Preventing malicious packet dropping nodes in MANET using IFHM based SAODV routing protocol
TL;DR: The improved failure aware third party Auditor (IFTPA) based homomorphism linear authenticator (HLA) mechanism (IFHM) is proposed with the secured ad hoc on demand distance vector (SAODV) for trustworthiness verification of packet loss information and malicious node detection by dropping identifying of routing and data packet.
Abstract: MANETs have grown into a usually used network for countless applications. Mostly, a transmission medium perspective undergoes with thoughtful security worries, which may be focused to packet dropping. In the network, when packet forward the drooping of valuable packets may occur due to the presence of malicious nodes. The major sources in MANET for packet losses are malicious packet dropping and link error. A node can perform unkindly and could harm the process of sending the packet. In order to overcome the issues and to have an efficient detection process of malicious drop with better secure performances, the improved failure aware third party Auditor (IFTPA) based homomorphism linear authenticator (HLA) mechanism (IFHM) is proposed with the secured ad hoc on demand distance vector (SAODV). The proposed approach permitsthe trustworthiness verification of packet loss information and malicious node detection by dropping identifying of routing and data packet. Packet dropping is because of the both link error and occurrence of malicious nodes, which can identify by SAODV. To make certain efficiency, the authentication service is implemented in the protocol. However, to succeed storage scalability, the protocol implements the pseudo random function (PRF) in the system to fix the secret key of a client to its uniqueness using the secret key of its server.
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TL;DR: An efficient Digital Signature algorithm based on the elliptic curve cryptosystem is applied to routing protocol, and an improved security method suitable for on-demand routing protocol is proposed, and results show that the improved routing protocol can effectively improve the security of the UAV communication network.
Abstract: With the rapid development of information technology and the increasing application of UAV in various fields, the security problems of unmanned aerial vehicle (UAV) communication network have become increasingly prominent. It has become an important scientific challenge to design a routing protocol that can provide efficient and reliable node to node packet transmission. In this paper, an efficient Digital Signature algorithm based on the elliptic curve cryptosystem is applied to routing protocol, and an improved security method suitable for on-demand routing protocol is proposed. The UAV communication network was simulated through the NS2 simulation platform, and the execution efficiency and safety of the improved routing protocol were analyzed. In the simulation experiment, the routing protocols of ad-hoc on demand distance vector (AODV), security ad-hoc on demand distance vector (SAODV), and improved security ad-hoc on demand distance vector (ISAODV) are compared in terms of the performance indicators of packet delivery rate, throughput, and end-to-end delay under normal conditions and when attacked by malicious nodes. The simulation results show that the improved routing protocol can effectively improve the security of the UAV communication network.
14 citations
01 Jan 2020
TL;DR: This paper proposed a selfish node detection algorithm (SNDA) for identifying and isolation of selfish node from the network for mobile ad hoc network.
Abstract: Mobile Ad hoc Network is a collection of autonomous mobile nodes connected with each other without any central coordinator. There is several security issues arise in MANET due to dynamically changing network topology. The reliable communication is achieved only when there exists cooperation among the mobile nodes in MANET. Due to the lack of resources some mobile nodes refuse to forward the packet to other nodes. This type of nodes is called the selfish nodes. These kind of selfish nodes in the route degrade the overall performance of the whole network. In this paper we discussed about the various selfish node detection methods and propose a selfish node detection algorithm (SNDA) for identifying and isolation of selfish node from the network.
10 citations
Cites background from "Preventing malicious packet droppin..."
...A MANET is a collection of autonomous mobile nodes with no central coordinator connected to each other [1][10]....
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TL;DR: Comparative analysis reveals that the proposed trust evaluation model outperforms the competitive trust evaluation models in terms of various performance metrics such as routing overheads, average end to end latency, packet delivery ratio, and throughput, and the proposed protocol is more secure against various security threats.
Abstract: Recently Mobile adhoc networks (MANETs) have received the great attention of researchers as these models provide a wide range of applications. But MANET nodes are prone to various security threats. To overcome this issue, many trust management frameworks have been implemented in the literature. It has been found that the use of machine learning can predict trust values more efficiently. However, machine learning performance suffers from the hyper-parameters tuning and over-fitting issues. Therefore, in this paper, novel trust management is proposed. initially, the Adaptive neuro-fuzzy inference system (ANFIS) is used to train the trust prediction model. Thereafter, a non-dominated sorting genetic algorithm-III (NSGA-III) is used to tune the hyper-parameters of the ANFIS model. Precision, recall, and root mean squared error metrics are used to design a multi-objective fitness function. Optimized link state routing (OLSR) protocol is used for comparative analyses purpose. Three different attacks are applied on the designed network i.e., link spoofing, jellyfish, and gray hole attacks to obtain the dataset. Comparative analysis reveals that the proposed trust evaluation model outperforms the competitive trust evaluation models in terms of various performance metrics such as routing overheads, average end to end latency, packet delivery ratio, and throughput. Thus, the proposed protocol is more secure against various security threats.
6 citations
01 Feb 2020
TL;DR: A fresh algorithm known as Multi-Keyword Interrogation Scheme (MKIS) algorithm is recommended, which lessens the maintenance overhead to a greater scope when the keyword dictionary expansion occurs dynamically.
Abstract: Cloud based computing is a skill which provide communications for large scale storage of data, along with its refine and assigning. The security and retreat become main concern for uploading sensitive data without any information leak. This can be achieved by the cloud servers by integrating the encryption techniques into it, which becomes a major objection to guide the efficient keyword based questions and the encrypted data of the matching results. The searching can be an interrogation technique which is either based on a single keyword or multi-keyword as input. In this paper, a fresh algorithm known as Multi-Keyword Interrogation Scheme (MKIS) algorithm is recommended. It lessens the maintenance overhead to a greater scope when the keyword dictionary expansion occurs dynamically. The experimental results show that MKIS presents excellent performance when compared with the existing schemes. The proposed technique is presented in 2 aspects: many-keyword graded the look to attain exact look for output and meaning-based explore to maintain synonym questions. Search Terms— Cloud based computing, Multi-keyword interrogation, Data encryption, Security preserving, semantic grilling.
5 citations
Cites background from "Preventing malicious packet droppin..."
...Vanitha and Zubair (2019) developed a protocol to control the packet loss using routing protocols[14]....
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TL;DR: The selfish node identification using hash function and positioning update using AODV-PSNHF method provides reliable and secure data transmission under selfish nodes and shows better performance in terms of throughput, packet delivery ratio and packet loss.
Abstract: Mobile ad hoc network is a self-organizing wireless network, which is formed by the wireless mobile devices without any centralized infrastructure. The mobile nodes in the network are mainly affected by the inherent characteristics such as unpredictable network topology and open wireless medium. Especially, the presence of selfish nodes in the network creates the packet loss and affects an entire communication system. In this paper, the hash function with position updating algorithm is proposed in the Ad hoc On-Demand Distance Vector (AODV) routing protocol for improving the security against the selfish nodes. The AODV routing protocol is used to transmit the data packets from the source to the destination. Therefore, the Prevention of Selfish Node using Hash Function (PSNHF) with position update algorithm is proposed for minimizing the packet loss through the network. The performances of proposed AODV-PSNHF method are analysed in terms of energy consumption, throughput, Packet Delivery Ratio (PDR), packet loss and normalized routing load. In addition, the AODV-PSNHF method is compared with the existing trust-aware ad-hoc routing protocol (T2AR). The selfish node identification using hash function and positioning update using AODV-PSNHF method provides reliable and secure data transmission under selfish nodes and shows better performance in terms of throughput, packet delivery ratio and packet loss. For 2% of malicious nodes the PDR of the AODV-PSNHF method is 89%, it is 9% higher when compared to the T2AR protocol whose PDR% is only 80% for the same.
3 citations
References
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TL;DR: A homomorphic linear authenticator (HLA) based public auditing architecture is developed that allows the detector to verify the truthfulness of the packet loss information reported by nodes, and a packet-block-based mechanism is proposed, which allows one to trade detection accuracy for lower computation complexity.
Abstract: Link error and malicious packet dropping are two sources for packet losses in multi-hop wireless ad hoc network. In this paper, while observing a sequence of packet losses in the network, we are interested in determining whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop. We are especially interested in the insider-attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy. To improve the detection accuracy, we propose to exploit the correlations between lost packets. Furthermore, to ensure truthful calculation of these correlations, we develop a homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes. This construction is privacy preserving, collusion proof, and incurs low communication and storage overheads. To reduce the computation overhead of the baseline scheme, a packet-block-based mechanism is also proposed, which allows one to trade detection accuracy for lower computation complexity. Through extensive simulations, we verify that the proposed mechanisms achieve significantly better detection accuracy than conventional methods such as a maximum-likelihood based detection.
59 citations
"Preventing malicious packet droppin..." refers background in this paper
...Generally, security is most needs process in communication for nodes preventing from threats [10]....
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16 Apr 2012
TL;DR: A homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes, and achieves significantly better detection accuracy than conventional methods such as a maximum-likelihood based detection.
Abstract: In a multi-hop wireless ad hoc network, packet losses are attributed to harsh channel conditions and intentional packet discard by malicious nodes. In this paper, while observing a sequence of packet losses, we are interested in determining whether losses are due to link errors only, or due to the combined effect of link errors and malicious drop. We are especially interested in insider's attacks, whereby a malicious node that is part of the route exploits its knowledge of the communication context to selectively drop a small number of packets that are critical to network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy. To improve the detection accuracy, we propose to exploit the correlations between lost packets. Furthermore, to ensure truthful calculation of these correlations, we develop a homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes. This architecture is privacy preserving, collusion proof, and incurs low communication and storage overheads. Through extensive simulations, we verify that the proposed mechanism achieves significantly better detection accuracy than conventional methods such as a maximum-likelihood based detection.
18 citations
12 Mar 2015
TL;DR: Various machine learning techniques are studied as artificial neural network, support vector machine, decision tree, Q-learning, Bayesian network for identifying the malicious nodes and future behaviors of the nodes are predicted with supervised, un-supervised, reinforcement machinelearning techniques.
Abstract: Mobile ad-hoc networks have to suffer with different types of packet dropping attacks. Therefore, we need strong mechanism to detect these malevolent nodes and to classify normal and abnormal nodes as per the behavior of nodes. Machine learning techniques distinguish outlier nodes quickly and accurately provide classification by observing behavior of those nodes in the network. In this paper, we study various machine learning techniques as artificial neural network, support vector machine, decision tree, Q-learning, Bayesian network for identifying the malicious nodes. These techniques are able to detect black hole, gray hole, flooding attacks and other packet dropping attacks. These types of misbehaving nodes are identified and future behaviors of the nodes are predicted with supervised, un-supervised, reinforcement machine learning techniques.
15 citations
"Preventing malicious packet droppin..." refers background in this paper
...Here, the case of inner threats is considered to know the details of the network efficiency after the effects of attack [6]....
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01 Sep 2016
TL;DR: This paper analysed nature of packet dropping and bandwidth attack based on AODV routing protocol on MANET, and proposed node bypassing technique to detect such kind of attacks.
Abstract: Mobile adhoc network is a wireless network. Which forwards the information in forms of packets either data packet or control packet from source to destination. It is a collection of mobile devices that can move from one direction to other that is the reason the topology is not fixed, and does not required any prefix infrastructure for configuring MANET. All devices under network can communicate with each other within a range. Packet dropping and bandwidth attacks are one of major concern on mobile adhoc network. If enough security measures are not their then the attacker nodes significantly degrades the performance of the network. This paper analysed nature of packet dropping and bandwidth attack based on AODV routing protocol on MANET, and proposed node bypassing technique to detect such kind of attacks.
5 citations
"Preventing malicious packet droppin..." refers background in this paper
...The major sources in MANET for packet losses are malicious packet dropping and link error....
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...Here, an secured ad hoc on demand distance vector (SAODV) protocol is introduced and implemented, which can identify the attack packet truthfully in MANET....
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...Generally, the connection of mobile devices is considered with the least infrastructure of self-configuration by using medium of wireless in the network of mobile ad hoc network (MANET)....
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...The packet dropping in the routing protocol is exposed in the nature of portable and mobility of mobile ad hoc networks (MANET) [8]....
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...In MANETs, the protocol of routing assumption is to cooperative and significant in the same way of every nodes....
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TL;DR: A mechanism which will detect the malicious packet dropping by using the correlation between packets, and an auditing architecture based on homomorphic linear authenticator can be used to ensure the proof of reception of packets at each node.
Abstract: In wireless ad hoc network, packet loss is a serious issue. Either it is caused by link errors or by malicious packet dropping. The malicious nodes in a route can intentionally drop the packets during the transmission from source to destination. It is difficult to distinct the packet loss due to link errors and malicious dropping. Here is a mechanism which will detect the malicious packet dropping by using the correlation between packets. An auditing architecture based on homomorphic linear authenticator can be used to ensure the proof of reception of packets at each node. Also to ensure the forwarding of packets at each node, a reputation mechanism based on indirect reciprocity can be used.
4 citations
"Preventing malicious packet droppin..." refers methods in this paper
...The detecting of dropping packet with error rate and accuracy is proceeding by conventional approach [4]....
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