{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T23:14:59Z","timestamp":1768691699480,"version":"3.49.0"},"reference-count":27,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:00:00Z","timestamp":1653955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Routing security attacks in Vehicular Ad hoc Networks (VANETs) represent a challenging issue that may dramatically decrease the network performances and even cause hazardous damage in both lives and equipment. This study proposes a new approach named Multivariate Statistical Detection Scheme (MVSDS), capable of detecting routing security attacks in VANETs based on statistical techniques, namely the multivariate normality tests (MVN). Our detection approach consists of four main stages: first, we construct the input data by monitoring the network traffic in real time based on multiple metrics such as throughput, dropped packets ratio, and overhead traffic ratio. Secondly, we normalize the collected data by applying three different rescaling techniques, namely the Z-Score Normalization (ZSN), the Min-Max Normalization (MMN), and the Normalization by Decimal Scaling (NDS). The resulting data are modeled by a multivariate dataset sampled at different times used as an input by the detection step. The next step allows separating legitimate behavior from malicious one by continuously verifying the conformity of the dataset to the multivariate normality assumption by applying the Rao\u2013Ali test combined with the Ryan\u2013Joiner test. At the end of this step, the Ryan\u2013Joiner correlation coefficient (R\u2013J) is computed at various time windows. The measurement of this coefficient will allow identifying an attacker\u2019s presence whenever this coefficient falls below a threshold corresponding to the normal critical values. Realistic VANET scenarios are simulated using SUMO (Simulation of Urban Mobility) and NS-3 (network simulator). Our approach implemented in the Matlab environment offers a real time detection scheme that can identify anomalous behavior relying on multivariate data. The proposed scheme is validated in different scenarios under routing attacks, mainly the black hole attack. As far as we know, our proposed approach unprecedentedly employed multivariate normality tests to attack detection in VANETs. It can further be applied to any VANET routing protocol without making any additional changes in the routing algorithm.<\/jats:p>","DOI":"10.3390\/info13060282","type":"journal-article","created":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T03:33:18Z","timestamp":1654054398000},"page":"282","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A New Multivariate Approach for Real Time Detection of Routing Security Attacks in VANETs"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9489-7696","authenticated-orcid":false,"given":"Souad","family":"Ajjaj","sequence":"first","affiliation":[{"name":"ENSAM, Hassan II University, Casablanca 20000, Morocco"}]},{"given":"Souad","family":"El Houssaini","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, Chouaib Doukkali University, El Jadida 24000, Morocco"}]},{"given":"Mustapha","family":"Hain","sequence":"additional","affiliation":[{"name":"ENSAM, Hassan II University, Casablanca 20000, Morocco"}]},{"given":"Mohammed-Alamine","family":"El Houssaini","sequence":"additional","affiliation":[{"name":"ESEF, Chouaib Doukkali University, El Jadida 24000, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"ref_1","first-page":"100310","article-title":"VANET Applications: Past, Present, and Future","volume":"28","author":"Lee","year":"2021","journal-title":"Veh. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Gon\u00e7alves, F., Macedo, J., and Santos, A. (2021). An Intelligent Hierarchical Security Framework for VANETs. Information, 12.","DOI":"10.3390\/info12110455"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"102696","DOI":"10.1016\/j.adhoc.2021.102696","article-title":"Survey and Taxonomy of Information-Centric Vehicular Networking Security Attacks","volume":"124","author":"Safwat","year":"2022","journal-title":"Ad Hoc Netw."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Karrupusamy, P., Balas, V.E., and Shi, Y. (2022). A Novel Privacy-Preserving and Denser Traffic Management System in 6G-VANET Routing Against Black Hole Attack. Proceedings of the Sustainable Communication Networks and Application, Springer Nature.","DOI":"10.1007\/978-981-16-6605-6"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Al-Shareeda, M.A., Anbar, M., Manickam, S., and Hasbullah, I.H. (2022). A Secure Pseudonym-Based Conditional Privacy-Preservation Authentication Scheme in Vehicular Ad Hoc Networks. Sensors, 22.","DOI":"10.3390\/s22051696"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Malik, A., Khan, M.Z., Faisal, M., Khan, F., and Seo, J.-T. (2022). An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs. Sensors, 22.","DOI":"10.3390\/s22051897"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"102148","DOI":"10.1016\/j.adhoc.2020.102148","article-title":"Recent Advancements, Review Analysis, and Extensions of the AODV with the Illustration of the Applied Concept","volume":"103","author":"Saini","year":"2020","journal-title":"Ad Hoc Netw."},{"key":"ref_8","unstructured":"Das, S.R., Belding-Royer, E.M., and Perkins, C.E. (2020, December 20). Ad Hoc On-Demand Distance Vector (AODV) Routing. Available online: https:\/\/tools.ietf.org\/html\/rfc3561."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Rencher, A.C. (2002). Methods of Multivariate Analysis, J. Wiley. [2nd ed.].","DOI":"10.1002\/0471271357"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ajjaj, S., El Houssaini, S., Hain, M., and El Houssaini, M.-A. (2022). Performance Assessment and Modeling of Routing Protocol in Vehicular Ad Hoc Networks Using Statistical Design of Experiments Methodology: A Comprehensive Study. Appl. Syst. Innov., 5.","DOI":"10.3390\/asi5010019"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"105524","DOI":"10.1016\/j.asoc.2019.105524","article-title":"Investigating the Impact of Data Normalization on Classification Performance","volume":"97","author":"Singh","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_12","unstructured":"Rao, C.R., and Ali, H. (2022, March 14). An Overall Test for Multivariate Normality Student. Available online: http:\/\/repository.ias.ac.in\/71898\/."},{"key":"ref_13","unstructured":"Ryan, T.A., and Joiner, B.L. (1976). Normal Probability Plots and Tests for Normality, Statistics Department, The Pennsylvania State University. Technical Report."},{"key":"ref_14","unstructured":"(2021, September 21). Documentation\u2014SUMO Documentation. Available online: https:\/\/sumo.dlr.de\/docs\/index.html."},{"key":"ref_15","unstructured":"(2021, September 21). Ns-3 | a Discrete-Event Network Simulator for Internet Systems. Available online: https:\/\/www.nsnam.org\/."},{"key":"ref_16","unstructured":"(2022, April 14). Build MEX Function or Engine Application\u2014MATLAB Mex. Available online: https:\/\/www.mathworks.com\/help\/matlab\/ref\/mex.html."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1080\/10629360600878449","article-title":"On Tests for Multivariate Normality and Associated Simulation Studies","volume":"77","author":"Farrell","year":"2007","journal-title":"J. Stat. Comput. Simul."},{"key":"ref_18","first-page":"9","article-title":"Efficiency Comparisons of Normality Test Using Statistical Packages","volume":"16","author":"Chantasorn","year":"2015","journal-title":"Thammasat Int. J. Sci. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"103352","DOI":"10.1016\/j.micpro.2020.103352","article-title":"Black Hole Attack Detection in Vehicular Ad-Hoc Network Using Secure AODV Routing Algorithm","volume":"80","author":"Kumar","year":"2021","journal-title":"Microprocess. Microsyst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"199618","DOI":"10.1109\/ACCESS.2020.3034327","article-title":"Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles","volume":"8","author":"Hassan","year":"2020","journal-title":"IEEE Access"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ali Zardari, Z., He, J., Zhu, N., Mohammadani, K., Pathan, M., Hussain, M., and Memon, M. (2019). A Dual Attack Detection Technique to Identify Black and Gray Hole Attacks Using an Intrusion Detection System and a Connected Dominating Set in MANETs. Future Internet, 11.","DOI":"10.3390\/fi11030061"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1016\/j.procs.2019.04.168","article-title":"Black Hole Attack Detection Using Fuzzy Based Intrusion Detection Systems in MANET","volume":"151","author":"Moudni","year":"2019","journal-title":"Proc. Comput. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1007\/s12652-018-0782-7","article-title":"EAODV: Detection and Removal of Multiple Black Hole Attacks through Sending Forged Packets in MANETs","volume":"10","author":"Delkesh","year":"2019","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.procs.2020.01.091","article-title":"Certain Investigation on MANET Security with Routing and Blackhole Attacks Detection","volume":"165","author":"Vinayagam","year":"2019","journal-title":"Proc. Comput. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.future.2017.12.008","article-title":"A Game Theory Based Multi Layered Intrusion Detection Framework for VANET","volume":"82","author":"Subba","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s11277-018-5824-0","article-title":"Advanced Secured Routing Algorithm of Vehicular Ad-Hoc Network","volume":"102","author":"Tyagi","year":"2018","journal-title":"Wirel. Pers. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5099","DOI":"10.1007\/s11277-017-4770-6","article-title":"Mitigation and Performance Analysis of Routing Protocols Under Black-Hole Attack in Vehicular Ad-Hoc Network (VANET)","volume":"97","author":"Purohit","year":"2017","journal-title":"Wirel. Pers. Commun."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/13\/6\/282\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:22:53Z","timestamp":1760138573000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/13\/6\/282"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,31]]},"references-count":27,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["info13060282"],"URL":"https:\/\/doi.org\/10.3390\/info13060282","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,31]]}}}