Verisign helps enable the security, stability, and resiliency of the internet. We are a trusted provider of internet infrastructure services for the networked world and deliver unmatched performance in domain name system (DNS) services.

We are a mission focused, values driven company where each individual can contribute to building a stronger, more secure internet. We offer a dynamic and flexible work environment with competitive benefits and the ability to grow your career.

DNS Real-Time Anomaly Detection Pipeline

Context

DNS is a fundamental component of the internet infrastructure allowing companies and individuals to connect, work and exchange information. Due to its criticality and stringent uptime requirements, monitoring the state of the infrastructure and detecting anomalies across the global DNS in real-time is vital.

RIPE (Réseau IP Européen, French for "European IP Networks") is a community which purpose is to maintain and develop the internet, facilitating cooperation between public and private sectors. As part of its mission to support the internet infrastructure, it develops a network of internet measurement probes called "Atlas". Atlas provides real-time measurements of various Internet connectivity with probes like ping, traceroute, DNS, SSL and NTP. Everyone, including individuals, can be part of the RIPE Atlas network by hosting a "probing server"[1]. RIPE Atlas[2] collects a vast amount of data about the state of the internet, and makes it all available via a free HTTP API[3].

The goal of this project is to propose and implement a state of the art real-time data processing and anomaly detection architecture to detect and report anomalies.

Project Description

This project will use the data freely available from the RIPE HTTP API about DNS infrastructure. It already runs a multitude of probes⁴ targeting root servers and various other DNS servers. All the data is freely available via their API.

The goal of this project will be to design and build a full-fledged data ingestion and anomaly detection pipeline:

Data ingestion in real-time from the HTTP API
Data processing to enhance and transform the data according to the needs of the project
Store the data into a suitable real-time database for doing analysis and visualization
Introduce real-time Anomaly Detection to detect any mis-functioning of DNS servers

State of the art technologies need to be evaluated and analyzed to find the better candidates, from the data collection, data processing, data storage and anomaly detection layers.

A fully functional pipeline should be developed, able to ingest RIPE data in real-time and generate alerts.

During this project, the student will acquire theoretical and practical knowledge about Data Processing, Anomaly Detection and Real-Time OLAP databases.

Goals

Design a data processing pipeline for ingesting a high volume of real-time data.
Analyze and select the best suitable technology for storing the high volume of data.
Propose a technology for Anomaly Detection able to learn from past events and automatically report potential anomalies.
Develop appropriate visualizations to showcase the ingested data.
The proposed solution should be scalable to ingest data from Root monitoring, .COM and .NET monitoring.
The performance of the solution should be evaluated in terms of throughput and latency.

Skills

During this project the student will have to work with the following technologies:

Distributed Systems and Data Processing Pipelines
Real-Time Databases
Anomaly Detection
DNS data

[1] https://atlas.ripe.net/docs/getting-started/become-a-host.html

[2] https://atlas.ripe.net/

[3] https://atlas.ripe.net/docs/apis/rest-api-manual/

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