Practical Anomaly Detection in Internet Services: An ISP centric approach

Identifying anomalies in a network is a crutial endeavor for Internet Service Providers (ISPs). Anomalies that impact the traffic of the ISP customers can lead to a degradation in the reputation of the company. Moreover, silent anomalies that do not break connectivity can impact the revenue and busi...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE/IFIP Network Operations and Management Symposium s. 1 - 4
Hlavní autoři: Feng, Alex Huang, Francois, Pierre, Fukuda, Kensuke, Du, Wanting, Graf, Thomas, Lucente, Paolo, Frenot, Stephane
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 06.05.2024
Témata:
Measurement
Monitoring
Real-time systems
Routing protocols
Soft sensors
Telemetry
Web and internet services
ISSN:2374-9709
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Identifying anomalies in a network is a crutial endeavor for Internet Service Providers (ISPs). Anomalies that impact the traffic of the ISP customers can lead to a degradation in the reputation of the company. Moreover, silent anomalies that do not break connectivity can impact the revenue and business of ISPs. Therefore, monitoring and anomaly detection has become essential for ISPs. In this paper, we present an ongoing research project aimed at identifying anomalies in Internet services provided by an ISP. We aim at detecting anomalies within the domain managed by the ISP that impact the customers and the business of the ISP. We propose a rule-based approach designed to promptly detect and provide reporting for such anomalies in near real time, giving information that allows the operator to identify whether a solution can be brought. In this paper, we describe the collected network telemetry metrics and illustrate how they are processed using open-source solutions. We introduce a set of use cases showing that an ISP can monitor Internet services using IETF standard metrics.
ISSN:2374-9709
DOI:10.1109/NOMS59830.2024.10575071