{"url":"/dataset/electro-magnetic-emanations-interception","name":"Electro-Magnetic Emanations Interception Dataset","full_name":null,"description_markdown":"An open data corpus of 123.610 labeled samples, \r\n\r\nSource: [Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification](/paper/electro-magnetic-side-channel-attack-through)","description_withheld":null,"homepage":"https://github.com/opendenoising/interception_dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/electro-magnetic-side-channel-attack-through","title":"Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification","first_author":"Florian Lemarchand","url":null},"license":null,"modalities":[],"tasks":[{"name":"Denoising","url":"/task/denoising","datasets_with_task":"/datasets/task/denoising"}],"languages":[],"variants":["Electro-Magnetic Emanations Interception Dataset"],"data_loaders":[{"repo":"https://github.com/opendenoising/interception_dataset","url":"https://github.com/opendenoising/interception_dataset","frameworks":[]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}