A flexible SDN-based framework for slow-rate DDoS attack mitigation by using deep reinforcement learning

NM Yungaicela-Naula, C Vargas-Rosales… - Journal of network and …, 2022 - Elsevier
Abstract Distributed Denial-of-Service (DDoS) attacks are difficult to mitigate with existing
defense tools. Fortunately, it has been demonstrated that Software-Defined Networking …

Application of artificial intelligence to network forensics: Survey, challenges and future directions

S Rizvi, M Scanlon, J Mcgibney, J Sheppard - Ieee Access, 2022 - ieeexplore.ieee.org
Network forensics focuses on the identification and investigation of internal and external
network attacks, the reverse engineering of network protocols, and the uninstrumented …

Revisiting TLS-encrypted traffic fingerprinting methods for malware family classification

H Kim, M Kim, J Ha, H Roh - 2022 13th International …, 2022 - ieeexplore.ieee.org
Transport Layer Security (TLS) is a well-known end-to-end encryption protocol for secure
communication, and the use of TLS is continuously increasing, which influences that …

Fingerprinting the Shadows: Unmasking Malicious Servers with Machine Learning-Powered TLS Analysis

A Theofanous, E Papadogiannaki, A Shevtsov… - Proceedings of the …, 2024 - dl.acm.org
Over the last few years, the adoption of encryption in network traffic has been constantly
increasing. The percentage of encrypted communications worldwide is estimated to exceed …

FG-SAT: Efficient Flow Graph for Encrypted Traffic Classification under Environment Shifts

S Cui, X Han, D Han, Z Wang, W Wang, Y Li… - arXiv preprint arXiv …, 2024 - arxiv.org
Encrypted traffic classification plays a critical role in network security and management.
Currently, mining deep patterns from side-channel contents and plaintext fields through …

Using cyberscore for network traffic monitoring

L Deri, A Cardigliano - … on Cyber Security and Resilience (CSR …, 2022 - ieeexplore.ieee.org
The growing number of cybersecurity incidents and the always increasing complexity of
cybersecurity attacks is forcing the industry and the research community to develop robust …

MVDet: Encrypted malware traffic detection via multi-view analysis

S Cui, X Han, C Dong, Y Li, S Liu… - Journal of Computer …, 2024 - content.iospress.com
Detecting encrypted malware traffic promptly to halt the further propagation of an attack is
critical. Currently, machine learning becomes a key technique for extracting encrypted …

[PDF][PDF] A survey of methods for encrypted network traffic fingerprinting

S Yu, Y Won - Mathematical Biosciences and Engineering, 2023 - aimspress.com
Privacy protection in computer communication is gaining attention because plaintext
transmission without encryption can be eavesdropped on and intercepted. Accordingly, the …

[PDF][PDF] A Machine Learning-based Real-time Monitoring System for Classification of Elephant Flows on KOREN.

W Akbar, JJD Rivera, KT Ahmed, A Muhammad… - KSII Transactions on …, 2022 - itiis.org
With the advent and realization of Software Defined Network (SDN) architecture, many
organizations are now shifting towards this paradigm. SDN brings more control, higher …

Generic Encrypted Traffic Identification using Network Grammar: A Case Study in Passive OS Fingerprinting

L Rajala, K Scott - 2022 - diva-portal.org
The increase in cybercrime and cyber-warfare has spurred the cat-and-mouse game of
finding and attacking vulnerable devices on government or private company networks. The …