Machine learning for encrypted malicious traffic detection: Approaches, datasets and comparative study

Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey

(2021) Mahmoud Abbasi et al.   COMPUTER COMMUNICATIONS

XAI Meets Mobile Traffic Classification: Understanding and Improving Multimodal Deep Learning Architectures

(2021) Alfredo Nascita et al.   IEEE Transactions on Network and Service Management

Improved KNN Algorithm for Fine-Grained Classification of Encrypted Network Flow

(2020) Chencheng Ma et al.   Electronics

Toward Effective Mobile Encrypted Traffic Classification through Deep Learning

(2020) Giuseppe Aceto et al.   NEUROCOMPUTING

THS-IDPC: A three-stage hierarchical sampling method based on improved density peaks clustering algorithm for encrypted malicious traffic detection

(2020) Liangchen Chen et al.   JOURNAL OF SUPERCOMPUTING

Building an Effective Intrusion Detection System Using the Modified Density Peak Clustering Algorithm and Deep Belief Networks

(2019) Yanqing Yang et al.   Applied Sciences-Basel

Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-IoT dataset

(2019) Nickolaos Koroniotis et al.   Future Generation Computer Systems-The International Journal of eScience

Deep packet: a novel approach for encrypted traffic classification using deep learning

(2019) Mohammad Lotfollahi et al.   SOFT COMPUTING

Feature analysis of encrypted malicious traffic

(2019) Anish Singh Shekhawat et al.   EXPERT SYSTEMS WITH APPLICATIONS

Mobile Encrypted Traffic Classification Using Deep Learning: Experimental Evaluation, Lessons Learned, and Challenges

(2019) Giuseppe Aceto et al.   IEEE Transactions on Network and Service Management

TR-IDS: Anomaly-Based Intrusion Detection through Text-Convolutional Neural Network and Random Forest

(2018) Erxue Min et al.   Security and Communication Networks

Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

(2017) Yang Yu et al.   Security and Communication Networks

A survey of methods for encrypted traffic classification and analysis

(2015) Petr Velan et al.   International Journal of Network Management

An empirical comparison of botnet detection methods

(2014) S. García et al.   COMPUTERS & SECURITY

A multilevel taxonomy and requirements for an optimal traffic-classification model

(2014) Jawad Khalife et al.   International Journal of Network Management

Toward developing a systematic approach to generate benchmark datasets for intrusion detection

(2012) Ali Shiravi et al.   COMPUTERS & SECURITY

GT

(2009) F. Gringoli et al.   ACM SIGCOMM Computer Communication Review

Improving network anomaly detection via selective flow-based sampling

(2008) G. Androulidakis et al.   IET Communications