{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T17:49:35Z","timestamp":1774806575640,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea government (MSIT)","award":["NRF-2022R1A2B5B01001190"],"award-info":[{"award-number":["NRF-2022R1A2B5B01001190"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Vehicle ad hoc networks (VANETs) are a vital part of intelligent transportation systems (ITS), offering a variety of advantages from reduced traffic to increased road safety. Despite their benefits, VANETs remain vulnerable to various security threats, including severe blackhole attacks. In this paper, we propose a deep-learning-based secure routing (DLSR) protocol using a deep-learning-based clustering (DLC) protocol to establish a secure route against blackhole attacks. The main features and contributions of this paper are as follows. First, the DLSR protocol utilizes deep learning (DL) at each node to choose secure routing or normal routing while establishing secure routes. Additionally, we can identify the behavior of malicious nodes to determine the best possible next hop based on its fitness function value. Second, the DLC protocol is considered an underlying structure to enhance connectivity between nodes and reduce control overhead. Third, we design a deep neural network (DNN) model to optimize the fitness function in both DLSR and DLC protocols. The DLSR protocol considers parameters such as remaining energy, distance, and hop count, while the DLC protocol considers cosine similarity, cosine distance, and the node\u2019s remaining energy. Finally, from the performance results, we evaluate the performance of the proposed routing and clustering protocol in the viewpoints of packet delivery ratio, routing delay, control overhead, packet loss ratio, and number of packet losses. Additionally, we also exploit the impact of the mobility model such as reference point group mobility (RPGM) and random waypoint (RWP) on the network metrics.<\/jats:p>","DOI":"10.3390\/s23198224","type":"journal-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T11:56:49Z","timestamp":1696247809000},"page":"8224","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Deep-Learning-Based Secure Routing Protocol to Avoid Blackhole Attacks in VANETs"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9828-5431","authenticated-orcid":false,"given":"Amalia","family":"Amalia","sequence":"first","affiliation":[{"name":"Department of Software and Communications Engineering in Graduate School, Hongik University, Sejong City 30016, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7732-7579","authenticated-orcid":false,"given":"Yushintia","family":"Pramitarini","sequence":"additional","affiliation":[{"name":"Department of Software and Communications Engineering in Graduate School, Hongik University, Sejong City 30016, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1680-1190","authenticated-orcid":false,"given":"Ridho Hendra Yoga","family":"Perdana","sequence":"additional","affiliation":[{"name":"Department of Software and Communications Engineering in Graduate School, Hongik University, Sejong City 30016, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4851-0811","authenticated-orcid":false,"given":"Kyusung","family":"Shim","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Applied Mathematics, Hankyong National University, Anseong City 17579, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0587-3754","authenticated-orcid":false,"given":"Beongku","family":"An","sequence":"additional","affiliation":[{"name":"Department of Software and Communications Engineering, Hongik University, Sejong City 30016, Republic of Korea"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101740","DOI":"10.1016\/j.adhoc.2018.08.010","article-title":"On trust models for communication security in vehicular ad-hoc networks","volume":"90","author":"Fan","year":"2019","journal-title":"Ad Hoc Netw."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Malik, A., Khan, M.Z., Faisal, M., Khan, F., and Seo, J.T. 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