Journal ArticleDOI
Using Neural Networks to Detect Internal Intruders in VANETs
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TLDR
The proposed approach to security provision relies on radial basis neural networks and makes it possible to identify malicious nodes by indicators of behavior to ensure protection of VANET against malicious nodes.Abstract:
This article considers ensuring protection of Vehicular Ad-Hoc Networks (VANET) against malicious nodes. Characteristic performance features of VANETs and threats are analyzed, and current attacks identified. The proposed approach to security provision relies on radial basis neural networks and makes it possible to identify malicious nodes by indicators of behavior.read more
Citations
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Book ChapterDOI
Vehicular Intelligence System: Time-Based Vehicle Next Location Prediction in Software-Defined Internet of Vehicles (SDN-IOV) for the Smart Cities
TL;DR: In this article, the development of traditional Vehicular Ad-Hoc Networks (VANETs) into the Internet of Vehicles (IOV) is inspired by the modern era of Internet of Things (IoT).
Journal ArticleDOI
Development of the Intrusion Detection System for the Internet of Things Based on a Sequence Alignment Algorithm
TL;DR: In this article, a prototype of the intrusion detection system for the Internet of Things has been developed, which is based on the Needleman-Wunsch global algorithm of sequence alignment.
Journal ArticleDOI
Ensuring Cyber Resilience of Large-Scale Network Infrastructure Using the Ant Algorithm
E. Yu. Pavlenko,K. V. Kudinov +1 more
TL;DR: In this paper, the application of the ant algorithm for ensuring the cyber resilience of a distributed system in conditions of various types of cyber attacks is considered, and a mathematical model of the network infrastructure is developed, and possible type of cyberattacks are determined within the framework of the model.
Journal ArticleDOI
Reduction of the Number of Analyzed Parameters in Network Attack Detection Systems
E. A. Popova,V. V. Platonov +1 more
TL;DR: In this paper, a prototype of the network attack detection system with a module for reducing the number of network traffic parameters is proposed and the accuracy and time of detecting network attacks by the developed prototype are assessed.
Journal ArticleDOI
Identification of Cyber Threats in Networks of Industrial Internet of Things Based on Neural Network Methods Using Memory
TL;DR: In this article, the authors proposed to use modern artificial neural networks to identify cyber threats in networks of the Industrial Internet of Things (IoT) by modeling an industrial system under the influence of cyberattacks.
References
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Book
Neural Networks And Learning Machines
TL;DR: Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together.
Journal Article
Prediction of Time Series Using RBF Neural Networks: A New Approach of Clustering
TL;DR: This approach is based on a new efficient method of clustering of the centers of the radial basis function neural network trying to concentrate more clusters in those input regions where the error is bigger and move the clusters instead of just the input values of the I/O data.
Proceedings ArticleDOI
Network security architectures for VANET
TL;DR: All of the proposed security architectures allow us to establish a security policy in m2m-networks and increase resistance capabilities of self-organizing networks.
Journal ArticleDOI
Energy-aware secure routing for large wireless sensor networks
Theodore Zahariadis,Helen C. Leligou,Stamatis Voliotis,Sotiris Maniatis,Panagiotis Trakadas,Panagiotis Karkazis +5 more
TL;DR: A secure routing protocol is proposed (Ambient Trust Sensor Routing, ATSR) which adopts the geographical routing principle to cope with the network dimensions and part of the routing attacks, while it relies on a distributed trust model for the detection of another part ofThe routing attacks.
Journal ArticleDOI