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Titlebook: Computational Intelligence, Cyber Security and Computational Models. Models and Techniques for Intel; 4th International Co Suresh Balusamy,

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31#
發(fā)表于 2025-3-26 21:38:36 | 只看該作者
Conference proceedings 20203 2019, which was held in Coimbatore, India, in December 2019.?.The 9 papers presented in this volume were carefully reviewed and selected from 38 submissions. They were organized in topical sections named: computational intelligence; cyber security; and computational models..
32#
發(fā)表于 2025-3-27 01:27:42 | 只看該作者
Conference proceedings 20203 2019, which was held in Coimbatore, India, in December 2019.?.The 9 papers presented in this volume were carefully reviewed and selected from 38 submissions. They were organized in topical sections named: computational intelligence; cyber security; and computational models..
33#
發(fā)表于 2025-3-27 06:47:36 | 只看該作者
Etappe 1: Strategien der Personalentwicklungor android malware detection techniques such as signature, anomaly and topic modelling based. The proposed methods also evaluated with system accuracy, analysis types and benefits and limitations of each proposed frameworks.
34#
發(fā)表于 2025-3-27 10:01:44 | 只看該作者
Etappe 2: Steuerung der Personalentwicklungrch problems in image processing and vision fields, is not explored much for IDS. In this paper, a DCNN architecture for IDS which is trained on KDDCUP 99 data set is proposed. This work also shows that the DCNN-IDS model performs superior when compared with other existing works.
35#
發(fā)表于 2025-3-27 14:05:46 | 只看該作者
36#
發(fā)表于 2025-3-27 19:03:40 | 只看該作者
https://doi.org/10.1007/978-3-540-29574-7probabilities are obtained in terms of confluent hyper geometric series and modified Bessel’s function of first kind using Laplace transform, continued fractions and generating function methodologies. Numerical illustrations are added to depict the effect of variations in different parameter values on the time dependent probabilities.
37#
發(fā)表于 2025-3-28 01:17:12 | 只看該作者
38#
發(fā)表于 2025-3-28 05:15:58 | 只看該作者
DCNN-IDS: Deep Convolutional Neural Network Based Intrusion Detection Systemrch problems in image processing and vision fields, is not explored much for IDS. In this paper, a DCNN architecture for IDS which is trained on KDDCUP 99 data set is proposed. This work also shows that the DCNN-IDS model performs superior when compared with other existing works.
39#
發(fā)表于 2025-3-28 09:59:22 | 只看該作者
Deep Learning Based Frameworks for Handling Imbalance in DGA, Email, and URL Data Analysishan the cost-insensitive approaches. This is mainly due to the reason that cost-sensitive approach gives importance to the classes which have a very less number of samples during training and this helps to learn all the classes in a more efficient manner.
40#
發(fā)表于 2025-3-28 13:04:35 | 只看該作者
An , Queueing Model Subject to Differentiated Working Vacation and Customer Impatienceprobabilities are obtained in terms of confluent hyper geometric series and modified Bessel’s function of first kind using Laplace transform, continued fractions and generating function methodologies. Numerical illustrations are added to depict the effect of variations in different parameter values on the time dependent probabilities.
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