{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T22:43:11Z","timestamp":1792622591753,"version":"4.5.0"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62374146"],"award-info":[{"award-number":["62374146"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92373205"],"award-info":[{"award-number":["92373205"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFB4404404"],"award-info":[{"award-number":["2023YFB4404404"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022963","name":"Key Research and Development Program of Zhejiang Province","doi-asserted-by":"publisher","award":["2024C01012"],"award-info":[{"award-number":["2024C01012"]}],"id":[{"id":"10.13039\/100022963","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Systems Architecture"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1016\/j.sysarc.2025.103646","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T23:00:53Z","timestamp":1763766053000},"page":"103646","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["EF-IDS: An efficient intrusion detection system with enriched features for CAN bus in modern vehicles"],"prefix":"10.1016","volume":"171","author":[{"given":"Aya","family":"El-Fatyany","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2263-5643","authenticated-orcid":false,"given":"Xiaohang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kui","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.sysarc.2025.103646_b1","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1109\/JPROC.2005.849725","article-title":"Trends in automotive communication systems","volume":"93","author":"Navet","year":"2005","journal-title":"Proc. IEEE"},{"issue":"7","key":"10.1016\/j.sysarc.2025.103646_b2","doi-asserted-by":"crossref","first-page":"6123","DOI":"10.1109\/TITS.2021.3078740","article-title":"A survey of attacks on controller area networks and corresponding countermeasures","volume":"23","author":"Jo","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.sysarc.2025.103646_b3","doi-asserted-by":"crossref","unstructured":"G. Bloom, WeepingCAN: A stealthy CAN bus-off attack, in: Workshop on Automotive and Autonomous Vehicle Security, 2021.","DOI":"10.14722\/autosec.2021.23002"},{"issue":"17","key":"10.1016\/j.sysarc.2025.103646_b4","doi-asserted-by":"crossref","first-page":"15593","DOI":"10.1109\/JIOT.2022.3151377","article-title":"ClockIDS: A real-time vehicle intrusion detection system based on clock skew","volume":"9","author":"Zhao","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.sysarc.2025.103646_b5","doi-asserted-by":"crossref","unstructured":"H. Lee, S.H. Jeong, H.K. Kim, OTIDS: A novel intrusion detection system for in-vehicle network by using remote frame, in: Proc. Conf. Privacy, Security and Trust, PST, 2017, pp. 57\u20135709.","DOI":"10.1109\/PST.2017.00017"},{"key":"10.1016\/j.sysarc.2025.103646_b6","article-title":"In-vehicle network intrusion detection using deep convolutional neural network","volume":"21","author":"Song","year":"2020","journal-title":"Veh. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b7","article-title":"Rec-CNN: In-vehicle networks intrusion detection using convolutional neural networks trained on recurrence plots","volume":"35","author":"Desta","year":"2022","journal-title":"Veh. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b8","doi-asserted-by":"crossref","unstructured":"A. Taylor, S. Leblanc, N. Japkowicz, Anomaly detection in automobile control network data with long short-term memory networks, in: Proc. Int\u2019L Conf. IEEE Data Science and Advanced Analytics, 2016, pp. 130\u2013139.","DOI":"10.1109\/DSAA.2016.20"},{"issue":"7","key":"10.1016\/j.sysarc.2025.103646_b9","doi-asserted-by":"crossref","first-page":"4507","DOI":"10.1109\/TITS.2020.3017882","article-title":"Novel deep learning-enabled LSTM autoencoder architecture for discovering anomalous events from intelligent transportation systems","volume":"22","author":"Ashraf","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.sysarc.2025.103646_b10","doi-asserted-by":"crossref","first-page":"124931","DOI":"10.1109\/ACCESS.2021.3110524","article-title":"Intrusion detection method using bi-directional GPT for in-vehicle controller area networks","volume":"9","author":"Nam","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.sysarc.2025.103646_b11","first-page":"52","article-title":"Anomaly intrusion detection method for vehicular networks based on survival analysis","volume":"14","author":"Han","year":"2018","journal-title":"Veh. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b12","doi-asserted-by":"crossref","unstructured":"S. Zhuo, N. Li, K. Ren, HistCAN: A real-time CAN IDS with enhanced historical traffic learning capability, 2024.","DOI":"10.14722\/vehiclesec.2024.23028"},{"key":"10.1016\/j.sysarc.2025.103646_b13","article-title":"A hybrid deep learning based intrusion detection system using spatial-temporal representation of in-vehicle network traffic","volume":"35","author":"Lo","year":"2022","journal-title":"Veh. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.comcom.2014.04.012","article-title":"False alarm minimization techniques in signature-based intrusion detection systems: A survey","volume":"49","author":"Hubballi","year":"2014","journal-title":"Comput. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b15","doi-asserted-by":"crossref","unstructured":"F. Zhang, D. Wang, An effective feature selection approach for network intrusion detection, in: Proc. Int\u2019L. Conf. Networking, Architecture and Storage, 2013, pp. 307\u2013311.","DOI":"10.1109\/NAS.2013.49"},{"key":"10.1016\/j.sysarc.2025.103646_b16","article-title":"CAVIDS: Real time intrusion detection system for connected autonomous vehicles using logical analysis of data","volume":"43","author":"Kumar","year":"2023","journal-title":"Veh. Commun."},{"key":"10.1016\/j.sysarc.2025.103646_b17","doi-asserted-by":"crossref","unstructured":"K.T. Cho, K.G. Shin, Viden: Attacker identification on in-vehicle networks, in: Proc. Int\u2019L. Conf. ACM SIGSAC on Computer and Communications Security, 2017, pp. 1109\u20131123.","DOI":"10.1145\/3133956.3134001"},{"key":"10.1016\/j.sysarc.2025.103646_b18","doi-asserted-by":"crossref","unstructured":"M. Kneib, C. Huth, Scission: Signal characteristic-based sender identification and intrusion detection in automotive networks, in: Proc. Int\u2019L. Conf. ACM SIGSAC on Computer and Communications Security, 2018, pp. 787\u2013800.","DOI":"10.1145\/3243734.3243751"},{"key":"10.1016\/j.sysarc.2025.103646_b19","unstructured":"J. Shin, H. Kim, S. Lee, W. Choi, D.H. Lee, H.J. Jo, {RIDAS}: Real-time identification of attack sources on controller area networks, in: Proc. Int\u2019L. Conf. USENIX Security Symposium, 2023, pp. 6911\u20136928."},{"issue":"16","key":"10.1016\/j.sysarc.2025.103646_b20","doi-asserted-by":"crossref","first-page":"12518","DOI":"10.1109\/JIOT.2020.3032935","article-title":"A cluster-based multidimensional approach for detecting attacks on connected vehicles","volume":"8","author":"D\u2019Angelo","year":"2020","journal-title":"IEEE Internet Things J."},{"issue":"3","key":"10.1016\/j.sysarc.2025.103646_b21","doi-asserted-by":"crossref","first-page":"2366","DOI":"10.1109\/TITS.2021.3088998","article-title":"Histogram-based intrusion detection and filtering framework for secure and safe in-vehicle networks","volume":"23","author":"Derhab","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.sysarc.2025.103646_b22","doi-asserted-by":"crossref","first-page":"127580","DOI":"10.1109\/ACCESS.2019.2937576","article-title":"An intelligent secured framework for cyberattack detection in electric vehicles\u2019 CAN bus using machine learning","volume":"7","author":"Avatefipour","year":"2019","journal-title":"IEEE Access"},{"issue":"11","key":"10.1016\/j.sysarc.2025.103646_b23","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.3390\/s24113461","article-title":"Multi-attack intrusion detection for in-vehicle CAN-FD messages","volume":"24","author":"Gao","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.sysarc.2025.103646_b24","doi-asserted-by":"crossref","first-page":"82402","DOI":"10.1109\/ACCESS.2024.3412933","article-title":"Intrusion detection system for in-vehicle can-fd bus id based on gan model","volume":"12","author":"Wang","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.sysarc.2025.103646_b25","series-title":"2023 4th International Conference on Intelligent Technologies","first-page":"1","article-title":"Enhancing CAN-FD security with an ensemble learning approach for intrusion detection","author":"Sreelekshmi","year":"2024"},{"key":"10.1016\/j.sysarc.2025.103646_b26","doi-asserted-by":"crossref","unstructured":"M.R. Moore, R.A. Bridges, F.L. Combs, M.S. Starr, S.J. Prowell, Modeling inter-signal arrival times for accurate detection of can bus signal injection attacks: a data-driven approach to in-vehicle intrusion detection, in: Proc. Int\u2019L. Conf. Cyber and Information Security Research, 2017, pp. 1\u20134.","DOI":"10.1145\/3064814.3064816"},{"key":"10.1016\/j.sysarc.2025.103646_b27","first-page":"25","article-title":"Car hacking and defense competition on in-vehicle network","volume":"vol. 2021","author":"Kang","year":"2021"},{"key":"10.1016\/j.sysarc.2025.103646_b28","unstructured":"V. Nair, G.E. Hinton, Rectified linear units improve restricted boltzmann machines, in: Proc. Int\u2019L. Conf. Machine Learning, 2010, pp. 807\u2013814."},{"issue":"1","key":"10.1016\/j.sysarc.2025.103646_b29","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.sysarc.2025.103646_b30","article-title":"Adam: A method for stochastic optimization 3rd international conference on learning representations","volume":"vol. 1","author":"Kingma","year":"2015"},{"key":"10.1016\/j.sysarc.2025.103646_b31","article-title":"A theoretically grounded application of dropout in recurrent neural networks","volume":"vol. 29","author":"Gal","year":"2016"},{"key":"10.1016\/j.sysarc.2025.103646_b32","doi-asserted-by":"crossref","unstructured":"G. Kumar, K. Kumar, AI based supervised classifiers: an analysis for intrusion detection, in: Proc. Int\u2019L. Conf. Advances in Computing and Artificial Intelligence, 2011, pp. 170\u2013174.","DOI":"10.1145\/2007052.2007087"},{"issue":"3","key":"10.1016\/j.sysarc.2025.103646_b33","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1007\/s00500-021-06532-4","article-title":"Importance-SMOTE: a synthetic minority oversampling method for noisy imbalanced data","volume":"26","author":"Liu","year":"2022","journal-title":"Soft Comput."},{"key":"10.1016\/j.sysarc.2025.103646_b34","series-title":"Machine Learning and Deep Learning in Real-Time Applications","first-page":"33","article-title":"Deep leaning using keras","author":"Joshi","year":"2020"},{"key":"10.1016\/j.sysarc.2025.103646_b35","doi-asserted-by":"crossref","unstructured":"E. Seo, H.M. Song, H.K. Kim, GIDS: GAN based intrusion detection system for in-vehicle network, in: Proc. Conf. Privacy, Security and Trust, 2018, pp. 1\u20136.","DOI":"10.1109\/PST.2018.8514157"},{"key":"10.1016\/j.sysarc.2025.103646_b36","doi-asserted-by":"crossref","first-page":"55389","DOI":"10.1109\/ACCESS.2023.3282110","article-title":"Transformer-based attention network for in-vehicle intrusion detection","volume":"11","author":"Nguyen","year":"2023","journal-title":"IEEE Access"},{"issue":"2","key":"10.1016\/j.sysarc.2025.103646_b37","doi-asserted-by":"crossref","first-page":"1484","DOI":"10.1109\/TVT.2019.2961344","article-title":"SAIDuCANT: Specification-based automotive intrusion detection using controller area network (CAN) timing","volume":"69","author":"Olufowobi","year":"2019","journal-title":"IEEE Trans. Veh. Technol."}],"container-title":["Journal of Systems Architecture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1383762125003182?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1383762125003182?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T19:44:08Z","timestamp":1773863048000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1383762125003182"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":37,"alternative-id":["S1383762125003182"],"URL":"https:\/\/doi.org\/10.1016\/j.sysarc.2025.103646","relation":{},"ISSN":["1383-7621"],"issn-type":[{"value":"1383-7621","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"EF-IDS: An efficient intrusion detection system with enriched features for CAN bus in modern vehicles","name":"articletitle","label":"Article Title"},{"value":"Journal of Systems Architecture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sysarc.2025.103646","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103646"}}