Detection of malicious nodes in drone ad-hoc network based on supervised learning and clustering algorithms

2020 ◽  
Author(s):  
Shanshan Sun ◽  
Zuchao Ma ◽  
Liang Liu ◽  
Hang Gao ◽  
Jianfei Peng
Keyword(s):  
Supervised Learning ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Malicious Nodes

scholarly journals A Novel Clustering Algorithm Based on Agent Technology for VANET

2016 ◽  
Vol 8 (2) ◽  
pp. 1 ◽  
Author(s):  
Samira Harrabi ◽  
Ines Ben Jaafar ◽  
Khaled Ghedira
Keyword(s):  
Traffic Congestion ◽  
Ad Hoc Network ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Clustering Algorithms ◽  
High Mobility ◽  
Agent Technology ◽  
Related Data ◽  
Network Overhead

Vehicular Ad-hoc Network (VANET) is a sub-family of Mobile Ad-hoc Network (MANET).The means goal of VANET is to provide communications between nearby nodes or between nodes and fixed infrastructure. Despite that VANET is considered as a subclass of MANET, it has for particularity the high mobility of vehicles producing the frequent changes of network topology that involve changing of road, varying node density and locations of vehicles existing in this road. That‘s why, the most proposed clustering algorithms for MANET are unsuitable for VANET. Various searches have been recently published deal with clustering for VANETs. But most of them are focused on minimizing network overhead value, number of created clusters and had not considered the vehicles interests which defined as any related data used to differentiate vehicle from another (such as traffic congestion, looking for free parking space etc). In this paper, we propose a novel clustering algorithm based on agent technology to solve the problems mentioned above and improve routing in VANET. Experimental part show promising results regarding the adoption of the proposed approach.

Distributed Trust Based Authentication Scheme in a Clustered Environment Using Threshold Cryptography for Vehicular Ad Hoc Network

2010 ◽  
Vol 6 (2) ◽  
pp. 1-18 ◽  
Author(s):  
S. Sivagurunathan ◽  
V. Mohan ◽  
P. Subathra
Keyword(s):  
Communication Networks ◽  
Ad Hoc Network ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Clustering Algorithms ◽  
Vehicular Ad Hoc Network ◽  
Data Traffic ◽  
Prime Concern ◽  
Moving Pattern

A Vehicular Ad-Hoc Network, or VANET, is a form of Mobile Ad-Hoc Network to provide communications among nearby vehicles and between vehicles and nearby fixed equipments. Security has become a prime concern in providing communication between these vehicles. Unlike wired networks, the characteristics of Vehicular Ad Hoc Networks (VANETs) pose a number of non-trivial challenges to security design. In this paper, the authors present a threshold security mechanism with a mobility based Clustering for Open Inter Vehicle Communication Networks (COIN). Nodes that have a similar moving pattern are grouped into a cluster, and unlike other clustering algorithms, it takes the moving pattern of the vehicles into consideration with the driver’s intention. The stability of clusters is estimated based on relative mobility of cluster members. A threshold cryptographic scheme is employed on top of the clusters to protect routing information and data traffic. To ensure distributed trust in the clustered environment, the private key (k) is divided into n pieces in such a way that k is easily reconstructable from any p number of pieces.

scholarly journals IP-CHOCK Reference Detection and Prevention of Denial of Service (DoS) Attacks in Vehicular Ad-Hoc Network

2017 ◽  
pp. 398-420 ◽  
Author(s):  
Karan Verma
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Vehicular Ad Hoc Network ◽  
Dos Attacks ◽  
Malicious Nodes ◽  
Efficient Detection ◽  
Flooding Attacks ◽  
Ip Spoofing ◽  
Prevention Method

Vehicular Ad-Hoc Network (VANET) is a subset of Mobile Ad-Hoc Network (MANET) and it is considered as a substantial component of Intelligent Transportation System (ITS). DoS attacks on VANET are varying and may be overwhelmed by VANET protocols, such as TCP or UDP flooding attacks. Different secure communications models can be used to detect and prevent IP spoofing DoS attacks, by which the attacks are committed by fraudulent and malicious nodes. In this chapter, an efficient detection method has been proposed to detect UDP flooding attacks, called Bloom-Filter-Based IP-CHOCK (BFICK). A prevention method using IP-CHOCK has also been proposed to prevent DoS, called Reference Broadcast Synchronization (RBS). In principle, the combined method is based on the IP-CHOCK filter concept of packets during an attack incident and with busy traffic condition. Fake identities from malicious vehicles can be analyzed with help of the existing reliable IP addresses. Beacon packets were exchanged periodically by all the vehicles to announce their presence and to forward it to the next node.

scholarly journals Prevention Techniques for Sybil Attack

2012 ◽  
Vol 11 (10) ◽  
pp. 3060-3064 ◽  
Author(s):  
Roopali Garg ◽  
Himika Sharma
Keyword(s):  
Wireless Network ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Multiple Identities ◽  
Sybil Attack ◽  
Malicious Nodes ◽  
Wireless Links ◽  
Prevention Techniques ◽  
Mobile Ad Hoc

Mobile ad-hoc network is a self-governing network, consists of group of nodes that communicates with each other through wireless links. As it is a wireless network, so it is subjected to various attacks. There is one attack which is very dangerous called Sybil attack. In Sybil attack, attackers or malicious nodes uses multiple identities to disrupt the communication between the nodes by capturing necessary and important information and creating misunderstandings between the nodes. In this paper some measures are described to prevent Sybil attack.

Detection and Prevention of Gray Hole and Black Hole Attack in MANET

2014 ◽  
Vol 13 (9) ◽  
pp. 5029-5038
Author(s):  
Deepali Raut ◽  
Kapil Hande
Keyword(s):  
Black Hole ◽  
Ad Hoc Network ◽  
Information Disclosure ◽  
Ad Hoc ◽  
Denial Of Service ◽  
Destination Node ◽  
Performance Parameters ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
Service Routing

An Ad hoc network is the network with no fixed infrastructure. There is no central administrator so any node can come and move in and outside of the network in a dynamic manner. This makes it more dynamic and complex which makes it more prone to attacks. They can attack either active or passive. Some effects of malicious nodes are Denial of service, Routing table overflow, Impersonation, Energy consumption, Information disclosure etc. A black hole attack node attracts all packets by falsely claiming a fresh route to the destination node and absorbs them without forwarding them to destination. In this work the effect of Black hole and Gray Hole attack on DSR protocol has been considered. Simulation has been performed on the basis of performance parameters and effect has been analyzed using NS2 simulator. 

scholarly journals Modified Fidelity Based On-Demand Secure (MFBOD) Routing Protocol in Mobile Ad-Hoc Network

2015 ◽  
Vol 40 (4) ◽  
pp. 267-298 ◽  
Author(s):  
Himadri Nath Saha ◽  
Rohit Singh ◽  
Debika Bhattacharyya ◽  
P.K. Banerjee
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Secure Routing ◽  
Malicious Nodes ◽  
On Demand ◽  
Mobile Ad Hoc ◽  
Demand Routing ◽  
Better Than

Abstract With advent of technology MANET is becoming more and more ubiquitous, and so is the vulnerability of such networks to attacks. In this paper, we propose a secure, lightweight, on-demand routing protocol for MANETs. It uses the concept of fidelity to allocate trust to a neighbor, thereby taking the decision whether to send data via that neighbor or not. To combat attacks efficiently new packets like report and recommendation are used. After receiving a few of these packets a node can conclude about the behavior of a node, thereby identifying and blacklisting the malicious nodes. We try to impose bounds for the fidelity with reference to the battery of the node, which restricts a node to increase its fidelity to infinity and become dominant in the network. This protocol not only finds a secure route to transmit data, but also identifies the malicious nodes in the network. Our protocol exhibits high packet delivery fraction, with low normalized routing load and low end to end delay; which has been observed while simulating in GloMoSim platform. We have observed that our protocol performs not only better than other existing secure routing protocol in a malicious environment, but also combats, many attacks which have not been dealt with these protocols.

scholarly journals Smart detection and prevention procedure for DoS attack in MANET

2021 ◽  
pp. 1-5
Author(s):  
A. S. M. Muntaheen ◽  
Milton Chandro Bhowmick ◽  
Md. Raqibul Hasan Rumman ◽  
Nayeem Al-Tamzid Bhuiyan ◽  
Md. Taslim Mahmud Bhuyain ◽  
...  
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Malicious Node ◽  
Specific Time ◽  
Mobile Nodes ◽  
Dos Attack ◽  
Malicious Nodes ◽  
Mobile Ad Hoc ◽  
Hoc Networks

A self-organized wireless communication short-lived network containing collection of mobile nodes is mobile ad hoc network (MANET). The mobile nodes communicate with each other by wireless radio links without the use of any pre-established fixed communication network infrastructure or centralized administration, such as base stations or access points, and with no human intervention. In addition, this network has potential applications in conference, disaster relief, and battlefield scenario, and have received important attention in current years. There is some security concern that increases fear of attacks on the mobile ad-hoc network. The mobility of the NODE in a MANET poses many security problems and vulnerable to different types of security attacks than conventional wired and wireless networks. The causes of these issues are due to their open medium, dynamic network topology, absence of central administration, distributed cooperation, constrained capability, and lack of clear line of defense. Without proper security, mobile hosts are easily captured, compromised, and attacked by malicious nodes. Malicious nodes behavior may deliberately disrupt the network so that the whole network will be suffering from packet losses. One of the major concerns in mobile ad-hoc networks is a traffic DoS attack in which the traffic is choked by the malicious node which denied network services for the user. Mobile ad-hoc networks must have a safe path for transmission and correspondence which is a serious testing and indispensable issue. So as to provide secure communication and transmission, the scientist worked explicitly on the security issues in versatile impromptu organizations and many secure directing conventions and security measures within the networks were proposed. The goal of the work is to study DoS attacks and how it can be detected in the network. Existing methodologies for finding a malicious node that causes traffic jamming is based on node’s retains value. The proposed approach finds a malicious node using reliability value determined by the broadcast reliability packet (RL Packet). In this approach at the initial level, every node has zero reliability value, specific time slice, and transmission starts with a packet termed as reliability packet, node who responded properly in specific time, increases its reliability value and those nodes who do not respond in a specific time decreases their reliability value and if it goes to less than zero then announced that it’s a malicious node. Reliability approach makes service availability and retransmission time.

scholarly journals Trusted Sensing Model for Mobile Ad HoC Network Using Differential Evolution Algorithm

2020 ◽  
Vol 49 (4) ◽  
pp. 556-563
Author(s):  
P Elamparithi ◽  
Dr. K. Ruba Soundar
Keyword(s):  
Differential Evolution ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Geographical Area ◽  
Differential Evolution Algorithm ◽  
Trust Model ◽  
Malicious Nodes ◽  
Penalty Factor ◽  
Mobile Ad Hoc

Mobile Ad Hoc Network (MANET) has set of mobile nodes that are allowed to communicate with each other through wireless links. The nodes are deployed spontaneously without any infrastructure in a geographical area. Due to the lack of centralized administration and prior organization, MANETs are vulnerable to different attacks of malicious nodes. To overcome the problem of black hole attack in MANETs, a trust model using Differential Evolution (DE) algorithm has been proposed. It identifies the malicious node and inhibits them to become the member of data transmission path. The proposed work consists of two phases; one is to obtain the optimized path and the other deals with the penalty factor for malicious nodes. Moreover, the Differential Evolution is one of the most promising optimization to enhance security with increased network density. The proposed algorithm is compared with AOMDV, DSR, Genetic algorithm and ACO.

Sign in / Sign up

Export Citation Format

Share Document