Multi-level trust based intelligence intrusion detection system to detect the malicious nodes using elliptic curve cryptography in MANET

Singh, Opinder; Singh, Jatinder; Singh, Ravinder

doi:10.1007/s10586-017-0927-z

Cited by 23 publications

(11 citation statements)

References 10 publications

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“…Perhaps this method performs attack detection; this method is not able to secure transmitted data. Blackhole attack, Grayhole attack and flooding attack were mitigated jointly by multi-level trust computation scheme [17]. Here Elliptic Curve Cryptography was used and the security was categorized into three levels.…”

Section: Survey On Attack Detection Methodsmentioning

confidence: 99%

Secure Group based Routing and Flawless Trust Formulation in MANET using Unsupervised Machine Learning Approach for IoT Applications

Ponguwala¹,

Rao²

2019

EAI Endorsed Transactions on Energy Web

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INTRODUCTION: Mobile Adhoc Network (MANET) is integrated with Internet of Things (IoT) in many application cases due to its flexibility and scalability. The dynamic nature of MANET introduces some security threats in IoT environment. In those threats, Blackhole attack and Grayhole attack are severe routing attacks that disrupts routing algorithm to crack transmission in the entire network. OBJECTIVES: Many security mechanisms are introduced in MANET based on trust computation schemes. However, computation of inaccurate trust value degrades the performance of mitigation schemes. Thus the major objective of this work is to design a novel security mechanism to protect the MANET-IoT from different adversaries. METHODS: in this paper we propose a novel group based routing algorithm with recommendation filtering supported by security monitors (SMs). Unsupervised machine learning algorithm is adapted for the purpose of recommendation filtering in the network. Initially the entire network is grouped by Secure Certificate based Group Formation (SCGF) algorithm. In each group, Recommendation Filtering by K-means algorithm (RF-K means) algorithm is employed to perform trust computation. For secure and optimal route selection, hybrid optimization algorithm that combines Genetic Algorithm and Fire Fly Algorithm (GA-FFA) is proposed. Data transmission is protected by novel Hash Message Authentication Code with Advanced Encryption Standard (HMAC-AES) algorithm in which hash function is integrated with cryptography function. RESULTS: The proposed work is validated in network simulator-3 environment and the obtained results show better performance in terms of packet delivery ratio (96.3%), throughput (135kbps), delay (3.26ms), detection rate (99%), and energy consumption (8.5%). CONCLUSION: The MANET-IoT network is secured by group formation and trust filtering approaches. Further, involvement of cryptography function ensures data security whereas hash function ensures data integrity..

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Section: Survey On Attack Detection Methodsmentioning

confidence: 99%

Secure Group based Routing and Flawless Trust Formulation in MANET using Unsupervised Machine Learning Approach for IoT Applications

Ponguwala¹,

Rao²

2019

EAI Endorsed Transactions on Energy Web

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“…The route overhead is extended regardless (P.Venkata Krishna et al,2012). An elliptic curve cryptography system for trust management to detect muggers.This approach removes malicious nodes from the network to achieve a greater packet delivery ratio, minimal delay, lowest packet loss, throughput, and successful end-toend delivery with elevated protection in mobile ad hoc network MANET, but it cannot identify when more attackers are possible (Opinder Singh et al,2017).…”

Section: Background and Related Workmentioning

confidence: 99%

“…The trust table ensures the effectiveness of the preceding multi-path communication intrusion detection in MANET. The next section deals with the formulation of the various trust models given as (Opinder Singh et al,2017).…”

Section: Build a Trust Table For The Nodes Of Manetmentioning

confidence: 99%

An energy efficient multipath routing protocol for MANET

Krishna¹,

Veeraiah

2022

JER is an international, peer-reviewed journal that publishes f

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Energy consumption is a critical consideration in mobile ad hoc networks because the majority of mobile nodes run on low battery resources. A hectic problem was the minimization of energy, which was solved by the use of multipath routing protocols. This article proposes an energy-efficient multi-path routing protocol supported by the MANET optimization algorithm. The energy efficiency within the MANET is efficiently achieved by the use of cluster head selection with fuzzy clustering and fuzz NB. Multipath routing can be achieved by integrating the bird swarm optimization algorithm (BSA) with the whale optimization algorithm (WOA), which is called the Bird Swarm-Whale Optimization Algorithm (BSWOA). Optimal route selection is predicated on fitness variables like connectivity between the nodes, energy consumption, the maximum trust value of the route, and throughput. In comparison to existing methods, the suggested BSWOA obtained a minimum energy consumption of 8.72 J, a minimum delay of 0.00333 msec, and a maximum throughput of 0.912 bps.

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“…This drawback is catered by using multicast approach for route reply in our proposal. Opinder et al in [11], proposed that for each node with public and private key used for encrypting and decrypting transmitted data with ECC. Dhiraj et al in [12] has proposed a detection and mitigation approach against Black-hole attacks using DYMO routing protocol.…”

Section: Literature Surveymentioning

confidence: 99%

Securing Mobile Adhoc Networks from Black-Hole Attacks

Taranum

Khan

2021

Frontiers in Artificial Intelligence and Applications

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MANETs are in-secure and vulnerable to attacks, as it lacks a central trusted authority. Providing security to such a network becomes an essential task and formulate the origin of the proposed work. The proposed system attempts to secure MANETs using route validation and cryptographic techniques. One of the most crucial, and primary concerns in today’s times is to be able to detect an attacker at its initial stages. With this focus point in mind, the approach used is to prevent such an attacks by detecting in initial stage and preventing from network degradation. The novelty of the proposal is the use of cryptographic techniques for improving the security, along a reverse-AODV for reducing path fail correction, and machine learning concepts for validation of results. Many of the existing malware detection techniques proposed by the researchers were executed either on machine independent platform, or on an available dataset with machine dependent approaches. This drawback has been addressed in the existing proposal, where in machine learning is used with self-generated data-set, to eliminate contingent problems. The proposed system includes a network that is free from malware. Justification of the results were generated using classifier tools that were trained with the obtained dataset. For secured communication, an Elliptical curve cryptographic algorithm is applied to reverse ad-hoc on-demand distance vector with reverse multiple route replies that have been generated from the destination to the source node. An investigation to ensure the correct delivery of data can be done by diverting the traffic through the shortest alternative secured path. The metrics used for statistical analysis include average transmission-delay, overhead, packet forwarding rate and packet- delivery-rate, based on which the conclusion is theorized for the detection. The major finding includes the process of selecting an appropriate condition for detecting a malicious node, observing the network behavior with varying number of suspicious nodes and then validating the correctness. The implementation gives us varied results, both when the suspicious node is deferred for some time, and then on its complete elimination. The limitation of the proposal is that the suspicious nodes are uncoordinated.

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Multi-level trust based intelligence intrusion detection system to detect the malicious nodes using elliptic curve cryptography in MANET

Cited by 23 publications

References 10 publications

Secure Group based Routing and Flawless Trust Formulation in MANET using Unsupervised Machine Learning Approach for IoT Applications

Secure Group based Routing and Flawless Trust Formulation in MANET using Unsupervised Machine Learning Approach for IoT Applications

An energy efficient multipath routing protocol for MANET

Securing Mobile Adhoc Networks from Black-Hole Attacks

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