{"as_of":"2026-08-22T06:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b5dbcd17060b3173d005e734955f7fcc7082cb06c61d2298c172786eb9848fa2","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T18:58:58.753205Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.08473/citation-record","integrity":"/paper/2606.08473/integrity","json":"/paper/2606.08473/citation-record.json","paper":"/paper/2606.08473"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"When The Lights Went Out: A Comprehensive Review Of The 2015 Attacks On Ukrainian Critical Infrastructure,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:990a092479a6961aa7eb82ecd547d075ef7fc8839c3a06d556aa665baea8bf74","observation_id":"32e5d04c-cf84-4ef5-a467-16c28e3a158f","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"US accuses Russia of cyberattacks on power grid,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:9e33774d473fec2b3197c82ceebc6e4bd9e77f356668064895f83747cd4c3a24","observation_id":"b09ebdaf-c332-4cb3-a149-cb540ca27f2d","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Available: https://www.cnn.com/2018/03/15/politics/ dhs-fbi-russia-power-grid/index.html","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:66e66b70712e28faed71558c4766adf20e6aa6db4cf6463cc6a521a61b6b882c","observation_id":"8957403e-ca45-45ea-8c27-7c4e537df5ed","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Significant Cyber Incidents,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:333b27ac0787e12dde9aa881a2fbfb978ae7b1b492c225f8c012cd44d3fe41d3","observation_id":"2b455e82-4a23-481a-8225-1b99c68884fe","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Data integrity attacks against outage manage- ment systems,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:c79eb33a54a8b30c655449def095fdd60ab0d774faa735ccead96027a653ab7d","observation_id":"c3b04251-78c6-41c7-931c-5d53881e2711","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Modified grey wolf optimization approach for power system transmission line congestion management based on the influence of solar photovoltaic system,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:c64cd9da9bb0b19f2bc95cb86e8f33e9c2466cbceafdb0eb9c8a8943677129ef","observation_id":"7fa4203e-d5fa-4e41-954a-d56f99e4b9d5","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"False data injection attacks against synchronization systems in microgrids,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:e31923b629e74fc5ab2bd3280529633552bf36571bbbaac9bbd9bdb502aef594","observation_id":"f7a8fa2f-024f-48a7-b33e-e0ea3a406131","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Impact analysis of topology poisoning attacks on economic operation of the smart power grid,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:53aa836ca5fe616d2de6f23e5c6ea8ce060eaf29a0d90bdf4215ed7c9b7b59b9","observation_id":"d55db40a-6432-4d7d-a571-438fd836e7ae","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.10587","last_updated":"2021-02-21T11:39:17Z","snapshot_observed_at":"2026-08-17T05:11:35.062645Z","submitted_at":"2021-02-21T11:39:17Z","title":"False Data Injection Attack Against Power System Small-Signal Stability","version":1},"cited_work":{"arxiv_id":"2102.10587","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2102.10587","snapshot_observed_at":"2026-07-02T22:27:25.362759Z","title":"False data injection attack against power system small-signal stability,","venue":null,"work_id":"6e69f570-7bca-4b39-ac36-1be0100dceb2","year":2021},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"cited_paper":"/paper/2102.10587","citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:01a56f878001353c3c181bcc169092d110f33b09bd7ba470b8adbf4caee58f87","observation_id":"3abdeb40-320a-41fa-b448-289653d1da5f","resolution":{"observed_at":"2026-07-02T22:27:25.364305Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Detection of false data injection attacks in a smart grid based on wls and an adaptive interpolation extended kalman filter,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:4f15f8e6386f2cbcbc33451b6cca1b9aeae3b1030ae2d94a4b7f6f998393fa4f","observation_id":"90fde04b-c67c-44b0-beca-0998925d5736","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Abur and A","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:542a13227bc0e1a501084ac9c6b9f4e770fbb5155ff2111078b5f1355be9e514","observation_id":"9ca745a7-d4ce-4fb8-a54d-2fa31eaeb9d2","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Ensuring cybersecurity of smart grid against data integrity attacks under concept drift,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:09b8b1bfae0c322c7ea8960ea7f0d887e03340f5b660935e81d33a8f26dc4f1d","observation_id":"a0096c55-5a37-47f0-8e38-3bc9b3c760be","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Detecting bi-level false data injection attack based on time series analysis method in smart grid,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:eb1f44921addef2dae63a174d7472194ef7e5c520923f7a78638116be5ca9a87","observation_id":"3bd3ce27-6bc8-4e29-a2a6-fcc38dafdead","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"(2023) Deep signal anomaly detector","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:eb4d4832e8477eca539bbe8073a4823c093d8d65581ea2d9ace5af10701ecb20","observation_id":"83229825-b809-44a9-a09e-4bd0752436d7","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Joint detection and localization of stealth false data injection attacks in smart grids using graph neural networks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:b4730af07ca1a89c208e35a5fba30dc7c7c52cf3c859ccf4ca2c248e629427bb","observation_id":"aaa3afd2-9bcd-4c89-960f-0f59230c5b03","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Generalized graph neural network-based detection of false data injection attacks in smart grids,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:f2f705722482bf53de03dd74ac568febe78f442d18397dc9749dc1906a478c8f","observation_id":"11760aaa-c56e-4eb1-9296-7c9663767886","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"False data injection attacks against state estimation in electric power grids,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:023699505343463e879b72ea731386e85a58024c8982c8449204306e3f52cd2c","observation_id":"9377f58f-d62d-4863-8a11-536b856b2b87","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Subspace methods for data attack on state estimation: A data driven approach,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:88507669f6e941685903f3c8696e1246c8c95a26dceffe287a523670883e6601","observation_id":"8cd24efb-be51-493a-909f-e579089200c3","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Blind false data injection attack using pca approximation method in smart grid,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:c4c72e12e9bacae0939490aa8aaf3c3b7cc789788f6b0ee40fcea683954f8828","observation_id":"85bf2918-d895-4a8c-8011-c066685d797d","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Modeling and perfor- mance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:f1e39a39919f45b62955e3e010385dafcffb3a2f3c91ae9131fb3d52251c87ea","observation_id":"9ab9c407-1a59-4925-bc2f-eef65a51f510","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Finding the worse case: Undetectable false data injection with minimized knowledge and resource,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:2771e1f7b52969240547c03c1f84cd23d92147938d62adcb935ab5fe4d9aad62","observation_id":"ac34b758-d13b-4491-8a22-00cf3019fa9b","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Self-attention spatio-temporal deep collaborative network for robust fdia detection in smart grids","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:a0f31ff76c1e4166e19d2a7d2209eac76a79012d81cfa743862cccdd315abc69","observation_id":"f3d61d34-f7ec-4021-b150-da0df7161313","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:23dcecbaada01542731749dfad60a9ac2aae8addadf16fa3db9d7aa4055bfbd5","observation_id":"4fbfa9d9-d7a1-42ca-b8f6-0fd2e70bd186","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Blind false data injection attacks against state estimation based on matrix reconstruction,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:136708487968ac3c29a9ef415ffdf14bd093ddbc0a2ac398b799ef5f8e22669f","observation_id":"3e5ebf19-e28d-4276-ad4d-fa78d292b096","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Detection of false data injection attacks using the autoencoder approach,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:35dbdbd4934f8e9c096c2f305b91f5eae462b3e3d9e46b04b95d2f3a09bf4d73","observation_id":"cca2ddbf-c16a-4c7e-84f8-1cf19db1cde3","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"False data injection attack with minimal network infor- mation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:46795947e9abd031fb652d9fc785dfb980dd87731e5330df645e3f57ed7e57ef","observation_id":"fdba3c47-4aae-4207-84b3-e5519e3feb37","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Attack power system state estima- tion by implicitly learning the underlying models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:807b68b042adff6508c830da95fadc642ee824915f88aa1a15fb95d6d94d8701","observation_id":"10ff6ec0-a8ae-42b1-b5b9-a1a5c2779077","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Vulnerability assessment of ac state estimation with respect to false data injection cyber-attacks,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:78d8939ed28cfff80aa6b5d1104c98b87ce47aa0625551d33425454b1e573a86","observation_id":"1b0dc4bf-ae5a-40b6-a05d-15adf8996f3a","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Machine learning- based techniques for false data injection attacks detection in smart grid: a review,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:be6e8f6b84692444b7432d95f48ec78381b4957aa24f9e0d25a506f8bd15ea81","observation_id":"ab2d4c61-14c3-4d83-b8ad-e26421089b83","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"False data injection attacks (fdia) detection by deep learning techniques in smart grids: survey,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:50816207f37a2d056b1726e5dd5fbf99692cbbdb156af73c6499f1174bdfb706","observation_id":"22283883-dde1-40d8-9b2d-b6e426e08323","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"A useful variant of the davis– kahan theorem for statisticians,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:ea883c6011e8fc03d24d493c4043ed281e2bfebcc67335408f6500d0b9dafd47","observation_id":"6767c5da-0a91-4165-8b00-a56069eda60c","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Minimum cross entropy thresholding,","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:fede10632dfc071375ae190cf27dff9f4fbe7a1b3f4115a7777e24ea991edb0d","observation_id":"0b40a90d-191f-461b-ab3a-0e8158452b6d","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"An iterative algorithm for minimum cross entropy thresholding,","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:abe401eb62835d80c6a1be480d6c2dfceade1492e65a9578dd8f3d2bdc308870","observation_id":"2211b4e4-7dc1-4003-a0f2-9523c0adb4fc","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Fast low-rank modifications of the thin singular value decomposition,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:c53fd78e9d926b12077bf04f7b746a94a56b020a6c0f03cb97dacff89aa26fa0","observation_id":"f40384d5-3ba9-4349-9f0c-7dbd6fdbb249","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Mat- power: Steady-state operations, planning, and analysis tools for power systems research and education,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:8bab76b88a480d7384f9c1241154f61a7856727bf8b7eae98b1370d4e29d8bb0","observation_id":"8d000af1-582b-4227-99ab-6fd761ab2d45","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Privacy-preserving line outage detec- tion in distribution grids: An efficient approach with uncompromised performance,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:e40e50037ac9aa8508d9dd721eab4f801660ec047713323afd6781290862deed","observation_id":"a8814c9f-3074-4b1a-9d68-cd5f293a91fa","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:2fb7a5ac063d8819737517494431477e9a5b63a98f1672154fec9b8977d00d1d","observation_id":"6e341221-151a-4b0a-ab46-c359c7d934d5","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Xtm: A novel transformer and lstm-based model for de- tection and localization of formally verified fdi attack in smart grid,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:a6f4300c1c37f9acfda1e26b36bd7f508a76d3221cec9c75f3c68cb304d9b7ab","observation_id":"57b79e6d-0d32-4b08-9ac5-e8255ec06bd8","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Vulnerability of the load frequency control against the network parameter attack,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:2f0d62026d1e6f321939fd823bdc1f7b56b751bb78e383e80de758628c857905","observation_id":"ba6367e4-2c27-4a70-9441-e56450c203b9","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:58:58.753205Z","title":"Integrity data attacks in power market operations,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-27T18:58:58.753205Z"},"links":{"citing_paper":"/paper/2606.08473"},"observation_digest":"sha256:751e2b199d453c44731fd3570179edf1d3c4a1cc75af7c5e33c00eec4d1ea2f2","observation_id":"2741dd3e-6110-44d1-bb87-d290de559688","resolution":{"observed_at":"2026-06-27T18:58:58.753205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.08473","last_updated":"2026-06-07T06:39:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T15:55:26.368498Z","submitted_at":"2026-06-07T06:39:09Z","title":"Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":39,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":40},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2606.08473."}