The DOI matches its Crossref record.
Proceedings of the Internet Measurement Conference
Abstract
This year, IMC received 197 submissions, 118 of which were full papers (60%) with the remaining being short submissions. Geographically, the distribution of papers included 47% from submitted by USA based first authors, 32% from Europe, 16% from Asia, and the remainder from other locations. 73% of submissions were authored by individuals from academia, while 22% of submissions came from a mix of academic and commercial authors. A remaining 5% of submitted papers had all commercial authors. Among the set of self-reported topics, security, web, measurement platforms, infrastructure and machine learning were the five most common topics for the submitted papers.
Overview
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Citations
Cited by
The Role of Machine Learning in Cybersecurity
Apruzzese, G., Laskov, P., Montes de Oca, E., Mallouli, W., Brdalo Rapa, L., Grammatopoulos, A. V., & Di Franco, F. (2023) · Digital Threats: Research and Practice · doi:10.1145/3545574 · Cited by 279
Decentralized social networks and the future of free speech online
Huang, T. (2024) · Computer Law & Security Review · doi:10.1016/j.clsr.2024.106059 · Cited by 15
Metadata
- Publisher
- ACM
- Published
- 2019-10-21
- OpenAlex
- W2917878349
- Cited by
- 190
- References
- 0
- Type
- paratext
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- The paper
- Proceedings of the Internet Measurement Conference. (2019). https://doi.org/10.1145/3355369
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.