Biblio
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.
In this paper, decentralized dynamic power allocation problem has been investigated for mobile ad hoc network (MANET) at tactical edge. Due to the mobility and self-organizing features in MANET and environmental uncertainties in the battlefield, many existing optimal power allocation algorithms are neither efficient nor practical. Furthermore, the continuously increasing large scale of the wireless connection population in emerging Internet of Battlefield Things (IoBT) introduces additional challenges for optimal power allocation due to the “Curse of Dimensionality”. In order to address these challenges, a novel Actor-Critic-Mass algorithm is proposed by integrating the emerging Mean Field game theory with online reinforcement learning. The proposed approach is able to not only learn the optimal power allocation for IoBT in a decentralized manner, but also effectively handle uncertainties from harsh environment at tactical edge. In the developed scheme, each agent in IoBT has three neural networks (NN), i.e., 1) Critic NN learns the optimal cost function that minimizes the Signal-to-interference-plus-noise ratio (SINR), 2) Actor NN estimates the optimal transmitter power adjustment rate, and 3) Mass NN learns the probability density function of all agents' transmitting power in IoBT. The three NNs are tuned based on the Fokker-Planck-Kolmogorov (FPK) and Hamiltonian-Jacobian-Bellman (HJB) equation given in the Mean Field game theory. An IoBT wireless network has been simulated to evaluate the effectiveness of the proposed algorithm. The results demonstrate that the actor-critic-mass algorithm can effectively approximate the probability distribution of all agents' transmission power and converge to the target SINR. Moreover, the optimal decentralized power allocation is obtained through integrated mean-field game theory with reinforcement learning.
Mobile ad hoc network (MANET) is an infrastructure less, self organizing on demand wireless communication. The nodes communicate among themselves through their radio range and nodes within the range are known as neighbor nodes. DSR (Dynamic Source Routing), a MANET reactive routing protocol identify the destination by transmitting route request (RREQ) control message into the network and establishes a path after receiving route reply (RREP) control messages. The intermediate node lies in between source to destination may also send RREP control message, weather they have path information about that destination is present into their route cache due to any previous communication. A malicious node may enter within the network and may send RREP control message to the source before original RREP is being received. After receiving RREP without knowing about the destination source starts to send data and data may reached to a different location. In this paper we proposed a novel algorithm by which a malicious node, even stay in the network and send RREP control message but before data transmission source can authenticate the destination by applying PGP (pretty Good Privacy) encryption program. In order to design our algorithm we proposed to add an extra field with RREQ control message with a unique index value (UIV) and two extra fields in RREP applied over UIV to form a random key (Rk) in such a way that, our proposal can maintained two way authorization scheme. Even a malicious node may exists into the network but before data transmission source can identified weather RREP is received by the requested destination or a by a malicious node.
A mobile ad hoc network (MANET) is a collection of mobile nodes that do not need to rely on a pre-existing network infrastructure or centralized administration. Securing MANETs is a serious concern as current research on MANETs continues to progress. Each node in a MANET acts as a router, forwarding data packets for other nodes and exchanging routing information between nodes. It is this intrinsic nature that introduces the serious security issues to routing protocols. A black hole attack is one of the well-known security threats for MANETs. A black hole is a security attack in which a malicious node absorbs all data packets by sending fake routing information and drops them without forwarding them. In order to defend against a black hole attack, in this paper we propose a new threshold-based black hole attack prevention method using multiple RREPs. To investigate the performance of the proposed method, we compared it with existing methods. Our simulation results show that the proposed method outperforms existing methods from the standpoints of packet delivery rate, throughput, and routing overhead.
A Mobile Ad Hoc Network (MANET) is considered a type of network which is wireless and has no fixed infrastructure composed of a set if nodes in self organized fashion which are randomly, frequently and unpredictably mobile. MANETs can be applied in both military and civil environments ones because of its numerous applications. This is due to their special characteristics and self-configuration capability. This is due to its dynamic nature, lack of fixed infrastructure, and the no need of being centrally managed; a special type of routing protocols such as Anonymous routing protocols are needed to hide the identifiable information of communicating parties, while preserving the communication secrecy. This paper provides an examination of a comprehensive list of anonymous routing protocols in MANET, focusing their security and performance capabilities.
Mobile Ad hoc Network (MANET) is the collection of mobile devices which could change the locations and configure themselves without a centralized base point. Mobile Ad hoc Networks are vulnerable to attacks due to its dynamic infrastructure. The routing attacks are one among the possible attacks that causes damage to MANET. This paper gives a new method of risk aware response technique which is combined version the Dijkstra's shortest path algorithm and Destination Sequenced Distance Vector (DSDV) algorithm. This can reduce black hole attacks. Dijkstra's algorithm finds the shortest path from the single source to the destination when the edges have positive weights. The DSDV is an improved version of the conventional technique by adding the sequence number and next hop address in each routing table.
Mobile Ad-hoc network is decentralized and composed of various individual devices for communicating with each other. Its distributed nature and infrastructure deficiency are the way for various attacks in the network. On implementing Intrusion detection systems (IDS) in ad-hoc node securities were enhanced by means of auditing and monitoring process. This system is composed with clustering protocols which are highly effective in finding the intrusions with minimal computation cost on power and overhead. The existing protocols were linked with the routes, which are not prominent in detecting intrusions. The poor route structure and route renewal affect the cluster hardly. By which the cluster are unstable and results in maximization processing along with network traffics. Generally, the ad hoc networks are structured with battery and rely on power limitation. It needs an active monitoring node for detecting and responding quickly against the intrusions. It can be attained only if the clusters are strong with extensive sustaining capability. Whenever the cluster changes the routes also change and the prominent processing of achieving intrusion detection will not be possible. This raises the need of enhanced clustering algorithm which solved these drawbacks and ensures the network securities in all manner. We proposed CBIDP (cluster based Intrusion detection planning) an effective clustering algorithm which is ahead of the existing routing protocol. It is persistently irrespective of routes which monitor the intrusion perfectly. This simplified clustering methodology achieves high detecting rates on intrusion with low processing as well as memory overhead. As it is irrespective of the routes, it also overcomes the other drawbacks like traffics, connections and node mobility on the network. The individual nodes in the network are not operative on finding the intrusion or malicious node, it can be achieved by collaborating the clustering with the system.
The traditional network used today is unable to meet the increasing needs of technology in terms of management, scaling, and performance criteria. Major developments in information and communication technologies show that the traditional network structure is quite lacking in meeting the current requirements. In order to solve these problems, Software Defined Network (SDN) is capable of responding as it, is flexible, easier to manage and offers a new structure. Software Defined Networks have many advantages over traditional network structure. However, it also brings along many security threats due to its new architecture. For example, the DoS attack, which overloads the controller's processing and communication capacity in the SDN structure, is a significant threat. Mobile Ad Hoc Network (MANET), which is one of the wireless network technologies, is different from SDN technology. MANET is exposed to various attacks such as DoS due to its security vulnerabilities. The aim of the study is to reveal the security problems in SDN structure presented with a new understanding. This is based on the currently used network structures such as MANET. The study consists of two parts. First, DoS attacks against the SDN controller were performed. Different SDN controllers were used for more accurate results. Second, MANET was established and DoS attacks against this network were performed. Different MANET routing protocols were used for more accurate results. According to the scenario, attacks were performed and the performance values of the networks were tested. The reason for using two different networks in this study is to compare the performance values of these networks at the time of attack. According to the test results, both networks were adversely affected by the attacks. It was observed that network performance decreased in MANET structure but there was no network interruption. The SDN controller becomes dysfunctional and collapses as a result of the attack. While the innovations offered by the SDN structure are expected to provide solutions to many problems in traditional networks, there are still many vulnerabilities for network security.
This project enhances the security in which Ad Hoc On-Demand Distance Vector (AODV) routing protocol for MANETs with the game theoretical approach. This is achieved by using public key and private key for encryption and decryption processes. Proactive and reactive method is implemented in the proposed system. Reactive method is done in identification process but in proactive method is used to identify the nodes and also block the hackers node, then change the direction of data transmission to good nodes. This application can be used in military, research, confidential and emergency circumferences.
In this paper, an agent-based cross-layer secure service discovery scheme has been presented. Service discovery in MANET is a critical task and it presents numerous security challenges. These threats can compromise the availability, privacy and integrity of service discovery process and infrastructure. This paper highlights various security challenges prevalent to service discovery in MANET. Then, in order to address these security challenges, the paper proposes a cross-layer, agent based secure service discovery scheme for MANET based on deep neural network. The software agents will monitor the intrusive activities in the network based on an Intrusion Detection System (IDS). The service discovery operation is performed based on periodic dissemination of service, routing and security information. The QoS provisioning is achieved by encapsulating QoS information in the periodic advertisements done by service providers. The proposed approach has been implemented in JIST/ SWANS simulator. The results show that proposed approach provides improved security, scalability, latency, packet delivery ratio and service discovery success ratio, for various simulation scenarios.
The growing use of MANETs and its vulnerability to attacks due to its fundamental characteristics make secure routing one of the most considerable challenges. In this paper, a new security scheme for mobile ad hoc networks (MANETs) is presented. The proposed scheme used Trivium lightweight stream cipher algorithm in combination with HMAC to secure the routing control packets. This paper compares the performance of the AODV after implementing the security scheme in terms of throughput, delay sum (end-to-end), jitter sum (end-to-end) and packet loss ratio. The proposed scheme shows better performance than original AODV under blackhole attack.
For the past few decades, mobile ad hoc networks (MANETs) have been a global trend in wireless networking technology. These kind of ad-hoc networks are infrastructure less, dynamic in topology and further doesn't have a centralized network administration which makes it easier for the intruders to launch several attacks on MANETs. In this paper, we have made a comparative analysis of the network layer attack by simulating rushing and black hole attack using NS-2 network simulator. For determining the most vulnerable attack we have considered packet delivery ratio, end to end delay and throughput as a evaluation metrices. Here, AODV routing protocol has been configured for data forwarding operations. From our Simulation result, it is evident that the black hole attack is more vulnerable when compared to the rushing attack.