Machine learning for networking = se...
International Conference on Machine Learning for Networking (2019 :)

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  • Machine learning for networking = second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019 : revised selected papers /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Machine learning for networking/ edited by Selma Boumerdassi, Eric Renault, Paul Muhlethaler.
    其他題名: second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019 : revised selected papers /
    其他題名: MLN 2019
    其他作者: Boumerdassi, Selma.
    團體作者: International Conference on Machine Learning for Networking
    出版者: Cham :Springer International Publishing : : 2020.,
    面頁冊數: xiii, 486 p. :ill., digital ;24 cm.
    內容註: Network Anomaly Detection using Federated Deep Autoencoding Gaussian Mixture Model -- Towards a Hierarchical Deep Learning Approach for Intrusion Detection -- Network Trafic Classifi cation using Machine Learning for Software Defined Networks -- A Comprehensive Analysis of Accuracies of Machine Learning Algorithms for Network Intrusion Detection -- Q-routing: from the algorithm to the routing protocol -- Language Model Co-occurrence Linking for Interleaved Activity Discovery -- Achieving Proportional Fairness in WiFi Networks via Bandit Convex Optimization -- Denoising Adversarial Autoencoder for Obfuscated Tra c Detection and Recovery -- Root Cause Analysis of Reduced Accessibility in 4G Networks -- Space-time pattern extraction in alarm logs for network diagnosis -- Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses -- Algorithm Selection and Model Evaluation in Application Design using Machine Learning -- GAMPAL: Anomaly Detection for Internet Backbone Tra c by Flow Prediction with LSTM-RNN -- Revealing User Behavior by Analyzing DNS Tra c -- A new approach to determine the optimal number of clusters based on the Gap statistic -- MLP4NIDS: an e cient MLP-based Network Intrusion Detection for CICIDS2017 dataset -- Random Forests with a Steepend Gini-Index Split Function and Feature Coherence Injection -- Emotion-based Adaptive Learning Systems -- Machine learning methods for anomaly detection in IoT networks, with illustrations -- DeepRoute: Herding Elephant and Mice Flows with Reinforcement Learning -- Arguments Against using the 1998 DARPA Dataset for Cloud IDS Design and Evaluation and Some Alternative -- Estimation of the Hidden Message Length in Steganography: A Deep Learning Approach -- An Adaptive Deep Learning Algorithm Based Autoencoder for Interference Channels -- A Learning Approach for Road Tra c Optimization in Urban Environments -- CSI based Indoor localization using Ensemble Neural Networks -- Bayesian Classi ers in Intrusion Detection Systems -- A Novel Approach towards Analysis of Attacker Behavior in DDoS Attacks -- Jason-RS, a Collaboration between Agents and an IoT Platform -- Scream to Survive(S2S): Intelligent System to Life-Saving in Disasters Relief -- Association Rules Algorithms for Data Mining Process Based on Multi Agent System -- Internet of Things: Security Between Challenges and Attacks -- Socially and biologically inspired computing for self-organizing communications networks.
    Contained By: Springer eBooks
    標題: Machine learning - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-030-45778-5
    ISBN: 9783030457785
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