{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:28:31Z","timestamp":1747189711957,"version":"3.40.5"},"reference-count":20,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2021,5]]},"abstract":"<jats:p> This study manifests a fuzzy-based trust prediction model for detecting malicious nodes in wireless sensor networks (WSN) by preventing black hole attack. Besides, a new routing protocol based on the shortest path and trust to the path nodes is presented with a fuzzy estimator, which uses the data mining methods to detect the malicious nodes (black holes). In a black hole attack, a malicious node selects the RREP (Route Replay) message as the shortest path from the source node to the destination node. After that, the packet sent to the malicious node is not received by the network. Eventually, the malicious node releases the entire data packet instead of sending it to the destination node. Optimal path selection is performed according to different algorithms on the objective function and its results are observed for route selection. After defining the objective function, different algorithms such as Genetic Algorithm (GA) and teaching\u2013learning-based optimization (TLBO) are utilized for routing. For each algorithm, the objective function for the most secure node is evaluated and simulated based on the parameters defined in fuzzy logic. Based on the simulation results under MATLAB software, TLBO algorithm has obtained the best response for path selection with the least cost for the target performance. Significantly, the proposed method is simple and based on the exchange of control packets between the sensor node and the base station. In accession, the results show that the proposed algorithms are effective in detecting and preventing black hole attacks. <\/jats:p>","DOI":"10.1142\/s0218126621500985","type":"journal-article","created":{"date-parts":[[2020,8,22]],"date-time":"2020-08-22T02:42:11Z","timestamp":1598064131000},"page":"2150098","source":"Crossref","is-referenced-by-count":5,"title":["Fuzzy-Based Reliability Prediction Model for Secure Routing Protocol Using GA and TLBO for Implementation of Black Hole Attacks in WSN"],"prefix":"10.1142","volume":"30","author":[{"given":"Sajad","family":"Nosratian","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Arak Branch, Islamic Azad University, Arak, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7215-0807","authenticated-orcid":false,"given":"Masoud","family":"Moradkhani","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ilam Branch, Islamic Azad University, Ilam, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad Bagher","family":"Tavakoli","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Arak Branch, Islamic Azad University, Arak, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,10,5]]},"reference":[{"key":"S0218126621500985BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2013.01.010"},{"key":"S0218126621500985BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2012.11.020"},{"key":"S0218126621500985BIB003","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126617500438"},{"key":"S0218126621500985BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCI.2016.7479930"},{"key":"S0218126621500985BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/JRPROC.1952.273898"},{"key":"S0218126621500985BIB006","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126617500049"},{"key":"S0218126621500985BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/30.125072"},{"key":"S0218126621500985BIB008","first-page":"33","volume":"1","author":"Hirota K.","year":"2004","journal-title":"Iran. 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