Survey: Black Hole Attack Detection in MANET

Singh, Vinay; Singh, Ajit; Hassan, Malik Mubasher

doi:10.2139/ssrn.3351016

Cited by 7 publications

(7 citation statements)

References 2 publications

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“…First, the packet generation rate means a value measured the amount of control packets that node k generates to its neighbor node n for a certain period time. And, the average value of the control packet of the cluster to which node n belongs is measured by equation (5).…”

Section: Intrusion Detection Techniquesmentioning

confidence: 99%

“…Here, 𝑃 𝑓 (𝑁 𝑘 ) is the amount of packets that the node n forwards to the destination node n, 𝑃 𝑟 (𝑁 𝑑 ) is the amount of packets that the destination node d is among packets received by the node n. And the average value of packet forwarding within the cluster is calculated in the same way as in equation (5). The third packet discard rate is the value measuring packets forwarded to other neighbor nodes among all packets received neighbor node n. If the value is high, the node can be suspected of being a selfish node.…”

Section: 𝐶 𝑘 (𝐴𝑣𝑔(𝑃mentioning

confidence: 99%

“…Nevertheless, there are many types of attacks in MANET because of many characteristics that are vulnerable to security. Therefore, an authentication technique through accurate trust evaluation of nodes participating in the network is very important [4,5]. The intrusion detection technique which is efficient for malicious nodes and minimizes the impact from these attacks is essential.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Performance Improvement of Intrusion Detection using Efficient Authentication and Distributed Monitoring

Yang¹

2022

IJCNIS

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In a Mobile Ad hoc Network (MANET), mobile nodes play multiple roles as hosts and routers and are dynamically changing multi-hop structures. MANET consists only of wireless nodes with limit processing power, and routing and data transfer are performed through cooperation with each other. It is exposed to many attack threats due to the dynamic topology by the movement of the nodes and the characteristic of multi-hop communication. Therefore, in MANET, a technique that can detect effectively must be applied while detecting malicious nodes and reducing the impact of various attacks. In this paper, we propose an trust based authentication technique for nodes and a distributed monitoring technique to improve the detection performance of malicious nodes. The hierarchical cluster structure was used to improve authentication of nodes and detection performance and management efficiency of malicious nodes. A lightweight authentication technique of member nodes in the cluster was applied and the efficiency of node authentication was improved. It was used to determine whether it was an attack node by transmitting traffic monitoring information for neighbor nodes to CA and using. In addition, the efficient authentication technique using only key exchange without anyone's help was applied in order to provide integrity when exchanging information between cluster heads. Through this, it was possible to be free from trust information about nodes and forgery and falsification of information about attack nodes. The superiority of the technique proposed in this paper was confirmed through comparative experiments with the existing intrusion detection technique.

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Section: Intrusion Detection Techniquesmentioning

confidence: 99%

Section: 𝐶 𝑘 (𝐴𝑣𝑔(𝑃mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Study on Performance Improvement of Intrusion Detection using Efficient Authentication and Distributed Monitoring

Yang¹

2022

IJCNIS

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“…MANET is more vulnerable than the wired network due to mobility of nodes and the way used to exchange of data packets and control packets, generally, they passed from the source to the destination via different intermediate nodes [11] that can be malicious nodes inside the network. OLSR routing protocol can be affected by many active routing attacks which reduce its performances, in following we present three main routing attacks have negative impacts on OLSR protocol:…”

Section: Manet Routing Attacksmentioning

confidence: 99%

Shapiro-Wilk Test to Detect The Routing Attacks In MANET

Nabou

Laanaoui

Ouzzif

et al. 2021

Preprint

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In the last recent years, the number of wireless devices has been growing and the security challenges increases too. Mobile Ad hoc Network (MANET) considers as a part of wireless network that connects mobile devices by using wireless channels without infrastructure. MANET use specific protocols to ensure the connectivity and exchange data between the source and destination. Optimized Link State Routing Protocol (OLSR) is a table-driven protocol that keep the route to all destination at any times, unfortunately it can be affected by many active routing attacks that reduce its performance by dropping the exchange packets or stopping the forward of data. In this paper we present a new approach to detect any active routing attacks by using the concept of Shapiro-Wilk test. Our method of detection is easy to implement and does not require any modification in the standard version of OLSR routing protocol as we will demonstrate by NS-3 simulations the detection of Black hole, Worm hole and Node isolation attacks that consider as most known attacks in MANET. A real experience is done by creating a small ad hoc network that connect six wireless devices by using OLSR protocol and finally we detect the presence of an active routing attack by applying our proposed method.

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“…Security is a paramount concern in MANETS due to having a dynamic topology and nodes that can easily enter or exit the network at any time and have access to data flow throughout the net-work. In addition, several mobile nodes are limited to resources in terms of computational power and energy source [2,3]. As such, the presence of permanent security monitoring nodes in the network is almost impossible due to limited resources, and there is a need for remote control of nodes' behavior in the network and determining security necessities in MANET [4,5].…”

Section: Introductionmentioning

confidence: 99%

Network Intrusion Detection System Based on the Combination of Multiobjective Particle Swarm Algorithm‐Based Feature Selection and Fast‐Learning Network

Einy

Öz

Navaei

2021

Wireless Communications and Mobile Computing

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Given the growth of wireless networks and the increase of the advantages and applications of communication networks, especially mobile ad hoc networks (MANETs), this type of network has attracted the attention of users and researchers more than before. The benefit of these types of networks in various kinds of networks and environments is that MANET does not require to hardware infrastructure to communicate and send and receive data packets within the network. It is one of the main reasons for using these MANET in various fields. On the other hand, the increased popularity of these networks has led to many challenges, one of the most important of which is network security. In this regard, a lack of regulatory and security infrastructure in MANETs has caused some problems in sending and receiving data, where intrusion in the network has been recognized as one of the most important issues. In MANETs, wireless notes act as a link between the source and destination nodes and play the role of relays and routers in the network. Therefore, malicious node penetration and the destruction of information packages become feasible. Today, intrusion detection systems (IDSs) are used as a solution to deal with the problem through remote monitoring of the performance and behaviors of nodes existing in wireless sensor networks. In addition to detecting malicious nodes in the network, IDSs can predict the behavior of malicious nodes in the future in most cases. Therefore, the present study introduced a network IDS (NIDS) entitled MOPSO-FLN by using a combination of multiobjective particle swarm optimization algorithm- (MOPSO-) based feature subset selection (FSS) and fast-learning network (FLN). In this work, we used the KDD Cup99 and dataset to select features, train the network, and test the model. According to the simulation results, this method was able to improve the performance of the IDS in terms of evaluation criteria, compared to other previous methods, by creating a balance between the objectives of the number of representative features and training errors based on the evolutionary power of MOPSO.

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Survey: Black Hole Attack Detection in MANET

Cited by 7 publications

References 2 publications

A Study on Performance Improvement of Intrusion Detection using Efficient Authentication and Distributed Monitoring

A Study on Performance Improvement of Intrusion Detection using Efficient Authentication and Distributed Monitoring

Shapiro-Wilk Test to Detect The Routing Attacks In MANET

Network Intrusion Detection System Based on the Combination of Multiobjective Particle Swarm Algorithm‐Based Feature Selection and Fast‐Learning Network

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