A Comprehensive Review and Performance Evaluation of Detection Techniques of Black Hole Attack in MANET

Hemrajani, Naveen; Jangir, Sunil Kumar

doi:10.3844/jcssp.2017.537.547

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…2 Literature Review Some of the most often used remedies to ad hoc networks and black-hole attack in MANETs are addressed in this section. Recent developments in this field have resulted in a slew of research [1] that has yielded a slew of effective models and routing protocols. Securing the linkages in the network design, particularly over unsecured means, is one of the most crucial difficulties.…”

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confidence: 99%

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Alkanhel¹,

El-kenawy²,

Abdelhamid³

et al. 2023

Computers, Materials &Amp; Continua

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In terms of security and privacy, mobile ad-hoc network (MANET) continues to be in demand for additional debate and development. As more MANET applications become data-oriented, implementing a secure and reliable data transfer protocol becomes a major concern in the architecture. However, MANET's lack of infrastructure, unpredictable topology, and restricted resources, as well as the lack of a previously permitted trust relationship among connected nodes, contribute to the attack detection burden. A novel detection approach is presented in this paper to classify passive and active black-hole attacks. The proposed approach is based on the dipper throated optimization (DTO) algorithm, which presents a plausible path out of multiple paths for statistics transmission to boost MANETs' quality of service. A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron (DTO-MLP), and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical (LEACH) clustering technique. MLP is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights of minor features. This hybrid method is primarily designed to combat active black-hole assaults. Using the LEACH clustering phase, however, can also detect passive black-hole attacks. The effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested approach. For diverse mobility situations, the results demonstrate 1906 CMC, 2023, vol.74, no.1 up to 97% detection accuracy and faster execution time. Furthermore, the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

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mentioning

confidence: 99%

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Alkanhel¹,

El-kenawy²,

Abdelhamid³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

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Enhanced Technique for Detecting Active and Passive Black-Hole Attacks in MANET

Eid

Hikal

2020

Advances in Intelligent Systems and Computing

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Detection of black-hole attacks in MANET using adaboost support vector machine

Hikal

Shams

Salem

et al. 2021

IFS

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Mobile Ad hock Networks (MANETs) are currently used for developing the privacy and accuracy of modern networks. Furthermore, MANET applications are fit to be data-oriented systems, that introduce a secure and more robust data transmission protocol making it a topmost priority in the design. The lack of infrastructure in the existence of dynamic topology as well as limited resources of MANET is a major challenge facing those interested in the field. Further, the nonexistence of a formerly authorized trust relationship within the connected nodes produces instability of the detection process in MANETs. Basically, by adding adapted LEACH routing protocol to MANET, enhancement of the preserved nodes vitality will be achieved, moreover, the load balancing with data loss reduction provides MANET ability to tracks along with shortest and limited paths. This paper proposes a newly developed detection scheme for both active and passive black-hole attacks in MANETs. Moreover, the scheme deals with assessing a group of selected features for each node-based AdaBoost-SVM algorithm. These features are collected from cluster members nodes based on Ad hoc On-demand Multipath Distance Vector (OMDV) with LEACH routing protocol clustering approaches. Although SVM is considered a more stable classifier, there are great influences of the AdaBoost weight adaption algorithm to enhance the classification process in terms of strengthening the weights of extracted features. This hybrid algorithm is essential for active black-hole attacks as well as for identifying passive black-hole attacks in MANET. The proposed scheme is tested against the effect of mobility variation to determine the accuracy of the detection process including the routing overhead protocol. The experimental results investigated that the accuracy of detecting both active and passive black-holes attacks in MANET reached 97% with a promising time complexity for different mobility conditions. Moreover, the proposed scheme provides an accurate decision about malicious vs benign node dropping behavior using an adjustable threshold value.

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A Comprehensive Review and Performance Evaluation of Detection Techniques of Black Hole Attack in MANET

Cited by 3 publications

References 17 publications

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Enhanced Technique for Detecting Active and Passive Black-Hole Attacks in MANET

Detection of black-hole attacks in MANET using adaboost support vector machine

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