Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of David Dagon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Dagon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Dagon more than expected).
This network shows the impact of papers produced by David Dagon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Dagon. The network helps show where David Dagon may publish in the future.
Co-authorship network of co-authors of David Dagon
This figure shows the co-authorship network connecting the top 25 collaborators of David Dagon.
A scholar is included among the top collaborators of David Dagon based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with David Dagon. David Dagon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Dagon, David, et al.. (2018). Wetlands Regulation and Mitigation After the Florida Environmental Reorganization Act of 1993. 8(2). 9.1 indexed citations
Antonakakis, Manos, Roberto Perdisci, Wenke Lee, Nikolaos Vasiloglou, & David Dagon. (2011). Detecting malware domains at the upper DNS hierarchy. USENIX Security Symposium. 27–27.175 indexed citations
7.
Lee, Wenke, Cliff Wang, & David Dagon. (2010). Botnet Detection: Countering the Largest Security Threat. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)).32 indexed citations
8.
Antonakakis, Manos, Roberto Perdisci, David Dagon, Wenke Lee, & Nick Feamster. (2010). Building a dynamic reputation system for DNS. USENIX Security Symposium. 18–18.250 indexed citations
9.
Antonakakis, Manos, Roberto Perdisci, David Dagon, Wenke Lee, & Nick Feamster. (2010). Notos: Building a Dynamic Reputation System for DNS.9 indexed citations
10.
Dagon, David, et al.. (2009). Recursive DNS Architectures and Vulnerability Implications.. Network and Distributed System Security Symposium.19 indexed citations
Dagon, David & Paul Vixie. (2008). Setting DNS's Hair on Fire. USENIX Security Symposium.2 indexed citations
13.
Dagon, David, Chris Lee, Wenke Lee, & Niels Provos. (2008). Corrupted DNS Resolution Paths: The Rise of a Malicious Resolution Authority. Network and Distributed System Security Symposium.69 indexed citations
14.
Lee, Wenke, Cliff Wang, & David Dagon. (2007). Botnet Detection: Countering the Largest Security Threat (Advances in Information Security). Springer eBooks.5 indexed citations
15.
Grizzard, J.B., et al.. (2007). Peer-to-peer botnets: overview and case study. 1–1.222 indexed citations
Ramachandran, Anirudh, Nick Feamster, & David Dagon. (2006). Revealing botnet membership using DNSBL counter-intelligence. 8–8.145 indexed citations
18.
Ramachandran, Anirudh, David Dagon, & Nick Feamster. (2006). Can DNS›Based Blacklists Keep Up with Bots?.64 indexed citations
19.
Dagon, David, Cliff C. Zou, & Wenke Lee. (2006). Modeling Botnet Propagation Using Time Zones.. Network and Distributed System Security Symposium. 12 Suppl D. 99–104.226 indexed citations
20.
Gu, Guofei, Prahlad Fogla, David Dagon, Wenke Lee, & Boris Škorić. (2006). Measuring intrusion detection capability. TU/e Research Portal. 90–101.104 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.