| 紀錄類型: |
書目-電子資源
: Monograph/item
|
| 正題名/作者: |
Machine learning for networking/ edited by Éric Renault, Selma Boumerdassi, Paul Mühlethaler. |
| 其他題名: |
6th International Conference, MLN 2023, Paris, France, November 28-30, 2023 : revised selected papers / |
| 其他作者: |
Renault, Éric. |
| 團體作者: |
International Conference on Machine Learning for Networking |
| 出版者: |
Cham :Springer Nature Switzerland : : 2024., |
| 面頁冊數: |
x, 286 p. :ill. (some col.), digital ;24 cm. |
| 內容註: |
Machine Learning for IoT Devices Security Reinforcement. -- All Attentive Deep Conditional Graph Generation for Wireless Network Topology Optimization. -- Enhancing Social Media Profile Authenticity Detection A Bio Inspired Algorithm Approach. -- Deep Learning Based Detection of Suspicious Activity in Outdoor Home Surveillance. -- Detecting Abnormal Authentication Delays in Identity and Access Management using Machine Learning. -- SIP DDoS SIP Framework for DDoS Intrusion Detection based on Recurrent Neural Networks. -- Deep Reinforcement Learning for multiobjective Scheduling in Industry 5.0 Reconfigurable Manufacturing Systems. -- Toward a digital twin IoT for the validation of AI algorithms in smart-city applications. -- Data Summarization for Federated Learning. -- ML Comparison Countermeasure prediction using radio internal metrics for BLE radio. -- Towards to Road Profiling with Cooperative Intelligent TransportSystems. -- Study of Masquerade Attack in VANETs with machine learning. -- Detecting Virtual Harassment in Social Media Using Machine Learning. -- Leverage data security policies complexity for users an end to end storage service management in the Cloud based on ABAC attributes. -- Machine Learning to Model the Risk of Alteration of historical buildings. -- A novel Image Encryption Technique using Modified Grain. -- Transformation Network Model for Ear Recognition. -- Cybersecurity analytics: Toward an efficient ML-based Network Intrusion Detection System (NIDS). |
| Contained By: |
Springer Nature eBook |
| 標題: |
Machine learning - Congresses. - |
| 電子資源: |
https://doi.org/10.1007/978-3-031-59933-0 |
| ISBN: |
9783031599330 |