Black Hole Attacks on MANETs: Analysis and Prevention

Wireless network technically, refers to the category of network in which communication is carried out without using wires. In modern era wireless network has great importance because the communication is taking place with the use of radio waves. Thus, the use of ad-hoc network starts yielding a great importance in variety of applications. The certain research work is carried out in this particular field. MANET is a constructed from various mobility in the form of mobile nodes and anytime without any need of fixed infrastructure. MANET can be made on fly due to lack of fixed infrastructure. MANET is numerous threats types of attacks due to dynamic changing topologies and wireless medium. Security of the MANET becomes one of the challenging tasks. Black hole attacks is the main type of attack that are possible in MANET. Black hole node not forward any data packets to the neighbour node instead it drops all the data packets. Black hole attacks are bit hard to detect due to lack of centralized access. This research work concentrates to enhance the security of MANET by identifying and blocking black hole assaults from occurring. A reactive routing system such as Ad-Hoc on Demand Distance Vector has previously been used to address security problems in the MANET (AODV). Various attack types were investigated, and the consequences of these assaults were detailed by describing how MANET performance was disrupted. Network Simulator 3 (NS3) is used for the simulation process.

Intrusion Detection in Manet Through Machine Learning Approach

Mobile ad hoc networks (MANETs) have evolved into a leading multi-hop infrastructure less wireless communication technology where every node performs the function of a router. Ad- hoc networks have been spontaneously and specifically designed for the nodes to communicate with each other in locations where it is either complex or impractical to set up an infrastructure. The overwhelming truth is that with IoT emergence, the number of devices being connected every single second keeps increasing tremendously on account of factors like scalability, cost factor and scalability which are beneficial to several sectors like education, disaster management, healthcare, espionage etc., where the identification and allocation of resources as well as services is a major constraint. Nevertheless, this infrastructure with dynamic mobile nodes makes it more susceptible to diverse attack scenarios especially in critical circumstances like combat zone communications where security is inevitable and vulnerabilities in the MANET could be an ideal choice to breach the security. Therefore, it is crucial to select a robust and reliable system that could filter malicious activities and safeguard the network. Network topology and mobility constraints poses difficulty in identifying malicious nodes that can infuse false routes or packets could be lost due to certain attacks like black hole or worm hole. Hence our objective is to propose a security solution to above mentioned issue through ML based anomaly detection and which detects and isolates the attacks in MANETs. Most of the existing technologies detect the anomalies by utilizing static behavior; this may not prove effective as MANET portrays dynamic behavior. Machine learning in MANETs helps in constructing an analytical model for predicting security threats that could pose enormous challenges in future. Machine learning techniques through its statistical and logical methods offers MANETs the learning potential and encourages towards adaptation to different environments. The major objective of our study is to identify the intricate patterns and construct a secure mobile ad-hoc network by focusing on security aspects by identifying malicious nodes and mitigate attacks. Simulation-oriented results establish that the proposed technique has better PDR and EED in comparison to the other existing techniques.

Mobile Ad-hoc Networks: A Survey on multipath routing protocols

A Mobile Ad Hoc Network (MANETs) connects mobile nodes without any base station. These nodes in the network can change the topology dynamically and transfer the data among themselves. The nodes in the MANET are categorized based on the resource factors like memory, computation, and power levels. The dynamic change in route makes the connection of the destination node more complex. Sometimes, it results in link failure, and hence the primary route is failed, which means an alternative route is required to transmit the packets. It required multiple paths from the source node to destination node with a stable path connecting the source node. This issue makes MANET routing a crucial task. To address these problems, multipath routing in MANET is discussed in this paper. Multipath routing provides various paths for a single source node to a single destination node. It is more important to consider load balancing and fault tolerance when establishing the multipath routing mechanism. This paper describes the various type of challenges along with their respective multipath routing protocols in MANETs.

Counteracting Selfish Nodes Using Reputation Based System in Mobile Ad Hoc Networks

A mobile ad hoc network (MANET) is a group of nodes constituting a network of mobile nodes without predefined and pre-established architecture where mobile nodes can communicate without any dedicated access points or base stations. In MANETs, a node may act as a host as well as a router. Nodes in the network can send and receive packets through intermediate nodes. However, the existence of malicious and selfish nodes in MANETs severely degrades network performance. The identification of such nodes in the network and their isolation from the network is a challenging problem. Therefore, in this paper, a simple reputation-based scheme is proposed which uses the consumption and contribution information for selfish node detection and cooperation enforcement. Nodes failing to cooperate are detached from the network to save resources of other nodes with good reputation. The simulation results show that our proposed scheme outperforms the benchmark scheme in terms of NRL (normalized routing load), PDF (packet delivery fraction), and packet drop in the presence of malicious and selfish attacks. Furthermore, our scheme identifies the selfish nodes quickly and accurately as compared to the benchmark scheme.

Performance Evaluation of Different ToS Using Heterogeneous Communication Interfaces in FANETs

The use of different types-of-services (ToS), such as voice, data, and video, has become increasingly present in the execution of applications involving networks composed of multiple UAVs. These applications usually require the UAVs to share different ToS in a dynamic and ad-hoc manner, such that they can support the execution of cooperative/collaborative tasks. The use of heterogeneous communication has showed gains in maintaining the connection among highly mobile nodes, while increasing the reliable transmission of data, as is necessary in MANETS, VANETs and, more recently, FANETs. The aim of this paper is to present a performance evaluation of a heterogeneous interface manager (IM), which applies a heuristic to choose the best among several single- and multi-band wireless communication interfaces, including IEEE 802.11n, IEEE 802.11p, IEEE 802.11ac, and IEEE 802.11ax. Simulated scenarios with three, five, and eight UAV nodes are developed by integrating NS-3 and Gazebo simulation tools. The IM performance is analyzed by applying different numbers of interfaces and comparing with interfaces applied homogeneously by defining two set of results, in terms of application and MAC and PHY metrics, respectively. Finally, we also evaluate the associated performance, considering voice, data, and video streaming ToS. The results indicate that the combination of different interfaces has a very powerful effect on maintaining or increasing the communication intensity.

A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks

The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems.

Trust-Based Security: Advancement towards Protection of the Adhoc Network

MANET (mobile ad hoc network) is a collection of mobile nodes that interact without the need for a fixed physical foundation. MANETs have grown in popularity as a result of characteristics like dynamic topology, quick setup, multi-hop data transfer, and so on. MANETs are well-suited to various real-time applications, including environmental monitoring, disaster management, and covert and military operations, because of their distinguishing characteristics. MANETs may also be used in conjunction with new technologies like cloud computing, IoT, and machine learning algorithms to help realize the vision of Industry 4.0. Secure and reliable data transfer is essential for any MANET-based sensitive real-time applications that must achieve the requisite QoS. It is challenging to provide safe and efficient data transfer with MANET. As a result, this article examines different Trust-based Approaches that take a step forward in providing secure transmission while simultaneously improving MANET performance. Furthermore, the study's analysis based on many aspects exposes the inadequacies of existing techniques and provides future directions for improvement.

Detection of Black Hole Attack Using Honeypot Agent-Based Scheme with Deep Learning Technique on MANET

Mobile Ad-Hoc Networks (MANETs) due to their reconfigurable nature are being integrated into new and futuristic knowledge such as Internet of Things (IoT), cloud, reconfigurable networks, etc. To attain such credibility of integration, the routing protocols associated with these mobile nodes have to connect, perform and facilitate routing that offers a high level of security and resistance to all possible threats and security issues that may emanate in the network. One of the solutions used to maintain network security is intrusion detection systems (IDSs). This article primarily emphasis on the network's susceptibility to a suction assault known as a black hole attack. The investigations about the employment of intelligent agents called Honeypot Agent-based detection scheme (HPAS) with Long-Short Term Memory (LSTM) in identifying such assaults. Hence, the proposed method is named HPAS-LSTM, where honeypots are roaming virtual software managers that create Route Request (RREQ) packets to attract and entrap black hole attackers. Extensive model results utilizing the ns-2 simulator are used to demonstrate the presence of the suggested detection technique. The simulation outcomes demonstrate that the suggested technique outperforms current black hole detection methods in terms of throughput (TH), packet loss rate (PLR), packet delivery ratio (PDR), and total network delay (TND).

Mobile Data-Mule Optimal Path Planning for Wireless Sensor Networks

This article is concerned with collecting stored sensor data from a static Wireless Sensor Network utilizing a group of mobile robots that act as data mules. In this scenario, the static sensor nodes’ locations are known a priori, and the overall optimization problem is formulated as a variation of the Traveling Salesman Subset-tour Problem (TSSP). The constraints that are taken into account include: (a) the pairwise distance between static nodes, (b) the maximum time interval between consecutive visits of each static node, (c) the service time that is required for the collection of the sensor data from the mobile element that visits this sensor node, and (d) the energy efficiency for the mobile nodes. The optimal mobile robot paths are computed using an enhanced Mobile Element Scheduling scheme. This scheme extracts the sequential paths of the mobile elements in an attempt to eliminate any sensor data loss.

A Gateway Selection Mechanism for Internet-assisted MANETs

Internet-assisted MANETs architecture is an emerging solution, strongly introduced in recent years. In fact, MANETs are self-configurable wireless network models for convenient communication between mobile nodes in the network. Because of simplicity, MANETs are applied in a series of domains to serve humanity, such as intelligent agriculture, intelligent transport system, and IoT ecosystem. To extend the ability of MANETs, the integration of Internet and MANETs to form Internet-assisted MANETs architecture was introduced in many studies. However, one of the biggest problems of this solution is how to choose the optimal Internet gateway. This study proposes a gateway selection mechanism based on parameters, including hop number and gateway traffic. To evaluate the effectiveness of the proposed mechanism, we compare the proposed solution with previous solutions. The simulation results demonstrated that our solution improved end-to-end delay, routing overload, and loss packet ratio compared to previous protocols.