Optimized Multi-level Data Aggregation Scheme (OMDA) for Wireless Sensor Networks

Ghai, Shilpy; Kumar, Vijay; Kumar, Ranvijay; Vaid, Rohit

doi:10.1007/978-981-15-7130-5_35

Cited by 4 publications

(6 citation statements)

References 29 publications

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“…This section provides a Dual Trust-based Multi-level Sybil Attack Detection Approach (DTMS). It consists of trust-based Sybil attack detection and employs an efficient data aggregation [55] at the cluster head. The scheme performs at three levels; CM-level, CH-level, and BS-level.…”

Section: Proposed Trust Evaluation Schemementioning

confidence: 99%

“…When a CH obtains data from any of its CM, it applies the ID verification, multi-trust (data trust and communication trust) evaluation. The data coming from CMs is aggregated using [55] and forwarded to BS via a single-hop structure. Verification: CH verifies the ID and location of the sender, i.e., the CM, which has sent data to the CH.…”

Section: Proposed Trust Evaluation Schemementioning

confidence: 99%

“…Aggregation: When BS receives data from all CHs in the network, it checks communication trust value is greater than the trust threshold ( T BS,CH C > Ø) and the reported data is successful. If the mentioned criteria hold BS, then accepts the data and perform aggregation using [55] same as on the CH-level.…”

Section: Iii) Dtms At Bs-levelmentioning

confidence: 99%

“…Check whether the data reported by node x is successful or not | data from (n-1) CMs[55] and send to BS.ElseCMx is a Sybil node. Delete the received data ENDAlgorithm 2: BS level: DTMS(Trust-based Sybil node Detection Algorithm) Input: Set of sensor nodes (SNs) S = {S 1 , S 2 , … , S n } and n is total number SNs The position (dimension) of SNs Trust threshold (Ø), energy threshold (£), error tolerance parameter (δ), misbehavior threshold (₥) Data(messages) forwarded from CHs Output: Detection of Sybil attack in WSN 4.1 Theoretical Analysis Theorem 1: "In CH to CM trust assessment as well as decision making, DTMS is potent against the selfish behavior of SNs.…”

mentioning

confidence: 99%

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DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

Khan

Singh

2023

Preprint

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Sensor network has been proven a promising technology for discerning data as well as details about the physical world. The sensor nodes are organized and positioned in an inaccessible and hostile environment and are consequently susceptible to various security attacks. Among the multiple attacks possible in any WSN, the Sybil attack is the most severe kind of attack. Detection of a Sybil node is a complex as well as challenging problem since it illegitimately uses multiple fraudulent identities to misguide and collapse the network. The paper proposes a dual trust-based multi-level Sybil (DTMS) attack detection approach in WSNs. The work engages a multi-level detection system grounded on verification of the node’s identity and location. Later, at each level, CM, CH, and BS, the trust value is calculated. For a satisfactory level of trust value, communication trust is calculated together with data trust. The trust function of DTMS involves dynamic reward and penalty coefficient to ensure severity. Besides, data aggregation is employed, which contributes to lesser communication overhead and energy consumption. The performance evaluation of DTMS is measured in terms of severity of trust function, true detection rate, false detection rate, residual energy, network lifetime, and packet loss ratio. The simulation results validate that DTMS can efficaciously detect Sybil nodes. Experiment results show that the proposed algorithm can detect [[EQUATION]] of Sybil nodes in the malicious environment. Additionally, the DTMS is compared with recent existing schemes in terms of various parameters (True Detection Rate, False Detection Rate, energy consumption, packet loss rate, number of alive nodes, etc.) which show that the DTMS performs desirably.

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Section: Proposed Trust Evaluation Schemementioning

confidence: 99%

Section: Proposed Trust Evaluation Schemementioning

confidence: 99%

Section: Iii) Dtms At Bs-levelmentioning

confidence: 99%

mentioning

confidence: 99%

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DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

Khan

Singh

2023

Preprint

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“…The present system on blockchain employs storage and high processing power. The huge amount of heterogeneous data in blockchain IoT, such as WSN outcomes in the consumption of huge energy at the time of data transmission from various sources [5][6][7]. Moreover, the major dispute in data aggregation is the data heterogeneity in the network.…”

Section: Introductionmentioning

confidence: 99%

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

Babu¹,

Jayalakshmi²

2021

IJACSA

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In wireless sensor networks (WSN), data aggregation is a widely used method. Security issues like data integrity and data confidentiality became a significant concern in data aggregation when the sensor network is deployed in a hostile environment. Many researches may carry out several works to tolerate these security issues. However, there were some limitations like delay, the arrival rate of packets, and so on. Hence, to overcome the existing problems, this approach offers a blockchain-dependent data aggregation scheme in WSN. The main intention of the proposed work is to generate a certificateless key generation so that the proposed system's secrecy rate is improved. The use of blockchain is employed for security purposes, and it enables the user to acquire the information stored internally in an effortless manner. Initially, deployment of sensor and base station (BS) is carried out, followed by node registration at which the public/private keys are generated. The computation of private hash values is carried by performing certificateless key generation. After that, the formation of blockchain is made using the PoW (Proof of Work) detection algorithm followed by the aggregation of data. In the data aggregation process, Elgammal based cryptographic approach is introduced to acquire member data, perform aggregation logic, and transfer the aggregated data. Finally, cluster-based routing is established with the use of Knapsack based cluster routing strategy. The performance investigation of the proposed system is estimated and the outcomes attained are compared with the existing techniques in terms of arrival rate, average delay, and the delay ratio of the packets. The investigation illustrates that the suggested approach is better than the traditional techniques.

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How to Optimally Reconfigure Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Kenyeres

2023

Software Engineering Application in Systems Design

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Optimized Multi-level Data Aggregation Scheme (OMDA) for Wireless Sensor Networks

Cited by 4 publications

References 29 publications

DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

DTMS: A Dual Trust-based Multi-level Sybil Attack Detection Approach in WSNs

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

How to Optimally Reconfigure Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

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