دورية أكاديمية

Watchdog malicious node detection and isolation using deep learning for secured communication in MANET

التفاصيل البيبلوغرافية
العنوان: Watchdog malicious node detection and isolation using deep learning for secured communication in MANET
المؤلفون: Narmadha A. S., Maheswari S., Deepa S. N.
المصدر: Automatika, Vol 64, Iss 4, Pp 996-1009 (2023)
بيانات النشر: Taylor & Francis Group, 2023.
سنة النشر: 2023
المجموعة: LCC:Automation
مصطلحات موضوعية: MANET, secure communication, deep neural network learning, projection pursuit regression function, watchdog malicious node detection, isolation, Control engineering systems. Automatic machinery (General), TJ212-225, Automation, T59.5
الوصف: Mobile Ad-hoc Networks (MANETs) are wireless networks formed dynamically by connecting or leaving nodes to and from the network without any fixed infrastructure. These categories of wireless networks are susceptible to different attacks based on their dynamic topological structure. Due to this, security is a primary constraint in MANETs to preserve communication between mobile nodes. A Deep Neural Learned Projective Pursuit Regression-based Watchdog Malicious Node Detection and Isolation (DNLPPR-WMNDI) technique is proposed and modelled in this paper to improve the security feature of MANETs. The newly proposed DNLPPR-WMNDI technique initially selects the neighbouring nodes by applying the projection pursuit regression function. In multicasting, the route paths are established through the intermediate node with the help of control commands named RREQ and RREP. After then, Watchdog Malicious Node Detection and Isolation (WMNDI) technique is applied to detect malicious nodes based on the data packet forwarding time. Basically, a malicious node is affected by a node isolation attack. For better communication, a malicious node is isolated from the network and multicast routing is carried out by selecting the next neighbouring node and this improves the communication security. Simulation is done for the developed technique based on different performance metrics.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 00051144
1848-3380
0005-1144
العلاقة: https://doaj.org/toc/0005-1144Test; https://doaj.org/toc/1848-3380Test
DOI: 10.1080/00051144.2023.2241766
الوصول الحر: https://doaj.org/article/da9fc0282da04894ad5801114e986103Test
رقم الانضمام: edsdoj.9fc0282da04894ad5801114e986103
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:00051144
18483380
DOI:10.1080/00051144.2023.2241766