Machine learning for networking : Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers /: Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers. (2020)
- Record Type:
- Book
- Title:
- Machine learning for networking : Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers /: Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers. (2020)
- Main Title:
- Machine learning for networking : Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers
- Other Titles:
- MLN 2019
- Further Information:
- Note: Selma Boumerdassi, Éric Renault, Paul Mühlethaler (eds.).
- Editors:
- Boumerdassi, Selma
Renault, Eric
Mühlethaler, Paul - Other Names:
- International Conference on Machine Learning for Networking, 2nd
- Contents:
- 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,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 Network s -- 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. … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2020
- Copyright Date:
- 2020
- Extent:
- 1 online resource (xii, 486 pages), illustrations
- Subjects:
- 004.6
Machine learning -- Congresses
Computer networks -- Congresses - Languages:
- English
- ISBNs:
- 9783030457785
3030457788 - Related ISBNs:
- 9783030457778
- Notes:
- Note: Includes bibliographical references and author index.
Note: Description based on online resource (SpringerLink, viewed June 29, 2020). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.508535
- Ingest File:
- 03_085.xml