5g-nidd: A comprehensive network intrusion detection dataset generated over 5g wireless network

S Samarakoon, Y Siriwardhana, P Porambage… - arxiv preprint arxiv …, 2022 - arxiv.org
With a plethora of new connections, features, and services introduced, the 5th generation
(5G) wireless technology reflects the development of mobile communication networks and is …

Reliable detection of location spoofing and variation attacks

C Kim, SY Chang, D Lee, J Kim, K Park, J Kim - IEEE Access, 2023 - ieeexplore.ieee.org
Location spoofing is a critical attack in mobile communications. While several previous
studies investigated the detection of location spoofing attacks, they are limited in their …

[HTML][HTML] Fine-grained TLS services classification with reject option

J Luxemburk, T Čejka - Computer Networks, 2023 - Elsevier
The recent success and proliferation of machine learning and deep learning have provided
powerful tools, which are also utilized for encrypted traffic analysis, classification, and threat …

Benchmarking class incremental learning in deep learning traffic classification

G Bovenzi, A Nascita, L Yang… - … on Network and …, 2023 - ieeexplore.ieee.org
Traffic Classification (TC) is experiencing a renewed interest, fostered by the growing
popularity of Deep Learning (DL) approaches. In exchange for their proved effectiveness …

ProGraph: Robust network traffic identification with graph propagation

W Li, XY Zhang, H Bao, H Shi… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
Network traffic identification is critical for effective network management. Existing methods
mostly focus on invariant network environments with stable attribute distributions …

[HTML][HTML] Robust open-set classification for encrypted traffic fingerprinting

T Dahanayaka, Y Ginige, Y Huang, G Jourjon… - Computer Networks, 2023 - Elsevier
Encrypted network traffic has been known to leak information about their underlying content
through side-channel information leaks. Traffic fingerprinting attacks exploit this by using …

Encrypted traffic classification: the QUIC case

J Luxemburk, K Hynek, T Čejka - 2023 7th Network Traffic …, 2023 - ieeexplore.ieee.org
The QUIC protocol is a new reliable and secure transport protocol that is an alternative to
TLS over TCP. However, compared to TLS, QUIC obfuscates the connection hand-shake …

A lightweight, efficient and explainable-by-design convolutional neural network for internet traffic classification

K Fauvel, F Chen, D Rossi - Proceedings of the 29th ACM SIGKDD …, 2023 - dl.acm.org
Traffic classification, ie, the identification of the type of applications flowing in a network, is a
strategic task for numerous activities (eg, intrusion detection, routing). This task faces some …

[HTML][HTML] MEMENTO: A novel approach for class incremental learning of encrypted traffic

F Cerasuolo, A Nascita, G Bovenzi, G Aceto… - Computer Networks, 2024 - Elsevier
In the ever-changing digital environment, ensuring the ongoing effectiveness of traffic
analysis and security measures is crucial. Therefore, Class Incremental Learning (CIL) in …

Self-supervised traffic classification: Flow embedding and few-shot solutions

E Horowicz, T Shapira, Y Shavitt - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Internet traffic classification has been intensively studied over the past decade due to its
importance for traffic engineering and cyber security. A promising approach to several traffic …