With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights, which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks. Second, Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure, which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios. Finally, a comparative analysis was conducted. The proposed method demonstrated the highest Kendall coordination coefficient of 0.952. This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.
In order to solve the problems of existing fingerprint localization technology,such as large amount of fingerprint data,difficulty in storage and processing,and insufficient adaptability to positioning in complex spaces,a three-dimensional indoor space fingerprint localization solution based on massive multiple-input multiple-output(MIMO)system is proposed.First,an Angle Delay Channel Frequency Power(ADCFP)fingerprint matrix with faster processing speed and smaller storage requirements is proposed.Secondly,a new similarity criterion,namely chi-square distance,is introduced to improve the positioning accuracy,and then an improved power Weighted K-Nearest Neighbor(WKNN)matching algorithm is proposed.The impact of the power value on the weight reduction speed is different,and different weights are allocated according to the fingerprint similarity.Finally,three types of compressed fingerprints are obtained by using row-by-column compression of ADCFP,further reducing the amount of fingerprint data.And the Central Angle of Arrival(CAOA)Clustering Algorithm is introduced to shorten the positioning time.The simulation results show that the ADCFP fingerprint matrix can offer a 89.2% reliability for 2 m accuracy.The average positioning error using chi-square distance is reduced by 5.63% compared with that using the Manhattan distance.The improved power WKNN algorithm reduces the average localization error by 4.45% compared with the traditional WKNN algorithm.The introduction of CAOA Clustering Algorithm can increase the localization speed to 1.72 times that of the non-clustering case.The average localization error is reduced by 44.05% compared with the K-means Clustering Algorithm,and the positioning performance is greatly improved.
With regard to the covert communication system based on transform domain technique,the anti-interception performance of weighted fractional Fourier transform(WFRFT)communication systems is discussed.Theoretical analysis and simulation results illustrate that the communication system based on WFRFT has actual performance boundary of anti-detection and anti-recognition in which the covert performance remains unchanged as the number of weights is more than 4.In accordance with this problem,a cross-layer and parallel WFRFT covert communication system is proposed.Firstly,a parallel multi-channel WFRFT processing architecture is adopted to effectively increase the number of transformation parameters.Secondly,based on the tack of cross-layer design,the parameters of each WFRFT are controlled by the destination address which can further increase the difficulty in intercepting and recognizing signal for the non-cooperative receivers.The simulation results show that the cross-layer parallel WFRFT covert communication system is superior to the multi-parameter WFRFT covert communication system in terms of anti-detection and anti-modulation recognition.
In response to the problem of low accuracy in automatic modulation recognition under low signal-to-noise ratio(SNR)conditions,the authors propose a channel gated residual 2-network(Res2Net)convolutional neural network(CNN)model.The model mainly consists of two-dimensional CNN(2D-CNN),multi-scale Res2Net,squeeze-and-excitation network(SENet)and long short-term memory(LSTM)network,which extracts multi-scale features from raw I/Q data through convolution,adjusts the weight of feature channels through gating mechanism,and uses LSTM to model the sequence of convolutional features to ensure effective data feature mining,thereby improving the accuracy of automatic modulation recognition.The modulation recognition experiment on the benchmark dataset RML2016.10a shows that the recognition accuracy of the proposed model is 92.68%at 12 dB SNR,and the average recognition accuracy is above 91% when the SNR is greater than 2 dB.Compared with classical CLDNN model,LSTM model,similar PET-CGDNN model and CGDNet model,the proposed model can achieve higher modulation type recognition accuracy.
For the information security problem of energy reveiver as potential eavesdropper in multi-antenna simultaneous wireless information and power transfer(SWIPT)system,a physical layer security transmission scheme assisted by intelligent reflecting surface(IRS)and artificial noise is proposed.Firstly,considering the transmit power,energy harvesting threshold and unit module constraints of IRS,a nonlinear and multivariable coupling nonconvex problem is established.The beamforming matrix,artificial noise covariance matrix and phase shift matrix at IRS are jointly optimized to maximize the system secrecy rate.Then the nonconvex objective function is transformed equivalently based on mean square error criterion and the nonconvex energy harvesting constraints are treated by Successive Convex Approximation(SCA)method.Finally,the transmitter variables and IRS variables are obtained by Lagrangian dual method and the Majorization-Minimization(MM)algorithm based on price mechanism respectively.Simulation results show that the proposed algorithm can significantly increase the secrecy performance and guarantee the energy harvesting requirement as compared with existing schemes.
