Improving Network Security: An Intelligent IDS with RNN-LSTM and Grey Wolf Optimization by murtadha ali

“…Based on the behavior of grey wolf, an optimization technique GWO is implemented for intrusion detection to enhance accuracy and minimize false alarm in RNN-LSTM. Preprocess and segment network data with creating RNN-LSTM model for considering the dependence of our dataset Our approach improves the IDS performance by optimizing hyperparameters such as hidden layers, units, learning rates using GWO. …”
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Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism by Tom Burr, Michael S. Hamada, John Howell, Misha Skurikhin, Larry Ticknor, Brian Weaver

“…Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. …”
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Analysis of 6G and B5G waveforms using hybrid MF-ED and ECG-ED spectrum sensing techniques by Arun Kumar, Aziz Nanthaamornphong

“…Additionally, characteristics including bit error rate (BER), power spectral density (PSD), probability of detection (pd), and probability of false alarm (pfa) were researched and evaluated for 500 and 1000 samples. …”
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Detection Performance of Polarization and Spatial Diversities for Indoor GNSS Applications by Mohammadreza Zaheri, Ali Broumandan, Vahid Dehghanian, Gérard Lachapelle

“…Experimental results show that, for a given target detection performance in terms of the probability of false alarm and the probability of detection, the required input SNR level to meet the target detection performance can be significantly reduced utilizing the diversity system.…”
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Multiantenna Spectrum Sensing in the Presence of Multiple Primary Users over Fading and Nonfading Channels by Dayan Adionel Guimarães, Rausley Adriano Amaral de Souza, Guilherme Pedro Aquino

“…The basis of this paper is Wei and Tirkkonen, 2012, in which expressions for the key performance metrics of the sphericity test applied to the multiantenna cooperative spectrum sensing of multiple primary transmitters in cognitive radio networks over nonfading channels are provided. The false alarm and the detection probabilities were derived in Wei and Tirkkonen, 2012, based on approximations obtained by matching the moments of the test statistics to the Beta distribution. …”
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Exploring Contingency Skill Scores Based on Event Sizes by S. W. Kahler, H. Darsey

“…It is more important that large events be well forecasted than threshold events. In addition, false alarms may be useful when they match observed events just below the forecast threshold. …”
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Incoherent Integration Detection Method of Airborne Phased Array Radar in a Multipath Environment by Yili Hu, Yongbo Zhao, Sheng Chen

“…Considering these two characteristics, this paper first proposes a target pairing algorithm for matching the DP range and multipath range of the same target in signal detection, and then, combined with the cell-averaging constant false alarm rate (CA-CFAR) detection model, an incoherent integration detection method for airborne PAR in the multipath environment is proposed. …”
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Multivariate Statistics and Supervised Learning for Predictive Detection of Unintentional Islanding in Grid-Tied Solar PV Systems by Shashank Vyas, Rajesh Kumar, Rajesh Kavasseri

“…The resulting voltage and current data underwent dimensionality reduction using principal component analysis (PCA) which formed the basis for the application of Q statistic control charts for detecting the anomalous currents that could island the system. For reducing the false alarm rate of anomaly detection, Kullback-Leibler (K-L) divergence was applied on the principal component projections which concluded that Q statistic based approach alone is not reliable for detection of the symptoms liable to cause unintentional islanding. …”
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Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network by Geoffrey Eappen, Shankar T, Rajesh A

“…Numerical results demonstrate the superiority of the MeTa hybrid NN in terms of detection probability, false alarm probability, and convergence rate compared to existing conventional spectrum sensing schemes. …”
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WMSNs Data Hidden Anomaly Detection Based on OH-KFJLT Bloom Filter by Chenkai Xiao, Zhongsheng Li, Yanming Wu

“…In the simulation experiments conducted on the NAB, SMD, and COCO benchmark datasets, the False Alarm Rate (FAR) of the OFBFAD algorithm is all lower than 5%. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

“…The proposed AccFIT-IDS achieves 99.86% accuracy, with precision, recall and F1-score of 99.81%, 99.92% and 99.86%, respectively, and a false alarm rate of 0.0021, demonstrating its effectiveness.…”
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Robust Spectrum Sensing Demonstration Using a Low-Cost Front-End Receiver by Daniele Borio, Emanuele Angiuli, Raimondo Giuliani, Gianmarco Baldini

“…The design of SS algorithms is one of the most challenging tasks in CR and requires innovative hardware and software solutions to enhance detection probability and minimize low false alarm probability. Although several SS algorithms have been developed in the specialized literature, limited work has been done to practically demonstrate the feasibility of this function on platforms with significant computational and hardware constraints. …”
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Ultra-Short Wave Communication Squelch Algorithm Based on Deep Neural Network by Yuanxin Xiang, Yi Lv, Wenqiang Lei, Jiancheng Lv

“…In particular, the false alarm rate of the proposed squelch algorithm for non-stationary burst-like noise is significantly lower than that of traditional squelch methods.…”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…The empirical model based on the extra trees algorithm and fitted to class-balanced dataset via random oversampling and multicollinearity removed via principal component analysis proved to be the best, as it detected and classified osteosarcoma cancer in 10 ms with 97.8% area under the receiver operating characteristics curve and acceptably low false alarm and misdetection. Thus, the proposed models can be cutting-edge techniques for automated detection and classification of osteosarcoma tumors to aid timely diagnosis, prognosis, and treatment.…”
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FWA-SVM Network Intrusion Identification Technology for Network Security by Yaohui Zhang

“…The average detection rate of the raised method is 96.43%, the false alarm rate is 0.91, and the average correlation coefficient is as high as 0.987, which is better than the other four comparative algorithms. …”
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Audio classification using grasshopper‐ride optimization algorithm‐based support vector machine by Suryabhan Pratap Singh, Umesh Chandra Jaiswal

“…The analysis reveals that the proposed audio classification acquired the maximal accuracy of 0.96, minimal false alarm rate, and false rejection rate of 0.022 and 0.0119, respectively.…”
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A Machine Learning Approach to Predicting SEP Events Using Properties of Coronal Mass Ejections by Jesse Torres, Lulu Zhao, Philip K. Chan, Ming Zhang

“…Our algorithm achieves an average True Skill Statistic of 0.906, an average F1 score of 0.246, an average probability of detection of 0.920, and an average false alarm rate of 0.882. An analysis of the features shows that sunspot number and a feature based on Type II radio bursts contribute the most, but when grouped together, CME speed‐related features are the most important features.…”
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Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter by Siva Karteek Bolisetti, Mohammad Patwary, Khawza Ahmed, Abdel-Hamid Soliman, Mohamed Abdel-Maguid

“…The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. …”
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Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Chaofeng Wang, Yu Mao, Zhenghai Liu

“…The results demonstrate that the proposed method achieves a 99.17% accuracy rate in detecting unauthorized movements of radioactive materials, with a missed alarm rate of 0.72% and a false alarm rate of 0.1%. This method also enables real-time detection of unauthorized removal of radioactive materials and effectively enhances the security of radioactive materials during transport to reduce the risks of theft, loss, diversion, or sabotage.…”
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An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications by Luoyan Zhu, Yinsheng Liu, Danping He, Ke Guan, Bo Ai, Zhangdui Zhong, Xi Liao

“…Pertaining to the detection performance, constant false alarm ratio detector is applied to demonstrate the detection ability as a result of the processor by use of probability of detection (Pd).…”
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