Exposure: A Passive DNS Analysis Service to Detect and Report Malicious Domains

By Leyla Bilge, Sevil Şen, Davide Balzarotti, Engin Kirda, Christopher Krügel. TSEC, 2014

332 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/9aa0ef94e47d6855aa28bb9c2cdc5453e1ae8a1d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Erhan Guven
2. Anna L. Buczak
3. André Costa Drummond
4. Paulo Angelo Alves Resende

In Computer Networks and Communications

1. Erhan Guven
2. Anna L. Buczak
3. André Costa Drummond
4. Paulo Angelo Alves Resende

In Information Systems

1. Erhan Guven
2. Anna L. Buczak

Citations in the corpus

• A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection (2016, background): “2) Anomaly Detection and Hybrid Detection EXPOSURE [56],[57] is a system that employs large-scale, passive Domain Name Service (DNS) analysis techniques to detect domains that are involved in malicious activity.”