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Thomas Daniels 0002

dblp:00/1175-2 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
0009-0007-2929-2077ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Security and privacy · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Web and mobile security · 55% Network security · 45%
Computer networks
2 papers
Network measurement and analytics · 74% Network management and operations · 26%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and mobile security
phishing
1.622025
RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations · KDD (2) 2025
Characterizing and Mitigating Phishing Attacks at ccTLD Scale · CCS 2024
Network security › protocol security › DNS security
malicious domain detection
1.122025
RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations · KDD (2) 2025
Characterizing and Mitigating Phishing Attacks at ccTLD Scale · CCS 2024
Network security › intrusion detection and prevention › intrusion detection
proactive detection
0.912025
RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations · KDD (2) 2025
Network measurement and analytics
web measurement
0.812024
Characterizing and Mitigating Phishing Attacks at ccTLD Scale · CCS 2024
Web and mobile security › phishing
phishing prevention
0.812024
Characterizing and Mitigating Phishing Attacks at ccTLD Scale · CCS 2024

Methods — techniques the papers use, named apart from their topics

machine learning classifier · 1.7measurement study · 1.5
YearPublicationVenuePosition
2025 RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations
abstract
Miscreants use domain names for malicious purposes such as phishing websites or fake webshops. Reactive approaches such as blocklists play an important role in fighting such abuse but have limitations, namely that the domains are typically only included in such a list after abuse has been reported (e.g., there may already be some victims). We propose RegCheck, a system designed to proactively flag suspicious domains at registration time. The core of RegCheck is a machine learning classifier that assesses the risk that the domain name will be used for malicious purposes based on characteristics known at the time of registration. Based on this assessment, it flags some registrations and requires them to undergo additional verification prior to the domain name being activated. The system has been developed collaboratively between SIDN (.nl) and DNS Belgium (.be) and has been deployed as a real-time system at the .be registry since March 2024. Since its deployment, the registry has witnessed a decrease in the number of .be domain name registrations that have been revoked for breaching the terms and conditions, indicating a decline in the number of active malicious registrations.
Thomas Daniels 0002, Maarten Bosteels, Pieter Robberechts, Jesse Davis
KDD (2)1
2024 Characterizing and Mitigating Phishing Attacks at ccTLD Scale
abstract
International audience
Giovane Cesar Moreira Moura, Thomas Daniels 0002, Maarten Bosteels, Sebastian Castro, Thymen Wabeke, Thijs van Den Hout, Maciej Korczynski, Georgios Smaragdakis
CCS2