Hidradenitis suppurativa/Acne inversa in der Genitoanalregion

Hessam, Schapoor; Bechara, F. G.

doi:10.1007/s00105-020-04556-9

Cited by 3 publications

(1 citation statement)

References 36 publications

(38 reference statements)

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“…FC is demanded to gather all compressed observations from each sensing CR receiver in the form of CS matrix considered as the input of multivariate Gaussian distribution (MGD) detector for making decision. Centralized cooperative CR strategy is presented in Hessam et al 10 FC is usually supposed in centralized or distributed collaborative SS schemes. However, the FC can be sensitive to JAs alike if it is relatively more secure than collaborative CR users.…”

Section: Introductionmentioning

confidence: 99%

Quickest physical‐layer MGD anomaly detection for jamming attacks in centralized modulated wideband converter‐based ROC curve

Moumena

2019

Int J Communication

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Summary In wireless communication systems, physical‐layer security menaces have evolved from jammers. Jammers, due to their furtive nature, make wireless communication systems vulnerable. The novelty in this work is to combine centralized modulated wideband converter, which is a networking system developed from the modulated wideband converter–based sub‐Nyquist sampling theory with a multivariate Gaussian distribution (MGD) anomaly detector‐based receiver operating characteristic curve that plot the detection rate (DR) versus false alarm rate (FAR) at various threshold values. We supposed the presence of a group of jammers in the spectrum corrupted with the primary source signal and noise. The received primary signal at each cognitive radio (CR) receiver is converted in to a digital signal using an analog‐to‐information converter. Each CR receiver give minimum number of samples denoted N1. All these compressed samples from every CR receiver are collected in the form of matrix called compressed sampling matrix, which is considered directly as the input of the MGD detector. The intelligent MGD detector proposed in the level of fusion center is based on the characteristics of the MGD. The numerical results show that this new system of combination detects faster anomalies perfectly in the presence of jammers in the spectrum in real‐time scenarios. Performance evaluation is performed in terms of DR versus FAR at different detection threshold values, under the presence of attacks in the system. By employing well‐known machine learning algorithms called MGD, the performance of this new proposed system shows good.

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Section: Introductionmentioning

confidence: 99%