Privacy preservation and protection for cluster based geographic routing protocol in MANET

Muthusenthil, B.; Murugavalli, S.

doi:10.1007/s11276-015-1135-5

Cited by 17 publications

(15 citation statements)

References 20 publications

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“…We describe the main metrics utilized for network estimation and also further introduce a new noise threshold criteria that is not considered in the prior works (Muthusenthil and Murugavalli, 2017). This helps us to evaluate the correctness of location information based on the direct symmetry test (DST).…”

Section: Metrics Utilized For Estimation In the Networkmentioning

confidence: 99%

Location Verification Technique for Cluster Based Geographical Routing in MANET

Muthusenthil¹,

Kim²,

Prasath³

2020

Informatica

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In mobile ad hoc network (MANET), routing has been the main issue because its high mobility and maintaining its routing structures are important requirements. Geographical routing mostly relies on real time location information, however, there exist lags in correctness of location information, and malicious nodes can cause troubles in accurate location tracking in the network. In order to ensure the correctness of location update information, in this paper, we propose a novel design based on a cluster based geographic routing (CBGR) formulation (Muthusenthil and Murugavalli, 2014), wherein we add a position verification technique based on a direct symmetry test (DST) to securely verify the location claims. We further introduce a new noise threshold parameter in the CBGR formulation to evaluate the correctness of location information based on a DST. Then a location based encryption scheme is employed to protect the estimated location against the eavesdropping attacks. With our simulation results, we show that the proposed location verification technique for CBGR (LVT-CBGR) network enhances the network security and performs better compared to other protocols in terms of performance metrics. The experimental outcomes illustrate the fact that our approach is well-geared to scale down the overall network expenditure.

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Section: Metrics Utilized For Estimation In the Networkmentioning

confidence: 99%

Location Verification Technique for Cluster Based Geographical Routing in MANET

Muthusenthil¹,

Kim²,

Prasath³

2020

Informatica

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“…Cluster based routing in MANETs can be differently classified. It may be classified as one hop clustering [25], [29], [30], [40], [45]- [53], multi hop clustering [28], [31], [34]- [36], [39], [42], [43], [54], [55], transmission range or signal strength based clustering [32], [33], [56]- [58] and zone based clustering [38]. MANETs can be classified based on a mobility model such as group mobility [51], [56], [59], [60], regular mobility [46] and random mobility [25], [28], [29], [31], [34], [35], [39], [40], [42], [44], [45], [48], [50], [52], [53], [55], [58], [61]- [64].…”

Section: How To Classify Clustering Schemes?mentioning

confidence: 99%

“…MANETs can be classified based on a mobility model such as group mobility [51], [56], [59], [60], regular mobility [46] and random mobility [25], [28], [29], [31], [34], [35], [39], [40], [42], [44], [45], [48], [50], [52], [53], [55], [58], [61]- [64]. The nature of events that take place in MANETs has a very strong impact on clustering process and the clustering process can be classified into proactive clustering [25], [26], [28], [29], [32], [43], [46], [48], [50], [52]- [55], [58]- [63], [65], reactive clustering [31], [36], [37], [40], [42], [47], [49], [51], [56], [57],…”

Section: How To Classify Clustering Schemes?mentioning

confidence: 99%

State-of-the-Art Clustering Schemes in Mobile Ad Hoc Networks: Objectives, Challenges, and Future Directions

et al. 2019

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Mobile ad hoc networks (MANETs) are self-organized networks without any fixed infrastructure. The topology changes are very frequent in MANETs due to nodes' mobility. The topology maintenance creates an extra overhead, as the mobility information of a single node is shared with all nodes in the network. To address the topology maintenance overhead problem in MANETs, the researchers proposed different cluster-based algorithms to reduce the size of a routing table. The clusters are formed to locally adjust the topology changes within the cluster. If a node wants to communicate with a node outside the cluster, it only communicates with its cluster head (CH). The CH communicates with other CHs to transmit data toward the destination. To efficiently utilize the clustering mechanism in MANETs, stable and balanced clusters are required. To form good quality and optimized clusters, some metrics, such as relative mobility (node speed and direction), node degree, residual energy, communication workload, and neighbor's behavior, are required. In this paper, we present a comprehensive survey of recent CAs in MANETs. We also present the objectives, goals, and contributions of recent research. Similarly, the findings, challenges, and future directions are stated. The validation of each proposed work is analyzed critically in terms of the mobility model, the simulation tool used during simulation, simulation metrics, and the performance metrics used in the validation process. INDEX TERMS MANETs, clustering algorithms, routing, cluster based MANET.

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“…Some lightweight encryption approaches [28], [29] for IoT are proposed, which can be used for geometric routing. Muthusenthil and Murugavalli [30] proposed a privacy preservation and protection for cluster based geographic routing protocol in MANET using the group signature and encryption. Roos et al [5] proposed anonymous addresses for geometric routing.…”

Section: Related Workmentioning

confidence: 99%

Lightweight Anonymous Geometric Routing for Internet of Things

Sun¹,

Wang²,

Li³

et al. 2019

IEEE Access

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Mobile service computing relies on efficient and secure data transfer. Geometric routing, which guarantees scalability, efficiency, and mobility, is a promising routing scheme for mobile services in the resource-constrained Internet of Things (IoT). However, the private data transmitted by geometric routing may be eavesdropped by the malicious node and the privacy-preserving becomes one of the important issues for the mobile service in IoTs. Due to the resource constrains, approaches using encryption or hashing are not suitable for geometric routing. In this paper, we propose a lightweight anonymous geometric routing (LAGER) to protect the node-related private data. Instead of using the encryption or hashing approach, LAGER adopts a coordinate confusion mechanism which provides each node an anonymous coordinate of virtual node, such that the private data is decoupled from the node coordinate. The malicious node cannot determine which node the data belongs to even if it obtains the private data. To support the data transmission with anonymous coordinates, LAGER adopts a hybrid routing scheme by combining the greedy routing and a source routing. The experiment results show that LAGER provides effective anonymity with acceptable costs of scalability and efficiency.

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Privacy preservation and protection for cluster based geographic routing protocol in MANET

Cited by 17 publications

References 20 publications

Location Verification Technique for Cluster Based Geographical Routing in MANET

Location Verification Technique for Cluster Based Geographical Routing in MANET

State-of-the-Art Clustering Schemes in Mobile Ad Hoc Networks: Objectives, Challenges, and Future Directions

Lightweight Anonymous Geometric Routing for Internet of Things

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