Cybersecurity Issues in Wireless Sensor Networks: Current Challenges and Solutions

Boubiche, Djallel Eddine; Athmani, Samir; Boubiche, Sabrina; Toral-Cruz, Homero

doi:10.1007/s11277-020-07213-5

Cited by 51 publications

(65 citation statements)

References 79 publications

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“…WSN often operates in sectors like health care, climate change, room monitoring, agriculture, military, and other surveillance application. It operates the system as a group that collaborates with other neighbouring nodes and transmit data to the sink (Boubiche et al, 2020). Nodes in WSN are independent which can self-organize and self-healing.…”

Section: A Wireless Sensor Network Intrusion Detection System (Wsn-ids)mentioning

confidence: 99%

A Review of Support Vector Machine-based Intrusion Detection System for Wireless Sensor Network with Different Kernel Functions

Hamzah

Othman

2021

Int J Innov Comp

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Wireless sensor network (WSN) is among the popular communication technology which capable of self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions. WSN also is the most standard services employed in commercial and industrial applications, because of its technical development in a processor, communication, and low-power usage of embedded computing devices. However, WSN is vulnerable due to the dynamic nature of wireless network. One of the best solutions to mitigate the risk is implementing Intrusion Detection System (IDS) to the network. Numerous researches were done to improve the efficiency of WSN-IDS because attacks in networks has been evolved due to the rapid growth of technology. Support Vector Machine (SVM) is one of the best algorithms for the enhancement of WSN-IDS. Nevertheless, the efficiency of classification in SVM is based on the kernel function used. Since dynamic environment of WSN consist of nonlinear data, linear classification of SVM has limitations in maximizing its margin during the classification. It is important to have the best kernel in classifying nonlinear data as the main goal of SVM to maximize the margin in the feature space during classification. In this research, kernel function of SVM such as Linear, RBF, Polynomial and Sigmoid were used separately in data classification. In addition, a modified version of KDD’99, NSL-KDD was used for the experiment of this research. Performance evaluation was made based on the experimental result obtained. Finally, this research found out that RBF kernel provides the best classification result with 91% accuracy.

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Section: A Wireless Sensor Network Intrusion Detection System (Wsn-ids)mentioning

confidence: 99%

A Review of Support Vector Machine-based Intrusion Detection System for Wireless Sensor Network with Different Kernel Functions

Hamzah

Othman

2021

Int J Innov Comp

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“…In Boubiche et al, 71 the author talks about several studies that have been conducted for lightweight and efficient security protocols for WSNs. In this paper, the author reviews the most important protocols and categorize them based on the addressed security issue.…”

Section: Literature Reviewmentioning

confidence: 99%

An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks

Ali

Humaria

Ramzan

et al. 2020

International Journal of Distributed Sensor Networks

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In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.

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“…This concern for wireless security can be resolved conspicuously by the algorithms developed for ensuring security of the physical layer. Unlike the traditional cryptographic [1] techniques which can be decrypted by the intruder, PLS schemes [2][3][4][5][6] exploit the temporal variations and reciprocity property of the wireless channel. In the former case, if the intruder possess exceptional computational capabilities, the goal of breaking the secret key can be easily accomplished.…”

Section: Introductionmentioning

confidence: 99%

An Investigation of Secret Key Generation for Physical Layer Security Using Wavelet Packets

Ramanathan

Jayakumar

2021

Wireless Pers Commun

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This work investigates the effectiveness of wavelet packets in dynamic secret key generation (DSKG) for physical layer security (PLS). Preprocessing channel coefficients before quantization is highly essential in DSKG, as noisy measurements on direct quantization produces distinct keys at the transmitter and receiver. Secret keys generated will be having high key disagreement. The performance of different wavelets namely, Daubechies, Symlet and Coiflet, of orders 3 and 5, are studied using Spearman correlation coefficient, bit disagreement rate and NIST randomness tests. NIST tests are evaluated for different bit sequence lengths and as an outcome of the experiment, the best performing wavelet is identified. Further, the proposed work is compared with an existing scheme. It is inferred that, along with maintaining higher correlation coefficient, wavelet packet based DSKG scheme ensures an enhancement in PLS.

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Cybersecurity Issues in Wireless Sensor Networks: Current Challenges and Solutions

Cited by 51 publications

References 79 publications

A Review of Support Vector Machine-based Intrusion Detection System for Wireless Sensor Network with Different Kernel Functions

A Review of Support Vector Machine-based Intrusion Detection System for Wireless Sensor Network with Different Kernel Functions

An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks

An Investigation of Secret Key Generation for Physical Layer Security Using Wavelet Packets

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