Nature of the BTC (IP) Network
All that Glitters is not Bitcoin – Unveiling the Centralized Nature of the BTC (IP) Network Open
Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple no…
View article: Two Decades of AI4NETS-AI/ML for Data Networks: Challenges & Research Directions
Two Decades of AI4NETS-AI/ML for Data Networks: Challenges & Research Directions Open
The popularity of Artificial Intelligence (AI) -- and of Machine Learning (ML) as an approach to AI, has dramatically increased in the last few years, due to its outstanding performance in various domains, notably in image, audio, and natu…
View article: DeepMAL -- Deep Learning Models for Malware Traffic Detection and Classification
DeepMAL -- Deep Learning Models for Malware Traffic Detection and Classification Open
Robust network security systems are essential to prevent and mitigate the harming effects of the ever-growing occurrence of network attacks. In recent years, machine learning-based systems have gain popularity for network security applicat…
View article: Two Decades of AI4NETS-AI/ML for Data Networks: Challenges & Research Directions
Two Decades of AI4NETS-AI/ML for Data Networks: Challenges & Research Directions Open
The popularity of Artificial Intelligence (AI) -- and of Machine Learning (ML) as an approach to AI, has dramatically increased in the last few years, due to its outstanding performance in various domains, notably in image, audio, and natu…
View article: White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges
White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges Open
This white paper is the outcome of the Würzburg seminar on "Crowdsourced Network and QoE Measurements" which took place from 25-26 September 2019 in Würzburg, Germany. International experts were invited from industry and academia. They are…