Detection and classification of slow DoS attacks targeting network servers
Author:
Affiliation:
1. Consiglio Nazionale delle Ricerche (CNR), IEIIT institute, Genoa, Italy
Funder
Horizon 2020
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3407023.3409198
Reference38 articles.
1. Toward a V2I-based Solution for Traffic Lights Optimization
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1. Packet Filtering and Sampling for Efficient Slow Denial of Service Detection in Resource Scarce IoT Networks;2023 International Symposium on Networks, Computers and Communications (ISNCC);2023-10-23
2. Work-in-Progress: Slow Denial of Service Attack on MQTT-Based IoT;2023 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom);2023-07-04
3. A Novel Approach for distributed denial of service defense using continuous wavelet transform and convolutional neural network for software-Defined network;Computers & Security;2022-01
4. A Reliable Real-Time Slow DoS Detection Framework for Resource-Constrained IoT Networks;2021 IEEE Global Communications Conference (GLOBECOM);2021-12
5. Analysis and detection of application-independent slow Denial of Service cyber attacks;2021 IEEE International Conference on Intelligence and Security Informatics (ISI);2021-11-02
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