Lightweight Anonymous Geometric Routing for Internet of Things

Sun, Yanbin; Wang, Yuhang; Li, Mohan; Su, Shen; Wang, Xianzhi; Fan, Dunqiu

doi:10.1109/access.2019.2902621

Cited by 12 publications

(8 citation statements)

References 35 publications

(37 reference statements)

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“…The proposed chronological ASO algorithm is compared with the existing methods, like FGSA [5], ASO [11], Lightweight anonymous geometric routing [10], LASeR [3].…”

Section: Comparative Methodsmentioning

confidence: 99%

Katsinovas Framework Prototype Apps Hardware as based Innovation Readiness Level

Waliulu*,

Saptono,

Suryani

et al. 2020

IJITEE

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Internet of Things (IoT) is a developing technology used for enhancing the communication and providing flexibility to humans. The data packets are transmitted through better routing path using the IoT nodes in the network. This research presents an effective optimization algorithm for selecting the effective routing path for the transmission of the speech signal to the destination effectively. The optimization algorithm namely, chronological atom search optimization (chronological ASO) algorithm is developed for selecting the routing path. The chronological ASO algorithm is developed by integrating the chronological concept in ASO algorithm. After the initialization of the network, the effective routing path is selected using the fitness parameters, such as energy, delay and distance. Then, the speech signal is transmitted from the source node to the destination node by selecting the routing path having maximum fitness function. The performance analysis of the proposed chronological ASO algorithm is done based on the metrics, such as energy, throughput, and PDR. When compared to the existing methods, the proposed method provided a maximal energy of 0.2375, maximal PDR of 46.1538, and maximal throughput of 0.0792 for 50 nodes and obtained a maximal energy of 0.1381, maximal PDR of 32.0988, and maximal throughput of 0.0395, respectively.

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“…The proposed chronological ASO algorithm is compared with the existing methods, like FGSA [5], ASO [11], Lightweight anonymous geometric routing [10], LASeR [3].…”

Section: Comparative Methodsmentioning

confidence: 99%

Katsinovas Framework Prototype Apps Hardware as based Innovation Readiness Level

Waliulu*,

Saptono,

Suryani

et al. 2020

IJITEE

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“…Liu et al [24] have implemented a scheme towards resisting sink hole attack in IoT using probing routes considering consumption of network energy. Usage of geometric-based communication scheme anonymously is presented by Sun et al [25] where hashing-based encryption has been utilized to ensure data privacy. Haseeb et al [26] have presented a trust-based security scheme for mesh network in IoT considering cost of link and dissemination of data.…”

Section: Related Workmentioning

confidence: 99%

Secure Inter-Domain Routing for Resisting Unknown Attacker in Internet-of-Things

Bhavana¹,

N²

2022

IJACSA

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With an increasing adoption of Internet-of-Things (IoT) over massively connected device, there is a raising security concern. Review of existing security schemes in IoT shows that there is a significant trade-off due to non-adoption of interdomain routing scheme over larger domain of heterogeneous nodes in an Internet of Things (IoT) via gateway nodes. Hence, the purpose of the proposed study is to bridge this trade-off by adopting a new security scheme that works over an inter-domain routing without any apriori information of an attacker. The goal of the proposed framework is to identify the malicious intention of attacker by evaluating their increasing attention over different types of hop links information. Upon identification, the framework also aims for resisting attacker node to participate in IoT environment by advertising the counterfeited route information with a target of misleading the attackers promoting autonomous self-isolation. The study outcome shows proposed scheme is secure compared to existing scheme.

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“…To calculate the private data of nodes, Sun, Y et al [12] presented (LAGER) Lightweight Anonymous Geometric Routing model. This approach was employed coordinate confusion model, and it afforded anonymous coordinate between virtual nodes.…”

Section: Literature Surveymentioning

confidence: 99%

“…In addition, security is a major topic of researchers for mobile services in IoT, for instance network attacks [13] [12], IoT device security, privacy protection, content security and so on. Meanwhile, early geometric routing techniques [14] [15] [12] expose physical position, such as GPS coordinates, as node coordinates for greedy forwarding. For lightweight anonymous routing, however these techniques are not suitable.…”

Section: Introductionmentioning

confidence: 99%

TH-FLICM: Tversky Hillenger Distance-Based Fuzzy Local Information C- Means Clustering Algorithm For Effective Cluster Head Selection In Iot Routing

Kore¹,

Mishra²

2022

Preprint

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In recent days, Internet of things (IoT) technology received more consideration from both academia and industry. IoT is a system that combines several computing devices, and digital tools offered by means of exclusive identifiers, which have capacity to transport data over a network through optimal path. Thus, dependable and secure IoT communication and correlation is necessary for appropriate operation of IoT network and the best strategy to attain a robustness security in an IoT network is to permit and generate trusted path between the nodes. An existing IoT models experienced a numerous decisive problems, namely cluster based trust techniques for IoT networks and attack identification of IoT trusted schemes from the malicious nodes, like poor Internet service providers. In this paper, Tversky hillenger distance-based Fuzzy Local Information C-Means clustering (Tversky hillenger distance-based FLICM clustering) approach is developed for Cluster Head Selection (CHS) in IoT routing. Accordingly, the developed Tversky hillenger distance-based FLICM clustering is newly designed by integrating tversky index, hillenger distance and FLICM clustering model. Moreover, Rider Foraging Optimization (RFO) algorithm is also employed in order to perform secure routing process. Besides, the developed Tversky hillenger distance-based FLICM model achieves better performance with respect to throughput, delay and energy consumption of 0.4390, 0.5882s, and 0.5614J.

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Lightweight Anonymous Geometric Routing for Internet of Things

Cited by 12 publications

References 35 publications

Katsinovas Framework Prototype Apps Hardware as based Innovation Readiness Level

Katsinovas Framework Prototype Apps Hardware as based Innovation Readiness Level

Secure Inter-Domain Routing for Resisting Unknown Attacker in Internet-of-Things

TH-FLICM: Tversky Hillenger Distance-Based Fuzzy Local Information C- Means Clustering Algorithm For Effective Cluster Head Selection In Iot Routing

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