diff --git a/i2p2www/pages/papers/anonbib.bib b/i2p2www/pages/papers/anonbib.bib
index 00cd00c507893f2f60b4d10032afed30c47902c4..0c62dd26c0b142020106b2f629c013eb9449a20c 100644
--- a/i2p2www/pages/papers/anonbib.bib
+++ b/i2p2www/pages/papers/anonbib.bib
@@ -100,6 +100,20 @@
   www_pdf_url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8537903},
 }
 
+@article{interconnection-between-darknets,
+  author={L. Ye and X. Yu and J. Zhao and D. Zhan and X. Du and M. Guizani},
+  journal={EEE INTERNET COMPUTING},
+  title={Interconnection between darknets},
+  year={2020},
+  month={December},
+  volume={1},
+  abstract={Tor and i2p networks are two of the most popular darknets. Both darknets have become an area of illegal activities highlighting the necessity to study and analyze them to identify and report illegal content to Law Enforcement Agencies (LEAs). This paper analyzes the connections between the Tor network and the i2p network. We created the first dataset that combines information from Tor and i2p networks. The dataset contains more than 49k darknet services. The process of building and analyzing the dataset shows that it is not possible to explore one of the networks without considering the other. Both networks work as an ecosystem and there are clear paths between them. Using graph analysis, we also identified the most relevant domains, the prominent types of services in each network, and their relations. Findings are relevant to LEAs and researchers aiming to crawl and investigate i2p and Tor networks.},
+  keywords={Tor, i2p, Darknet, Graph Analysis, Dataset},
+  doi={10.1109/MIC.2020.3037723},
+  ISSN={2169-3536},
+  www_section = comm,
+  www_pdf_url = {https://arxiv.org/pdf/2012.05003},
+}
 
 @mastersthesis{smits2018:i2p-enhanced-outproxy,
   title = {Risk Assessment for I2P With an Enhanced Outproxy Design},