Attacks In Mobile Ad Hoc Networks Research Articles

A Framework for Various Attack Identification in MANET Using Multi-Granular Rough Set

The topology changes randomly and dynamically in a mobile adhoc network (MANET). The composite characteristics of MANETs makes it exposed to interior and exterior attacks. Avoidance support techniques like authentication and encryption are appropriate to prevent attacks in MANETs. Thus, an authoritative intrusion detection model is required to prevent from attacks. These attacks can be at either the layers present in the network or can be of a general attack. Many models have been developed for the detection of intrusion and detection. These models aim at any one of the layer present in the network. Therefore, effort has been made to consider either the layers for the detection of intrusion and detection. This article uses a multigranular rough set (MGRS) for the detection of intrusion and detection in MANET. The advantage of MGRS is that it can aim at either the layers present in the network simultaneously by using multiple equivalence relations on the universe. The proposed model is compared with many traditional models and attained higher accuracy.

Utilization of Energy Consumption Metric to Detect Black Hole Attacker in DSR Routing Protocol

A Mobile Adhoc Network (MANET) is a self-organized system comprised of multiple mobile wireless nodes. They do not require the existing network infrastructure. Autonomous telescopes can change freely and inadvertently in a network that can establish a dynamic network temporarily, and these networks can often change their appearance. Due to the openness in network topology and the absence of centralized administration in management, MANET is vulnerable to attacks from malicious nodes. Therefore, security is a major issue in MANET, which drastically reduces network performance. Several trust parameters such as packet delivery ratio, packet dropping ratio, etc are used for detecting the malicious node attack in MANET. Among these, this paper uses the energy as the trust parameter for detecting the malicious node. The energy reduction ratio differs from the normal node and attacker node in MANET. Hence, the main aim of this paper is to find the Normal Energy Reduction Ratio (NERR) and Attacker Energy Reduction Ratio (AERR). These two values are used for differentiating the normal node and attacker node in MANET. For routing, this paper uses the Dynamic Source Routing (DSR) Protocol.

Cross centric intrusion detection system for secure routing over black hole attacks in MANETs

Due to the constraint of resources in Mobile Adhoc Network (MANET), usually mobile nodes do not gain perfect routing efficiency. This routing efficiency will be reduced by several numbers of data blockages and the communication time in the routing path. There are many data blockages arising, especially Black Hole Attack (BHA) is a massive anomalous attack in routing. This may cause the efficiency of communication time between nodes. In this juncture, the availability of Intrusion Detection System with Cross centric network which is overloaded with routing path packets, so it is easily affected by the BHA. To decrease the impact of black hole attack using Cross Centric Network Intrusion Detection System, this research proposes the CniDsor framework. CniDsor framework is a diminutive form of the “Cross Centric Intrusion Detection System for Secure Routing over Black Hole Attacks in MANETs”. This system is used to prevent the Black Hole Attacks over the Secure Routing. CniDsor works based on the Path Origin Selection, Priority Portion Assignment (PPA) and IDS attack reduction. In this study, path origin selection utilizes secure routing by “PIHNSPRA Routing Algorithm” and it selects the path from end to end nodes with secure manner and reduces the black-hole attack. Meanwhile, priority portion assignment is used to manage the node position and network monitoring by the “Past Interaction History”. Finally, CniDsor framework provides secure IDS communication efficiency in MANET which is used to accomplish the efficient routing path. Moreover, the proposed CniDsor framework works better and minimizes the communication overhead, packet delay and end to end delay, thus increases the network lifetime, packet delivery ratio (PDR).

Ddos Attack Detection and Prevention using Aodv Routing Mechanism and FFBP Neural Network in a Manet

Security is considered as the most important feature in a Mobile Ad-hoc Network (MANET). There are different types of attacks which may affect the data transmission in MANET but Distributed Denial of Service (DDoS) attack is one of the complex and harsh worthy in a MANET. In the existing work, it has been found that the researchers have utilized Support Vector Machine (SVM) and fuzzy logic as a classification algorithm to identify the DoS attack in MANET. The problem with SVM and Fuzzy logic is that they are more complex and more time consuming mechanism to detect attackers. Also, in the existing work, Optimized Link State Routing (OLSR) routing protocol is used to find route and it is a searching mechanism which does not include the concept of trust routing table and hence the searching mechanism consumes more energy. To solve the mentioned problems, we are presenting a machine learning approach that is Feed Forward Back Propagation Neural Network (FFBPNN) as a classifier and Ad hoc On-Demand Distance Vector(AODV) routing protocol for route discovery to shield the network from Distributed Denial of Service (DDoS) attack. The MANET is trained using FFBPNN. Therefore, when malicious node appears in the network, the node is identified on the basis of the node properties like energy consumption and delay. The route is changed by discarding the malicious nodes from the route and hence the network is protected. The throughputs, PDR have been increased by 60.71%, 53.57% and delay has been reduced by 42.21%.

Defending Against Flooding Attacks in Mobile Ad-Hoc Networks Based on Statistical Analysis

Due to their specific structure and plenty of their utilization, mobile ad-hoc networks are vulnerable to various attacks. An attack which impacts on network layer is referred to as flooding attack. By transmitting several packets, this attack occupies the processor so that it cannot receive the remaining data and packets. Hence, it causes disruption and disorder in the network. In this paper, for preventing this problem, a method has been proposed based on DSR routing protocol which quickly identifies the flooding attack. Indeed, the proposed method not only identifies and detects the malicious nodes in comparison with valid and proper nodes but also imposes sufficient penalties and reconsiders it again. The method proposed in this paper is called defending against flooding attacks-dynamic source routing. At the outset, it detects misbehavior in the network; then, for discovering malicious nodes, it uses average packet transmission RREQ which measures average transmission route request (RREQ) packets. The results of simulating the proposed method in NS-2 environment indicated that it improved packet delivery rate and end-to-end delay.

Detection and Prevention of Collaborative Attacks in Mobile Adhoc Networks Using Bait Method

Detection and Prevention of Collaborative Attacks in Mobile Adhoc Networks Using Bait Method

An Analysis on Security Threats of Black-Hole and Jellyfish Attacks in Mobile Ad-Hoc Network using HTTP Traffic

Mobile ad-hoc network (MANET) is an infrastructure less network. This network is a collection of randomly moving mobile nodes. As MANET does not have any centralized management, this network can form anywhere with the participation of randomly moving nodes. Because of such vulnerable behavior of MANET, this network has to face many security problems. There are so many security threats of MANET, which does not have any solution. Even detection of those problems is not easy. Some of the security threats are very severe. Those threats can even destroy the whole network. Researchers are working to find out the solution of those threats. Among those threats, we have worked with two security threats, which are Black-hole attack and Jellyfish attack. Here, we have found out the threats using HTTP traffic. We use OPNET modeler 14.5 as simulator AODV routing protocol. The aim of this paper is to find out the impact of security threats on MANET using HTTP traffic. We decide the impact using number of events and average number of events utilizing throughput of the OPNET modeler.

Detection and Prevention of Man-in-the-Middle Spoofing Attacks in MANETs Using Predictive Techniques in Artificial Neural Networks (ANN)

A Mobile Ad-Hoc Network (MANET) is a convenient wireless infrastructure which presents many advantages in network settings. With Mobile Ad-Hoc Network, there are many challenges. These networks are more susceptible to attacks such as black hole and man-in-the-middle (MITM) than their corresponding wired networks. This is due to the decentralized nature of their overall architecture. In this paper, ANN classification methods in intrusion detection for MANETs were developed and used with NS2 simulation platform for attack detection, identification, blacklisting, and node reconfiguration for control of nodes attacked. The ANN classification algorithm for intrusion detection was evaluated using several metrics. The performance of the ANN as a predictive technique for attack detection, isolation, and reconfiguration was measured on a dataset with network-varied traffic conditions and mobility patterns for multiple attacks. With a final detection rate of 88.235%, this work not only offered a productive and less expensive way to perform MITM attacks on simulation platforms but also identified time as a crucial factor in determining such attacks as well as isolating nodes and reconfiguring the network under attack. This work is intended to be an opening for future malicious software time signature creation, identification, isolation, and reconfiguration to supplement existing Intrusion Detection Systems (IDSs).

Intrusion Detection System Based on Genetic Algorithm for Detection of Distribution Denial of Service Attacks in MANETs

Mobile ad hoc networks (MANETs) are more susceptible towards security attacks because of its complicated characteristics i.e. lack of clear boundary of defense, no centralized points and dynamic topologies. Due to MANET characteristics, detection of attacks are more difficult than the traditional networks. One of very significant attack is distributed denial of service attack (DDoS) in MANETs. This attack may restrict the availability of the network resources. This paper focuses to develop an intrusion detection system using genetic algorithm for DDoS attacks in MANETs. The implementation results present that the proposed intrusion detection system which is based on genetic algorithm can able to detect the DDoS attacks on MANETs with a good detection rates.

Performance analysis on cluster-based intrusion detection techniques for energy efficient and secured data communication in MANET

Mobile ad hoc network (MANET) is a network which includes the number of mobile nodes (MN) is joined without any access point (AP). In MANET, the numbers of mobile devices are deployed for communication within the transmission range. MANET has large number of vulnerabilities that degrades the network and makes communication as difficult one. Challenges in MANET include non-existence of reliability in-between nodes because of their mobility and topology variation. Lack of security in network makes the intruder to interrupt the data transmission that resulted in data loss. Most of the routing protocols perform efficient routing but the networks are more susceptible to various attacks. The conventional security method protects wired network however it is not effectual for detecting the variants of intrusive attack in MANET. Our main objective is to detect the variants of attacks in MANET with lesser EC and higher IDR. To improve the performance of routing, various intrusion detection techniques are discussed and examined using clustering process.

An Evolutionary Self-Cooperative Trust Scheme Against Routing Disruptions in MANETs

How to achieve reliable routing has always been a major issue in the design of communication networks, among which mobile ad hoc networks (MANETs) possess the most adversarial networking environment due to the absence of fixed infrastructure, the nature of open transmission media and the dynamic network topology. These characteristics also make the design of routing protocols in MANETs become even more challenging. In this paper, we propose an evolutionary self-cooperative trust (ESCT) scheme that imitates human cognitive process and relies on trust-level information to prevent various routing disruption attacks. In this scheme, mobile nodes will exchange trust information and analyze received trust information based on their own cognitive judgment. Eventually, each node dynamically evolves its cognition to exclude malicious entities. The most attractive feature of ESCT is that they cannot compromise the system even if the internal attackers know how the security mechanism works. In this paper, we evaluate the performance of ESCT scheme under various routing disruption attack situations. Simulation results affirm that ESCT scheme promotes network scalability and ensures the routing effectiveness in the presence of routing disruption attackers in MANETs.

Mitigate black hole attack using bee optimised weighted trust with AODV in MANET

Mobile ad hoc network (MANET) is a decentralised network that can be used without any fixed setup or infrastructure and offers unlimited opportunities in all fields. Both the advantage and disadvantage of this mediums is the wide transmission range of the network that exceeds the area where the network is deployed, giving great opportunities for intruders to hack the network thus making it an unsafe mode of transmission. The conventional approaches for security attacks require high memory and high power consumption and so they cannot be used to tackle the security attacks for ad hoc routing. In this work, trust is used for addressing the maliciousness in the network. In this paper, the proposition is to reduce black hole attack in MANET using artificial bee colony optimisation for finding optimal secure routes. Proposed method outperforms the performance metrics like packet delivery ratio (PDR) and number of hops to sink. Also performs as normal effect for end-to-end delay.

Survey: Black Hole Attack Detection in MANET

Mobile Ad-hoc network (MANET) is dynamic in nature consists infrastructure less topology and de centralized behavior of nodes. Due to dynamic in nature each node is free to move anywhere so network become more vulnerable to attacks like black hole, gray hole any many more types of attacks. Infrastructure less mean each node some time act like host and sometimes like router. De centralized means it does not fallow client server model of communication. AODV is a routing protocol for data and control packet far wording between nodes during the communication between nodes black hole attacks are major issue in MANETs. In this paper discus some important technique used to detect the black hole attacks in MANETs using AODV routing protocol and their merits and demerits which play major role for future research.

DAPV: Diagnosing Anomalies in MANETs Routing With Provenance and Verification

Routing security plays an important role in the mobile ad hoc networks (MANETs). Despite many attempts to improve its security, the routing mechanism of MANETs remains vulnerable to attacks. Unlike most existing solutions that prevent the specific problems, our approach tends to detect the misbehavior and identify the anomalous nodes in MANETs automatically. The existing approaches offer support for detecting attacks or debugging in different routing phases, but many of them cannot answer the absence of an event. Besides, without considering the privacy of the nodes, these methods depend on the central control program or a third party to supervise the whole network. In this paper, we present a system called DAPV that can find single or collaborative malicious nodes and the paralyzed nodes which behave abnormally. DAPV can detect both direct and indirect attacks launched during the routing phase. To detect malicious or abnormal nodes, DAPV relies on two main techniques. First, the provenance tracking enables the hosts to deduce the expected log information of the peers with the known log entries. Second, the privacy-preserving verification uses Merkle Hash Tree to verify the logs without revealing any privacy of the nodes. We demonstrate the effectiveness of our approach by applying DAPV to three scenarios: 1) detecting injected malicious intermediated routers which commit active and passive attacks in MANETs; 2) resisting the collaborative black-hole attack of the AODV protocol, and; 3) detecting paralyzed routers in university campus networks. Our experimental results show that our approach can detect the malicious and paralyzed nodes, and the overhead of DAPV is moderate.

The Nash’s Balance in the Theory of Games for A Secure Model Mechanism in Routing Protocol of Manet

The present work is dedicated to study attacks and countermeasure in MANET. After a short introduction to what the Mobile Ad hoc Networks (MANETs) are and network security we present a survey of various attacks in MANETs pertaining to fail routing protocols. We present the different tools used by these attacks and the mechanisms used by the secured routing protocols to counter them. We also study a mechanism of security, named the reputation, proposed for the MANETs and the protocol which implements it. We also propose a secure mechanism which is based on the reputation. Our work ends with a proposal analytical model to the modules of our mechanism and the equilibrium states of our model.

A lightweight technique for detection and prevention of wormhole attack in MANET

A mobile ad-hoc network (MANET) is an ordinary and self-orbiting communication network that is capable of managing mobile nodes. Many proposed protocols on MANET address its vulnerability against different threats and attacks. The malicious node exploits these vulnerabilities to lunch attacks, especially when nodes have mobility and network do not have constant topology, like wormhole attack. This paper presents a lightweight technique that detects the wormhole attacks in MANET. In the proposed technique, the source node calculates the average sequence number of the reply (RREP) packets. If the sequence number of the corresponding node exceeds the calculated average value of the sequence number, then all traffic is discarded, and the node is marked as malicious. The proposed technique is less complex, power-efficient, and enhances network lifetime as more data packets are delivered to the destination node. This technique is validated through comprehensive simulations results in NS2.

A Survey to Monitor and Defend Against Blackhole Attacks in Mobile Adhoc Networks

Mobile adhoc networks is defined as collection of infrastructure less, self-organized, dynamic networks of mobile nodes that can be connected anywhere and at any time. In Mobile Adhoc Networks, every node in the network habitually amalgamate and deliver every other nodes packets in a sequence to permit out of reach conveyance. In this aggressive background, a part of the nodes may opposed to have it, either for preserving their self-resources or deliberately distorting usual conveyance. This class of misconduct is cited as packet dropping attack or Black hole attack. This kind of attack is supposed to be more catastrophic attack and it may provide a route to network crumble. The black hole malicious node organize its malevolent performance during the route locating procedures. In this paper we make a compendious study and survey examination on the counteract ant to be concerned with black hole attack and also we explore some of the propounded solution to diagnose and to avert the attack.

Defense Against Co-Operative Black-hole Attack and Gray-hole Attack in MANET

Mobile Ad-hoc networks (MANETs) can be termed as an autonomous system created by the collaboration of a set of motile nodes communicating with one another through available wireless media and each node behaves as an end system, as well as a router for packet forwarding. Each node is allowed to move freely, change locations and configure them to form a network. Finding an optimal and efficient path between the sender and receiver node is the main aim of routing protocols. Multipath routing protocols show a better result in comparison to single path routing protocols, for data transmission from source to destination extending lifetime of the network. Along with that security in routing for a protected communication between nodes has become a prime concern as any attack during routing may interrupt data transmission, paralyzing the whole network. During packet transmission through multiple paths a number of attacks make come into action by the unauthenticated and compromised nodes present within the network and black-hole attack is one of them. So our objective is to design a multipath routing protocol that detects and avoids the path containing black-hole. Our paper proposes a way to defense the black-hole and gray-hole attacks with the help of intelligence in MANET.

An Efficient multi stage security model based on cross layer mechanism for identifying and preventing black hole attack in wireless ad-hoc networks

Mobile Adhoc Network (MANET) is one of the popular and highly demanded networks functioning under wireless adhoc network. It has high demand by various emerging applications in the entire world. MANET and its necessities are increasing day by day. MANET and its various components like node, route and etc., are too dynamic regarding creating, deployment, mobility, speed, join and disconnect from the network. MANET does not require any existing infrastructure whereas it starts functions in any place at any time. Due these reasons various malicious activities are created dynamically and it degrades the performance of the network. This paper focused on detecting and identifying malicious activities one who affects the data directly. Such kind of malicious activity is blackhole attack where it destroys the data during transmission in a route. In order to detect and eliminated blackhole attack this paper focused on monitoring and investigating various functionalities of the network using a Multi Stage Security Model (MSSM). The MSSM is used for detecting and preventing blackhole attacks in MANET which involves investigating cross layer functionalities during data transmission. And it also investigates and analyzes the entire information that is available in the network. This proposed MSSM is simulated in Network Simulation-2 software and the results are verified and the performance is evaluated.

Attacks in Mobile Adhoc-Networks

Attacks in Mobile Adhoc-Networks