Machine Learning for Networking
Springer International Publishing (Verlag)
978-3-030-45777-8 (ISBN)
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 forInternet 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 ersin 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.
Erscheinungsdatum | 23.04.2020 |
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Reihe/Serie | Information Systems and Applications, incl. Internet/Web, and HCI | Lecture Notes in Computer Science |
Zusatzinfo | XIII, 486 p. 267 illus., 183 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 759 g |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | Applications • Artificial Intelligence • Communication Systems • computer crime • Computer Networks • Computer Science • Computer Security • Computer systems • conference proceedings • cryptography • Data Security • Education • Engineering • Informatics • Internet • learning • machine learning • Network Protocols • Research • Signal Processing • Telecommunication networks • Telecommunication Systems • telecommunication traffic • wireless telecommunication systems |
ISBN-10 | 3-030-45777-X / 303045777X |
ISBN-13 | 978-3-030-45777-8 / 9783030457778 |
Zustand | Neuware |
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