Detection and Ignoring of Blackhole Attack in Vanets Networks

2016 ◽  
Vol 6 (2) ◽  
pp. 1-10
Author(s):  
Chaima Bensaid ◽  
Sofiane Boukli Hacene ◽  
Kamel Mohamed Faraoun
Keyword(s):  
Black Hole ◽  
Communication Networks ◽  
Network Performance ◽  
Vehicular Networks ◽  
Data Communication ◽  
Main Idea ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
The Future ◽  
Detailed Simulation

Vehicular networks or VANET announce as the communication networks of the future, where the mobility is the main idea. These networks should be able to interconnect vehicles. The optimal goal is that these networks will contribute to safer roads and more effective in the future by providing timely information to drivers and concerned authorities. They are therefore vulnerable to many types of attacks among them the black hole attack. In this attack, a malicious node disseminates spurious replies for any route discovery in order to monopolize all data communication and deteriorate network performance. Many studies have focused on detecting and isolating malicious nodes in VANET. In this paper, the authors present two mechanisms to detect this attack. The main goal is detecting as well as bypass cooperative black hole attack. The authors' approaches have been evaluated by the detailed simulation study with NS2 and the simulation results shows an improvement of protocol performance.

scholarly journals Secured and Hybrid Recognition and Segregation of Black Hole Using Clustering Method in Manet

2019 ◽  
pp. 71-79
Author(s):  
Ramakanth Reddy Malladi ◽  
A. Govardhan
Keyword(s):  
Black Hole ◽  
Network Performance ◽  
Ad Hoc ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
Wormhole Attack ◽  
Routing Security ◽  
Security Issues ◽  
Hoc Networks ◽  
Future Work

The routing security issues of MANETs are described. The Black hole attack, which can easily be deployed against MANET and an efficient technique to isolate the multiple black hole attack, is described. The proposed technique will be based on to analyze the route reply packets in which the nodes reply with the exceptional high sequence number is add into blacklist. To isolate these nodes from the network, technique of clustering will be applied this improvement leads to increase network performance. The future work may be concentrate on the proposed technique can be compared with some other technique of intrusion detection for mobile ad-hoc networks. And also the proposed technique can be applied for the detection of wormhole attack in the network. The malicious nodes which are increasing delay in the network.

A Solution for Detecting Black Hole Attack Using Improved DRI in MANET

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Atifa Parveen ◽  
Shish Ahmad ◽  
Jameel ◽  
Ahmad
Keyword(s):  
Black Hole ◽  
Network Performance ◽  
Ad Hoc ◽  
Security Threats ◽  
Mobile Nodes ◽  
Black Hole Attack ◽  
Self Organized ◽  
Aodv Protocol ◽  
Autonomous Network ◽  
The Common

Ad hoc Network is a self organized autonomous network that consists of mobile nodes which communicate with each other over wireless links. One of the common attacks in MANETs is the Black hole Attack, in which malicious node falsely claiming it to have the fresh and shortest path to the destination and then drops all the receiving packets. The black hole attack is one of the well-known security threats in wireless mobile adhoc networks. We proposed a mechanism to mitigate single black hole attack to discover a safe route to the destination by avoiding attacks. In this paper we proposed an approach for better analysis and improve security of AODV, which is one of the popular routing protocols for MANET. Our scheme is based on AODV protocol which is improved by deploying improved DRI table with additional check bit. The Simulation on NS2 is carried out and the proposed scheme has produced results that demonstrate the effectiveness of the mechanism in detection and elimination of the attack and improve network performance by reducing the packet dropping ratio in network. In this paper, We not only classify these proposals into single black hole attack but also analyze the categories of these solutions.

scholarly journals Detection and Elimination of Black Hole Attack in WSN

2019 ◽  
Vol 9 (1) ◽  
pp. 1377-1382
Keyword(s):  
Black Hole ◽  
Sensor Nodes ◽  
Security Threats ◽  
Traffic Surveillance ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
Wormhole Attack ◽  
Digital Signature Algorithm ◽  
Secure Network ◽  
The Cost

Wireless Sensor Network has become one of the most emerging areas of research in recent days. WSNs have been applied in a variety of application areas such as military, traffic surveillance, environment monitoring and so on. Since WSN is not a secure network and each sensor node can be compromised by the intruder. There are plenty of security threats in sensor networks like Black hole Attack, Wormhole attack, Sinkhole attack. Recently, there are so many algorithms are proposed to detect or to prevent attack by the researchers. Still, the research is continuing to evaluate sensor nodes' trust and reputation. At present to monitor nodes’ behavior direct and indirect trust values are used and most of the detection method uses additional nodes to detect an attack. These method increases the cost and also overhead. This paper proposed a method which detects the Black hole attack without using any additional node to monitor the network. The proposed work uses Attacker Detection metric (AD metric) to detect malicious node based on the average sequence number, time delay and reliability. OLSR protocol is used for routing which improves the network lifetime by minimizing the packet flooding. Besides, to ensure reliable data transmission Elliptical Curve Digital Signature Algorithm is used. Simulation results are obtained and show malicious nodes are eliminated using AD metrics

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. 

Closed User Group Automotive Communication Network Based on Addressing at Physical Layer

2012 ◽  
Vol 4 (4) ◽  
pp. 26-39
Author(s):  
Rajarshi Sanyal ◽  
Ernestina Cianca ◽  
Ramjee Prasad
Keyword(s):  
Mobility Management ◽  
Network Performance ◽  
Vehicular Networks ◽  
Data Communication ◽  
High Mobility ◽  
Physical Layer ◽  
User Group ◽  
Collision Warning ◽  
Classical Voice ◽  
Closed User Group

Intelligent Vehicle communication is the keyword for the emerging vehicular technologies such as group cooperative driving, real time Engine Operating parameters (EOP) monitoring, collision warning, geo location based mobility applications, and classical voice and data conveyance. The technologies require extensive interaction between the peers which mostly use the framework of the state of the art cellular or radio trunking networks. This may vitiate the network performance due to the surge in mobility management messages originated by the devices plugged in the vehicles. The performance may be severely impacted due to the unique characteristics of vehicular networks e.g., high mobility. Due to the high proliferation of these Machine to Machine (M2M) and Machine to Application (M2A) devices in near future, the cell sizes will shrink, resulting in more signalling messages in the network. Considering classical voice communication services for typical car fleet implementations, the radio trunking networks have capacity constrains due to inability of frequency reuse and absence of mobility management techniques. The alternative is to seek out an access technology considering the fact that a more intelligent physical layer can be employed directly for addressing and mobility management. In this paper the authors address a Closed User Group network implementation for Vehicle to Vehicle/central office communication which can actuate voice and data communication without incorporating any application layer.

NS2-Based Black Hole Attack Modeling and Simulation of Ad Hoc Network

2013 ◽  
Vol 846-847 ◽  
pp. 1697-1700
Author(s):  
Yuan Ming Ding ◽  
Hao Qu ◽  
Xue Wang
Keyword(s):  
Black Hole ◽  
Ad Hoc Network ◽  
Network Performance ◽  
Ad Hoc ◽  
Black Hole Attack ◽  
Attack Model ◽  
Attack Modeling ◽  
Security Research ◽  
Different Types ◽  
The Impact

Taking the AODV protocol as an example, the attack characteristics of different types of black holes are analyzed. Then, an attack model of black hole is established. Finally, the effects of black hole attacks to network performance are analyzed by simulations in different types and intensities. The simulation results show that this model can accurately simulate the impact of black hole attack on network performance and can provide reference and corresponding simulation environment for the security research of Ad Hoc network.

scholarly journals Security Improvement of AODV Routing Protocol through IPSO-IDRS Mechanism for Ad-hoc Networks

2019 ◽  
Vol 8 (12) ◽  
pp. 1009-1015
Keyword(s):  
Black Hole ◽  
Particle Swarm Optimization ◽  
Intrusion Detection ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
Swarm Optimization ◽  
Response System ◽  
Aodv Routing Protocol

Ad-hoc network is vulnerable to different types of attacks because of its vigorously changing topology, limited storage capacity, absence of centralized infrastructure etc. Adhoc On Demand Distance Vector (AODV) is established protocol for routing for this type of networks. AODV is exposed to black hole attack due to the inadequacy of security consideration. The malicious nodes drop all information packets rather than sending it to the neighboring node. In this research paper, Anomaly based intrusion detection system (IDS) known as Particle swarm optimization (PSO) is purposefully utilized to detect the misbehavior activities in the network. In AODV routing protocol, swarm agents are used for identifying misbehavior activities of nodes based on dropping behavior of data packets. An intrusion response system (IRS) is activated after the detection of an intrusion. It is necessary to take action against black hole attack or reduce the effect of the damage caused by the attack. IDS and a response system are integrated for detection and removal of the source of an attack respectively. The guard nodes are placed in the network with the aim to oppose black hole attackers and in this way IR is initiated. The malevolent nodes detected by PSO are bypassed and new routing paths are established using guard nodes. This research has been carried out for analyzing the influence of malicious nodes and guard nodes on varying network size vice versa. The simulation study of proposed technique integrated particle swarm optimization intrusion detection response system (IPSO-IDRS) explains how it is better in terms of the performance metric like throughput and PDR.

scholarly journals Prevention of Black Hole Attacks in Virtualized Cloud Network using Trust-Aware Energy Efficient AODV Routing with Firefly Based AI Technique

2019 ◽  
Vol 8 (2) ◽  
pp. 5799-5805
Keyword(s):  
Black Hole ◽  
Network Performance ◽  
Ad Hoc ◽  
Secure Routing ◽  
Support Vector ◽  
Delivery Ratio ◽  
Malicious Nodes ◽  
Safety Issues ◽  
Artificial Neural Network Ann ◽  
Cloud Network

Cloud networks are very widespread and unreliable because of the amount of VMs and presented nodes in their Virtual Cloud Network. Nodes might connect and revoke networks at any time. Resilience is a advantage of cloud computing, but it has many safety issues in routing and transmitting information between messages. VCN research is very similar to the portable ad-hoc network (MANET), which depends on the collaboration of all involved nodes to provide fundamental activities. Many safety assaults and risks exploit the safety of information transmission due to the decentralized environment in VCN and MANET. Malicious nodes can interfere and use information during wireless communications. Numbers of methods are there that has a diverse effect on such attacks for malicious nodes. Varied attacks are susceptible to security, but Black hole assault is one of the most common effective assaults, as fraudulent nodes dump all incoming emails reducing network performance and reliability. A black hole node is designed to lampoon every node in the network that conveys with some other node by saying it always has the easiest route to the target node. In this manuscript, a secure routing discovery method has been presented using Ad hoc on demand distance vector (AODV) routing protocol. For the detection of attack in the cloud, the concept of Artificial Intelligence (AI) has been used. Therefore, in this research, Artificial Neural Network (ANN) and Support Vector Machine (SVM)is adapted to determine Packet Delivery Ratio (PDR), Delay and Throughput measures. The comparative examination has been conducted to depict the proposed FNN-AODV effectiveness. There is an enhancement of 61.01% in FNN-AODV and 5.08% enhancement in Throughput in proposed FNN-AODV than R-AODV, 6.26% enhancement in PDR for FNN-AODV than R-AODV and 10.8% is the decrement in delay in FNN-AODV than of R-AODV

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