No abstract available.
Proceeding Downloads
Stream-based Machine Learning for Network Security and Anomaly Detection
Data Stream Machine Learning is rapidly gaining popularity within the network monitoring community as the big data produced by network devices and end-user terminals goes beyond the memory constraints of standard monitoring equipment. Critical network ...
Finding Anomalies in Network System Logs with Latent Variables
System logs are useful to understand the status of and detect faults in large scale networks. However, due to their diversity and volume of these logs, log analysis requires much time and effort. In this paper, we propose a log event anomaly detection ...
Telemetry-based stream-learning of BGP anomalies
- Andrian Putina,
- Dario Rossi,
- Albert Bifet,
- Steven Barth,
- Drew Pletcher,
- Cristina Precup,
- Patrice Nivaggioli
Recent technology evolution allows network equipments to continuously stream a wealth of "telemetry" information, which pertains to multiple protocols and layers of the stack, at a very fine spatialgrain and at high-frequency. Processing this deluge of ...
NetSlicer: Automated and Traffic-Pattern Based Application Clustering in Datacenters
Companies often have very limited information about the applications running in their datacenter or public/private cloud environments. As this can harm efficiency, performance, and security, many network administrators work hard to manually assign ...
Data Analytics Service Composition and Deployment on Edge Devices
Data analytics on edge devices has gained rapid growth in research, industry, and different aspects of our daily life. This topic still faces many challenges such as limited computation resource on edge devices. In this paper, we further identify two ...
Deep Learning IP Network Representations
We present DIP, a deep learning based framework to learn structural properties of the Internet, such as node clustering or distance between nodes. Existing embedding-based approaches use linear algorithms on a single source of data, such as latency or ...
Learning and Generating Distributed Routing Protocols Using Graph-Based Deep Learning
Automated network control and management has been a long standing target of network protocols. We address in this paper the question of automated protocol design, where distributed networked nodes have to cooperate to achieve a common goal without a ...
Understanding the Modeling of Computer Network Delays using Neural Networks
Recent trends in networking are proposing the use of Machine Learning (ML) techniques for the control and operation of the network. In this context, ML can be used as a computer network modeling technique to build models that estimate the network ...
- Proceedings of the 2018 Workshop on Big Data Analytics and Machine Learning for Data Communication Networks
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
Big-DAMA '19 | 11 | 7 | 64% |
Overall | 11 | 7 | 64% |