De-anonymisation attacks on tor: A survey
Anonymity networks are becoming increasingly popular in today's online world as more
users attempt to safeguard their online privacy. Tor is currently the most popular anonymity …
users attempt to safeguard their online privacy. Tor is currently the most popular anonymity …
Realtime robust malicious traffic detection via frequency domain analysis
Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …
particularly for zero-day attack detection, which is complementary to existing rule based …
Defeating {DNN-Based} traffic analysis systems in {Real-Time} with blind adversarial perturbations
Deep neural networks (DNNs) are commonly used for various traffic analysis problems, such
as website fingerprinting and flow correlation, as they outperform traditional (eg, statistical) …
as website fingerprinting and flow correlation, as they outperform traditional (eg, statistical) …
[PDF][PDF] FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications.
An emerging trend in network security consists in the adoption of programmable switches for
performing various security tasks in large-scale, high-speed networks. However, since …
performing various security tasks in large-scale, high-speed networks. However, since …
Deepcorr: Strong flow correlation attacks on tor using deep learning
Flow correlation is the core technique used in a multitude of deanonymization attacks on
Tor. Despite the importance of flow correlation attacks on Tor, existing flow correlation …
Tor. Despite the importance of flow correlation attacks on Tor, existing flow correlation …
A long way to the top: Significance, structure, and stability of internet top lists
A broad range of research areas including Internet measurement, privacy, and network
security rely on lists of target domains to be analysed; researchers make use of target lists …
security rely on lists of target domains to be analysed; researchers make use of target lists …
Encrypted DNS--> privacy? A traffic analysis perspective
Virtually every connection to an Internet service is preceded by a DNS lookup which is
performed without any traffic-level protection, thus enabling manipulation, redirection …
performed without any traffic-level protection, thus enabling manipulation, redirection …
Optimizing feature selection for efficient encrypted traffic classification: A systematic approach
Traffic classification is a technology for classifying and identifying sensitive information from
cluttered traffic. With the increasing use of encryption and other evasion technologies …
cluttered traffic. With the increasing use of encryption and other evasion technologies …
DeepCoFFEA: Improved flow correlation attacks on Tor via metric learning and amplification
SE Oh, T Yang, N Mathews, JK Holland… - … IEEE Symposium on …, 2022 - ieeexplore.ieee.org
End-to-end flow correlation attacks are among the oldest known attacks on low-latency
anonymity networks, and are treated as a core primitive for traffic analysis of Tor. However …
anonymity networks, and are treated as a core primitive for traffic analysis of Tor. However …
Frequency domain feature based robust malicious traffic detection
Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …
particularly for zero-day attack detection, which is complementary to existing rule based …