{"created":"2026-02-16T07:18:40.975257+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02007394","sets":["1164:4088:1771221559804:1771221642894"]},"path":["1771221642894"],"owner":"80578","recid":"2007394","title":["コネクテッドカーにおけるネットワークエッジでの異常検出方式の提案"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2026-02-24"},"_buckets":{"deposit":"3e00667c-b966-4f7d-af85-450d242282ec"},"_deposit":{"id":"2007394","pid":{"type":"depid","value":"2007394","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"コネクテッドカーにおけるネットワークエッジでの異常検出方式の提案","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"コネクテッドカーにおけるネットワークエッジでの異常検出方式の提案","subitem_title_language":"ja"},{"subitem_title":"Proposal of Network-Edge-based Anomaly Detection Method for Connected Cars","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"IOT","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2026-02-24","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"トヨタ自動車株式会社"},{"subitem_text_value":"トヨタ自動車株式会社"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/2007394/files/IPSJ-IOT26072017.pdf","label":"IPSJ-IOT26072017.pdf"},"date":[{"dateType":"Available","dateValue":"2028-02-24"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IOT26072017.pdf","filesize":[{"value":"318.9 KB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"43"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"35a7ade4-672f-4a1b-8884-558d90b8f307","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2026 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大野,允裕"}]},{"creatorNames":[{"creatorName":"伊藤,雅典"}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12326962","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8787","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"コネクテッドカーの普及により、車両追跡技術を活用した盗難検出が可能となり、盗難車両の発見や検挙率が向上してきている。しかし近年、リレーアタックやCAN通信への攻撃など手口が高度化しており、従来のセンター集中処理では迅速な対応が困難になりつつある。本稿では、ネットワークエッジでの異常検出方式を提案する。提案方式は、車両から送信される複数のセンサーデータをエッジサーバで受信し、ベイズ推論を組み合わせた段階的判定フローにより、機器故障、通信異常、盗難の異常要因を推定し、センター集中処理と比較して判定遅延と通信負荷を低減する。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The proliferation of connected cars has enabled theft detection using vehicle tracking technology, contributing to improved recovery and arrest rates for stolen vehicles. However, attack methods have become increasingly sophisticated in recent years, including relay attacks and CAN bus intrusions, making it difficult for conventional center-centric processing to respond quickly due to detection latency. This paper proposes a network-edge-based anomaly detection method. The proposed method receives multiple sensor data from vehicles at edge servers and estimates anomaly causes such as device fault, communication anomalies, and theft through a stepwise decision flow combining Bayesian inference, reducing detection latency and network traffic compared to centralized processing.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告インターネットと運用技術（IOT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2026-02-24","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"17","bibliographicVolumeNumber":"2026-IOT-72"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"id":2007394,"updated":"2026-02-16T07:50:11.542359+00:00","links":{}}