TY - GEN A1 - Vallina, Pelayo A1 - Le Pochat, Victor A1 - Feal, Álvaro A1 - Paraschiv, Marius A1 - Gamba, Julien A1 - Burke, Tim A1 - Hohlfeld, Oliver A1 - Tapiador, Juan A1 - Vallina-Rodriguez, Narseo T1 - Mis-shapes, Mistakes, Misfits: An Analysis of Domain Classification Services T2 - ACM Internet Measurement Conference 2020, IMC ’20, October 27–29, 2020, Virtual Event, USA N2 - Domain classification services have applications in multiple areas,including cybersecurity, content blocking, and targeted advertising.Yet, these services are often a black box in terms of their method-ology to classifying domains, which makes it difficult to assesstheir strengths, aptness for specific applications, and limitations. Inthis work, we perform a large-scale analysis of 13 popular domainclassification services on more than 4.4M hostnames. Our studyempirically explores their methodologies, scalability limitations,label constellations, and their suitability to academic research aswell as other practical applications such as content filtering. Wefind that the coverage varies enormously across providers, rangingfrom over 90% to below 1%. All services deviate from their docu-mented taxonomy, hampering sound usage for research. Further,labels are highly inconsistent across providers, who show littleagreement over domains, making it difficult to compare or combinethese services. We also show how the dynamics of crowd-sourcedefforts may be obstructed by scalability and coverage aspects aswell as subjective disagreements among human labelers. Finally,through case studies, we showcase that most services are not fitfor detecting specialized content for research or content-blockingpurposes. We conclude with actionable recommendations on theirusage based on our empirical insights and experience. Particularly,we focus on how users should handle the significant disparitiesobserved across services both in technical solutions and in research. KW - Network KW - Network measurement KW - Information systems KW - Clustering and classification KW - Web applications KW - Web searching and information discovery Y1 - 2020 UR - https://eprints.networks.imdea.org/2183/1/paper.pdf SN - 978-1-4503-8138-3 U6 - https://doi.org/10.1145/3419394.3423660 SP - 598 EP - 618 ER - TY - GEN A1 - Feal, Álvaro A1 - Vallina, Pelayo A1 - Gamba, Julien A1 - Pastrana, Sergio A1 - Nappa, Antonio A1 - Hohlfeld, Oliver A1 - Vallina-Rodriguez, Narseo A1 - Tapiador, Juan T1 - Blocklist Babel: On the Transparency and Dynamics of Open Source Blocklisting T2 - IEEE Transactions on Network and Service Management N2 - Blocklists constitute a widely-used Internet security mechanism to filter undesired network traffic based on IP/domain reputation and behavior. Many blocklists are distributed in open source form by threat intelligence providers who aggregate and process input from their own sensors, but also from thirdparty feeds or providers. Despite their wide adoption, many open-source blocklist providers lack clear documentation about their structure, curation process, contents, dynamics, and interrelationships with other providers. In this paper, we perform a transparency and content analysis of 2,093 free and open source blocklists with the aim of exploring those questions. To that end, we perform a longitudinal 6-month crawling campaign yielding more than 13.5M unique records. This allows us to shed light on their nature, dynamics, inter-provider relationships, and transparency. Specifically, we discuss how the lack of consensus on distribution formats, blocklist labeling taxonomy, content focus, and temporal dynamics creates a complex ecosystem that complicates their combined crawling, aggregation and use. We also provide observations regarding their generally low overlap as well as acute differences in terms of liveness (i.e., how frequently records get indexed and removed from the list) and the lack of documentation about their data collection processes, nature and intended purpose. We conclude the paper with recommendations in terms of transparency, accountability, and standardization. Y1 - 2021 U6 - https://doi.org/10.1109/TNSM.2021.3075552 SN - 1932-4537 PB - IEEE ER - TY - GEN A1 - Moreno, José Miguel A1 - Pastrana, Sergio A1 - Reelfs, Jens Helge A1 - Vallina, Pelayo A1 - Panchenko, Andriy A1 - Smaragdakis, Georgios A1 - Hohlfeld, Oliver A1 - Vallina-Rodriguez, Narseo A1 - Tapiador, Juan T1 - Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls N2 - During the first days of the 2022 Russian invasion of Ukraine, Russia’s media regulator blocked access to many global social media platforms and news sites, including Twitter, Facebook, and the BBC. To bypass the information controls set by Russian authorities, pro-Ukrainian groups explored unconventional ways to reach out to the Russian population, such as posting war-related content in the user reviews of Russian business available on Google Maps or Tripadvisor. This paper provides a first analysis of this new phenomenon by analyzing the creative strategies to avoid state censorship. Specifically, we analyze reviews posted on these platforms from the beginning of the conflict to September 2022. We measure the channeling of war messages through user reviews in Tripadvisor and Google Maps, as well as in VK, a popular Russian social network. Our analysis of the content posted on these services reveals that users leveraged these platforms to seek and exchange humanitarian and travel advice, but also to disseminate disinformation and polarized messages. Finally, we analyze the response of platforms in terms of content moderation and their impact. KW - Side Channels KW - Disinformation KW - Propaganda KW - User-Generated Content KW - Russia KW - Ukraine KW - Tripadvisor KW - Google Maps KW - VKontakte Y1 - 2023 UR - https://arxiv.org/abs/2302.00598 U6 - https://doi.org/10.48550/arXiv.2302.00598 ER -