{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:58:25Z","timestamp":1777705105618,"version":"3.51.4"},"reference-count":11,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2024,1,10]]},"abstract":"<jats:p>Mobile Ad-Hoc Networks (MANET) are considered one of the significant and growing areas in today\u2019s scenario of technological advancement. It is an infrastructure-less and dynamic ad-hoc network that requires a connection between nodes to deliver packets and data. However, its design adopts a connection-less approach, at the helm of which no monitoring node exists. Hence, the threat of maintaining the network\u2019s security remains an uphill task. Many attacks have been attempted to breach the protection of the MANET. This paper discusses one of the most potent attacks in a MANET infrastructure, the Sinkhole Attack. We try to minimize the possibility of a sinkhole attack using a Fuzzy Q-learning-based approach, a reinforcement learning technique. The results are encouraging, suggesting that sinkhole attacks can be minimized to a great extent after the adaption of the proposed approach.<\/jats:p>","DOI":"10.3233\/jifs-232003","type":"journal-article","created":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T11:01:47Z","timestamp":1700564507000},"page":"1615-1626","source":"Crossref","is-referenced-by-count":0,"title":["A fuzzy based Q \u2013 learning approach to prevent sinkhole attacks in MANET (FQ \u2013 SPM)"],"prefix":"10.1177","volume":"46","author":[{"given":"Ankita","family":"Kumari","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandip","family":"Dutta","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soubhik","family":"Chakraborty","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Birla Institute of Technology, Mesra, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-232003_ref1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/978-3-642-36169-2_2","article-title":"Security issues in mobile ad hoc network,}","author":"Islam Noman","year":"2013","journal-title":"Wireless Networks and Security"},{"key":"10.3233\/JIFS-232003_ref6","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.jnca.2015.04.008","article-title":"Identification of contamination zones for sinkhole detection in MANETs","volume":"54","author":"Sanchez-Casado","year":"2015","journal-title":"Journal of Network and Computer Applications"},{"key":"10.3233\/JIFS-232003_ref7","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1016\/j.procs.2014.05.319","article-title":"Sinkhole attack detection based on redundancy mechanism in wireless sensor networks","volume":"31","author":"Zhang","year":"2014","journal-title":"Procedia Computer Science"},{"key":"10.3233\/JIFS-232003_ref8","doi-asserted-by":"crossref","first-page":"108413","DOI":"10.1016\/j.comnet.2021.108413","article-title":"A trust-aware security mechanism to detect sinkhole attacks in RPL-based IoT environment using random forest\u2013RFTRUST","volume":"198","author":"Prathapchandran","year":"2021","journal-title":"Computer Networks"},{"key":"10.3233\/JIFS-232003_ref9","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.asoc.2014.01.015","article-title":"Swarm intelligence-based approach for sinkhole attack detection in wireless sensor networks","volume":"19","author":"Sreelaja","year":"2014","journal-title":"Applied Soft Computing"},{"issue":"3","key":"10.3233\/JIFS-232003_ref10","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.jcss.2013.06.016","article-title":"Detection and mitigation of sinkhole attacks in wireless sensor networks","volume":"80","author":"Shafiei","year":"2014","journal-title":"Journal of Computer and System Sciences"},{"key":"10.3233\/JIFS-232003_ref11","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.sysarc.2018.07.005","article-title":"Effectiveness of HT-assisted sinkhole and blackhole denial of service attacks targeting mesh networks-on-chip","volume":"89","author":"Zhang","year":"2018","journal-title":"Journal of Systems Architecture"},{"issue":"5","key":"10.3233\/JIFS-232003_ref12","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/j.comcom.2009.11.006","article-title":"Military tactics in agent-based sinkhole attack detection for wireless ad hoc networks","volume":"33","author":"Stafrace","year":"2010","journal-title":"Computer Communications"},{"issue":"5","key":"10.3233\/JIFS-232003_ref14","first-page":"390","article-title":"A cooperative-sinkhole detection method for mobile ad hoc networks","volume":"64","author":"Kim","year":"2010","journal-title":"AEU-International Journal of Electronics and Communications"},{"key":"10.3233\/JIFS-232003_ref15","doi-asserted-by":"crossref","first-page":"104504","DOI":"10.1016\/j.micpro.2022.104504","article-title":"CL-MLSP: The design of a detection mechanism for sinkhole attacks in smart cities","volume":"90","author":"Sangaiah","year":"2022","journal-title":"Microprocessors and Microsystems"},{"key":"10.3233\/JIFS-232003_ref16","doi-asserted-by":"crossref","first-page":"3055","DOI":"10.1007\/s11277-018-5994-9","article-title":"Secure Data Transfer Using Multi-Layer Security Protocol with Energy Power Consumption AODV in Wireless Sensor Networks","volume":"103","author":"Vidhya","year":"2018","journal-title":"Wireless Pers Commun"}],"container-title":["Journal of Intelligent &amp; 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