Highly Secured Cluster Based WSN Using Novel FCM and Enhanced ECC-ElGamal Encryption in IoT

Reegan, A. Selva; Kabila, V.

doi:10.1007/s11277-021-08076-0

Cited by 25 publications

(11 citation statements)

References 36 publications

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“…In [25], the authors propose a clustering-based approach that employs fuzzy C-means and enhanced ECC-ElGamal encryption for secure data transmission in wireless sensor networks. The authors employ Koblitz's method to encode messages onto a curve point.…”

Section: Related Workmentioning

confidence: 99%

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Lahraoui,

Lazaar,

Amal

et al. 2024

Cryptography

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To ensure the security of sensitive data, elliptic curve cryptography (ECC) is adopted as an asymmetric method that balances security and efficiency. Nevertheless, embedding messages into elliptic curve (EC) points poses a significant challenge. The intricacies of this process can greatly affect the overall security and efficiency of the cryptosystem, reflecting security vulnerabilities observed in many existing schemes that utilize ElGamal ECC-based encryption. In this paper, we introduce an innovative hash-based technique for securely embedding messages into EC points before encryption. A random parameter and a shared secret point generated through the EC Diffie–Hellman protocol are used to bolster the scheme’s security. The security of the proposed method is evaluated against various attack models; moreover, the complexity, and sensitivity of the encryption scheme, as well as its inputs, are analyzed. The randomness assessment of the ciphertext was performed using the NIST statistical test suite. Additionally, we propose a mechanism to ensure the integrity of the message by securely appending a tag to the ciphertext. As a consequence, a comprehensive analysis of our scheme demonstrates its effectiveness in maintaining data security and integrity against various attack models. The algorithm also meets more criteria such as the strict avalanche criterion, linear complexity, and operability.

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Section: Related Workmentioning

confidence: 99%

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Lahraoui,

Lazaar,

Amal

et al. 2024

Cryptography

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“…CM modifies the output of FCM through its reliance on the produced centroid to re‐form the clusters into balanced sizes. Reegan and Kabila 122 provided a novel FCM and enhanced ECC‐ElGamal encryption‐based protocol to achieve secure transmission of data while reducing transmission time. Clusters are formed using FCM and the ideal CHs are selected using the clustering coefficient, which provides high neighboring nodes, a small distance to BS, and high residual energy.…”

Section: Solutionsmentioning

confidence: 99%

“…The work described in Moussaoui et al 115 uses unequal clustering in order to alleviate the load of CHs. In terms of security, previous works 109,120,122 provide secure transmission, while the protocol in Salman and Alisa 119 handles CHs failure by considering backup CHs, and the work in Wan et al 104 guarantees outlier diagnosis. Works in the literature 105,115,116,119 handle the dynamic aspect of IoT networks.…”

Section: Node Clusteringmentioning

confidence: 99%

Machine learning‐based clustering protocols for Internet of Things networks: An overview

Merah

Aliouat

Harbi

et al. 2023

Int J Communication

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Summary The Internet of Things (IoT) continues to expand the current Internet, opening the door to a wide range of novel applications. The increasing volume of the IoT requires effective strategies to overcome its challenges. Machine Learning (ML) has led to a growing technology that enables computers to solve problems without the need for knowledge of their intricate details. Over the past years, various ML techniques have been used to efficiently manage IoT networks. Clustering is a technique that has proven its performance in the networking domain. Many works in the literature have studied ML‐based clustering methods for IoT networks, including their main properties, characteristics, underlying technologies, and open issues. In this paper, we focus on topology‐centered ML‐based clustering protocols for IoT networks. Specifically, we investigate the potential benefits of adopting the clustering approach to address several IoT challenges. Moreover, we provide a comprehensive taxonomy of ML‐based clustering algorithms for IoT networks. Finally, we statistically analyze the incorporation of ML techniques for clustering in various IoT systems and highlight the related open issues.

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“…Packet Delivery Ratio is the ratio between the number of received packets at the BS and the amount of generated packets by the source that is shown in equation (10). On the contrary, PLR is the ratio among the lost packets and sent packets which are simplified as shown in equation (11).…”

Section: A Pdr and Plrmentioning

confidence: 99%

“…The sensors are formed into groups by a clustering process that gathers and transmits the data to the chosen Cluster Head (CH). Subsequently, the CH collects the data and broadcasted it to the BS that act as a bridge between the network and the end user [11] [12]. The sensors are generally located in the open and remote environment which creates the devices susceptible to security threats, specifically when malicious node attacks are occurring in the network [13] [14].…”

Section: Introductionmentioning

confidence: 99%

Secure Cluster-based Routing using TCSA and Hybrid Security Algorithm for WSN

Supriya,

Adilakshmi

2023

IJRITCC

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Wireless Sensor Network (WSN) is operated as a medium to connect the physical and information network of Internet-of-Things (IoT). Energy and trust are two key factors that assist reliable communication over the WSN-IoT. Secure data transmission is considered a challenging task during multipath routing over the WSN-IoT. To address the aforementioned issue, secure routing is developed over the WSN-IoT. In this paper, the Trust-based Crow Search Algorithm (TCSA) is developed to identify the Secure Cluster Heads (SCHs) and secure paths over the network. Further, data security while broadcasting the data packets is enhanced by developing the Hybrid Security Algorithm (HSA). This HSA is a combination of the Advanced Encryption Standard (AES) and Hill Cipher Algorithm (HCA). Therefore, the developed TCSA-HSA avoids malicious nodes during communication which helps to improve data delivery and energy consumption. The performance of the TCSA-HSA method is analyzed using Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), energy consumption, End to End Delay (EED), and throughput. The existing methods namely Optimal Privacy-Multihop Dynamic Clustering Routing Protocol (OP-MDCRP) and Secure and Energy-aware Heuristic-based Routing (SEHR) are used to evaluate the TCSA-HSA performances. The PDR of TCSA-HSA for 100 nodes is 99.7449%, which is high when compared to the OP-MDCRP and SEHR.

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Highly Secured Cluster Based WSN Using Novel FCM and Enhanced ECC-ElGamal Encryption in IoT

Cited by 25 publications

References 36 publications

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Machine learning‐based clustering protocols for Internet of Things networks: An overview

Secure Cluster-based Routing using TCSA and Hybrid Security Algorithm for WSN

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