Efficient physical intrusion detection in Internet of Things: A Node deployment approach

Halder, Subir; Ghosal, Amrita; Conti, Mauro

doi:10.1016/j.comnet.2019.02.019

Cited by 20 publications

(6 citation statements)

References 38 publications

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“…Formula (28) belongs to the revenue function. Players in each game need to actively change their action tactics to maximize the revenue value, check malicious attacks in the mobile network according to the revenue function, and delete the combination of malicious nodes to improve the security performance of the mobile network [12][13][14].…”

Section: Optimization Methods Of Practical Byzantine Fault-mentioning

confidence: 99%

Intrusion Detection Analysis of Internet of Things considering Practical Byzantine Fault Tolerance (PBFT) Algorithm

Chen

Lin

2021

Wireless Communications and Mobile Computing

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In order to improve the security performance and accuracy of the Internet of things in the use process, it is necessary to use the Internet of things intrusion detection method. At present, the problem of inconsistency between the accuracy of detection results and nodes is more prominent when the Internet of things intrusion detection methods are running. This paper proposes a practical Byzantine fault-tolerant intrusion detection method for the use process of the Internet of things. This method introduces the intrusion detection method and the operation function of foreign attackers on the basis of practical Byzantine fault tolerance; using the expected utility function to the corresponding benefit function of practical Byzantine fault tolerance, the results of Internet of things intrusion detection model can be effectively calculated. Finally, the experimental results show that compared with the existing intrusion detection methods, the proposed method can effectively reduce the energy consumption of the Internet of things in the operation process, can effectively reduce 14.3% and 7.8%, and can effectively reduce the energy consumption of the Internet of things in the operation process.

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Section: Optimization Methods Of Practical Byzantine Fault-mentioning

confidence: 99%

Intrusion Detection Analysis of Internet of Things considering Practical Byzantine Fault Tolerance (PBFT) Algorithm

Chen

Lin

2021

Wireless Communications and Mobile Computing

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“…Though the approach is novel, it is unable to prove its strength in the environment of IoTs as the number of nodes (devices and connections) is large and optimal solution for the incentive is complex with dynamic situations. Energyefficient and quick detection of intrusion is well experimented based on Gaussian distribution [19]. The method emphasizes on the connections among nodes and establishes a relationship among the network parameters and the detection capability.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Intrusion Detection in Edge Computing Using Cerebellar Model Articulation Controller and Spline Fit

Kumar

Saha

Conti

et al. 2023

IEEE Trans. Serv. Comput.

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“…A reduction of sensory operations while making sure that there is no loss in coverage of the network and at an acceptable distortion margin [8] [20].…”

Section: Sampling Compressionmentioning

confidence: 99%

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

et al. 2022

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There is continuous intensive research on image compression techniques in wireless sensor networks (WSNs) in the literature. Some of the image compression techniques in WSNs that exist in the literature include discrete cosine transform (DCT), discrete waveform transforms (DWT), set partitioning in a hierarchical tree (SPIHT), and embedded zero tree wavelet (EZW) coding. Research on image compression in WSNs is necessitated by the need to improve the energy efficiency of sensor nodes and WSNs' lifetimes without compromising the quality of the reconstructed data. Several approaches have been developed centered around image compression and other factors in trying to limit the energy consumption of sensor nodes. Most of these approaches do not provide the error-bound mechanism that balances the rate of compression and distortion of the reconstructed image. Therefore, in this paper, a review and analysis of image compression techniques and approaches in WSNs are conducted. Available image compression approaches in WSNs in literature were then classified according to the image compression technique adopted, and their strengths and weaknesses were highlighted. In addition, a rate-distortion balanced data compression algorithm with error bound mechanism based on artificial neural networks (ANN) in the form of an autoencoder (AE) was coded and simulated in MATLAB before being evaluated and compared to the conventional approaches. The experimental results show that the simulated algorithm has less root mean square error (RMSE) and a higher coefficient of determination (𝑅 2 ) values on variable compression ratios as compared to the Principal Component Analysis (PCA), Discrete Cosine Transform, and Fast Fourier Transform (FFT) when using the Grand-St-Bernard metrological dataset. Furthermore, it presented less RMSE, and higher compression ratio values compared to the Lightweight Temporal Compression (LTC) algorithm on variable error bounds when using the LUCE metrological dataset. Therefore, it was found that the simulated algorithm presents better compression fidelity as compared to the conventional approaches without an error-bound mechanism. Moreover, the algorithm analyzed presents a significant approach to balancing the compression ratio and reconstructed data quality through its error-bound mechanism.

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Efficient physical intrusion detection in Internet of Things: A Node deployment approach

Cited by 20 publications

References 38 publications

Intrusion Detection Analysis of Internet of Things considering Practical Byzantine Fault Tolerance (PBFT) Algorithm

Intrusion Detection Analysis of Internet of Things considering Practical Byzantine Fault Tolerance (PBFT) Algorithm

Adaptive Intrusion Detection in Edge Computing Using Cerebellar Model Articulation Controller and Spline Fit

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

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