Biblio

MANETs are wireless networks, providing properties such as self-configuration, mobility, and flexibility to the network, which make them a popular and widely used technique. As the usage and popularity of the networks increases, security becomes the most important factor to be concerned. For the sake of security, several protocols and methodologies have been developed for the networks. Along with the increase in security mechanisms, the number of attacks and attackers also increases and hence the threat to the network and secure communication within it increases as well. Some of the attacks have been resolved by the proposed methodologies but some are still a severe threat to the framework, one such attack is Black Hole Attack. The proposed work integrates the SUPERMAN (Security Using Pre-Existing Routing for Mobile Ad-hoc Networks) framework with appropriate methodology to detect and prevent the network from the Black Hole Attack. The mechanism is based on the AODV (Ad-hoc On-demand Distance Vector) routing protocol. In the methodology, the source node uses two network routes, from the source to the destination, one for sending the data packet and another for observing the intermediate nodes of the initial route. If any node is found to be a Black Hole node, then the route is dropped and the node is added to the Black Hole list and a new route to send the data packet to the destination is discovered.

Wireless technology is rapidly proliferating. Devices such as Laptops, PDAs and cell-phones gained a lot of importance due to the use of wireless technology. Nowadays there is also a huge demand for spectrum allocation and there is a need to utilize the maximum available spectrum in efficient manner. Cognitive Radio (CR) Network is one such intelligent radio network, designed to utilize the maximum licensed bandwidth to un-licensed users. Cognitive Radio has the capability to understand unused spectrum at a given time at a specific location. This capability helps to minimize the interference to the licensed users and improves the performance of the network. Routing protocol selection is one of the main strategies to design any wireless or wired networks. In Cognitive radio networks the selected routing protocol should be best in terms of establishing an efficient route, addressing challenges in network topology and should be able to reduce bandwidth consumption. Performance analysis of the protocols helps to select the best protocol in the network. Objective of this study is to evaluate performance of various cognitive radio network routing protocols like Spectrum Aware On Demand Routing Protocol (SORP), Spectrum Aware Mesh Routing in Cognitive Radio Networks (SAMER) and Dynamic Source Routing (DSR) with and without black hole attack using various performance parameters like Throughput, E2E delay and Packet delivery ratio with the help of NS2 simulator.

A self-governing system consisting of mobile nodes that exchange information within a cellular area and is known as a mobile ad hoc network (MANET). Due to its dynamic nature, it is vulnerable to attacks and there is no fixed infrastructure. To transfer a data packet Ad-hoc On-Demand Distance Vector (AODV) is used and it's another form of a reactive protocol. The black-hole attack is a major attack that drastically decreases the packet delivery ratio during a data transaction in a routing environment. In this attack, the attacker's node acts as the shortest path to the target node itself. If the attacker node receives the data packet from the source node, all obtained data packets are excluded from a routing network. A trust-based routing scheme is suggested to ensure secure routing. This routing scheme is divided into two stages, i.e., the Data retrieval (DR), to identify and preserve each node data transfer mechanism in a routing environment and route development stage, to predict a safe path to transmit a data packet to the target node.

Robotics Mobile Ad-hoc Networks (MANETs) are comprised of stations having mobility with no central authority and control. The stations having mobility in Robotics MANETs work as a host as well as a router. Due to the unique characteristics of Robotics MANETs such type of networks are vulnerable to different security attacks. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol that belongs to the reactive category of routing protocols in Robotics MANETs. However, it is more vulnerable to the Black hole (BH) attack that is one of the most common attacks in the Robotics MANETs environment. In this attack during the route disclosure procedure a malicious station promotes itself as a most brief path to the destination as well as after that drop every one of the data gotten by the malicious station. Meanwhile the packets don't reach to its ideal goal, the BH attack turns out to be progressively escalated when a heap of malicious stations attack the system as a gathering. This research analyzed different BH finding as well as removal mechanisms for AODV routing protocol.

Vehicular Ad-Hoc Networks (VANET) are liable to the Black, Worm and Gray Hole attacks because of the broadcast nature of the wireless medium and a lack of authority standards. Black Hole attack covers the situation when a malicious node uses its routing protocol in order to publicize itself for having the shortest route to the destination node. This aggressive node publicizes its availability of fresh routes regardless of checking its routing table. The consequences of these attacks could lead not only to the broken infrastructure, but could cause hammering people's lives. This paper aims to investigate and compare methods for preventing such types of attacks in a VANET.

Mobile Ad hoc Network (MANET) is one of the emerging technologies to communicate between nodes and its decentralized structure, self-configuring nature are the few properties of this Ad hoc network. Due to its undefined structure, it has found its usage in the desired and temporary communication network. MANET has many routing protocols governing it and due to its changing topology, there can be many issues arise in recent times. Problems like no central node, limited energy, and the quality of service, performance, design issues, and security challenges have been bugging the researchers. The black hole attacks are the kind that cause ad hoc network to be at loss of information and make the source to believe that it has the actual least distance path to the destination, but in real scenario the packets do not get forwarded to neighbouring nodes. In this paper, we have discussed different solutions over the past years to deal with such attacks. A summary of the schemes with their results and drawbacks in terms of performance metrics is also given.

Self-organising networks, such as mobile ad-hoc networks (MANETs), are growing more and more in importance each day. However, due to their nature and constraints MANETs are vulnerable to a wide array of attacks, such as black hole attacks. Furthermore, there are numerous routing protocols in use in MANETs, and what works for one might not for another. In this paper, we present a review of previous surveys of black hole attack solutions, followed by a collation of recently published papers categorised by original routing protocol and evaluated on a set of common metrics. Finally, we suggest areas for further research.

Mobile Ad hoc Network is a very important key technology for device to device communication without any support of extra infrastructure. As it is being used as a mode of communication in various fields, protecting the network from various attacks becomes more important. In this research paper, we have created a real network scenario using random mobility of nodes and implemented Black hole Attack and Gray hole Attack, which degrades the performance of the network. In our research, we have found a novel mitigation technique which is efficient to mitigate both the attack from the network.

Wireless technology is widely used today and is growing rapidly. One of the wireless technologies is VANET where the network can communicate with vehicles (V2V) which can prevent accidents on the road. Energy is also a problem in VANET so it needs to be used efficiently. The presence of malicious nodes or nodes can eliminate and disrupt the process of data communication. The routing protocol used in this study is AODV. The purpose of this study is to analyze the comparison of blackhole attack and flooding attack against energy-efficient AODV on VANET. This research uses simulation methods and several supporting programs such as OpenStreetMap, SUMO, NS2, NAM, and AWK to test the AODV routing protocol. Quality of service (QOS) parameters used in this study are throughput, packet loss, and end to end delay. Energy parameters are also used to examine the energy efficiency used. This study uses the number of variations of nodes consisting of 20 nodes, 40 nodes, 60 nodes, and different network conditions, namely normal network conditions, network conditions with black hole attacks, and network conditions with flooding attacks. The results obtained can be concluded that the highest value of throughput when network conditions are normal, the greatest value of packet loss when there is a black hole attack, the highest end to end delay value and the largest remaining energy when there is a flooding attack.

Mobile Ad-hoc Network (MANET) consists of different configurations, where it deals with the dynamic nature of its creation and also it is a self-configurable type of a network. The primary task in this type of networks is to develop a mechanism for routing that gives a high QoS parameter because of the nature of ad-hoc network. The Ad-hoc-on-Demand Distance Vector (AODV) used here is the on-demand routing mechanism for the computation of the trust. The proposed approach uses the Artificial neural network (ANN) and the Support Vector Machine (SVM) for the discovery of the black hole attacks in the network. The results are carried out between the black hole AODV and the security mechanism provided by us as the Secure AODV (SAODV). The results were tested on different number of nodes, at last, it has been experimented for 100 nodes which provide an improvement in energy consumption of 54.72%, the throughput is 88.68kbps, packet delivery ratio is 92.91% and the E to E delay is of about 37.27ms.

Wireless Sensor Network is the combination of small devices called sensor nodes, gateways and software. These nodes use wireless medium for transmission and are capable to sense and transmit the data to other nodes. Generally, WSN composed of two types of nodes i.e. generic nodes and gateway nodes. Generic nodes having the ability to sense while gateway nodes are used to route that information. IoT now extended to IoET (internet of Everything) to cover all electronics exist around, like a body sensor networks, VANET's, smart grid stations, smartphone, PDA's, autonomous cars, refrigerators and smart toasters that can communicate and share information using existing network technologies. The sensor nodes in WSN have very limited transmission range as well as limited processing speed, storage capacities and low battery power. Despite a wide range of applications using WSN, its resource constrained nature given birth to a number severe security attacks e.g. Selective Forwarding attack, Jamming-attack, Sinkhole attack, Wormhole attack, Sybil attack, hello Flood attacks, Grey Hole, and the most dangerous BlackHole Attacks. Attackers can easily exploit these vulnerabilities to compromise the WSN network.

Mobile ad hoc networking (MANET) has been most popular research area for last decade. In MANET node (mobile node) is communicate with each other over wireless link where all nodes behave like both as host and router. In comparison with wired networks, mobile network is more vulnerable to security threat because of no centralized administration. One of the momentous routing protocols used in MANET is AODV (Ad hoc On demand Distance Vector) protocol. The Ad hoc On demand Distance Vector (AODV) protocol is compromised with its security by a various types of attacks due to malicious nodes present in the network. A hybrid approach is given for intrusion detection by removing malicious nodes during the route discovery process. The proposed approach increases the network performance in terms of PDR, throughput and end to end delay and security also.