Machine learning-powered encrypted network traffic analysis: A comprehensive survey

M Shen, K Ye, X Liu, L Zhu, J Kang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice

G Apruzzese, HS Anderson, S Dambra… - … IEEE Conference on …, 2023 - ieeexplore.ieee.org
Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …

Subverting website fingerprinting defenses with robust traffic representation

M Shen, K Ji, Z Gao, Q Li, L Zhu, K Xu - 32nd USENIX Security …, 2023 - usenix.org
Anonymity networks, eg, Tor, are vulnerable to various website fingerprinting (WF) attacks,
which allows attackers to perceive user privacy on these networks. However, the defenses …

A Systematic Survey On Security in Anonymity Networks: Vulnerabilities, Attacks, Defenses, and Formalization

D Chao, D Xu, F Gao, C Zhang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
The importance of safeguarding individuals' privacy rights in online activities is unmistakable
in today's anonymity networks. Since the introduction of Mixnet by Chaum, numerous …

Sok: A critical evaluation of efficient website fingerprinting defenses

N Mathews, JK Holland, SE Oh… - … IEEE Symposium on …, 2023 - ieeexplore.ieee.org
Recent website fingerprinting attacks have been shown to achieve very high performance
against traffic through Tor. These attacks allow an adversary to deduce the website a Tor …

Manda: On adversarial example detection for network intrusion detection system

N Wang, Y Chen, Y Xiao, Y Hu, W Lou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the rapid advancement in machine learning (ML), ML-based Intrusion Detection
Systems (IDSs) are widely deployed to protect networks from various attacks. One of the …

Black-box Adversarial Example Attack towards {FCG} Based Android Malware Detection under Incomplete Feature Information

H Li, Z Cheng, B Wu, L Yuan, C Gao, W Yuan… - 32nd USENIX Security …, 2023 - usenix.org
The function call graph (FCG) based Android malware detection methods have recently
attracted increasing attention due to their promising performance. However, these methods …

" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

Robust multi-tab website fingerprinting attacks in the wild

X Deng, Q Yin, Z Liu, X Zhao, Q Li… - … IEEE Symposium on …, 2023 - ieeexplore.ieee.org
Website fingerprinting enables an eavesdropper to determine which websites a user is
visiting over an encrypted connection. State-of-the-art website fingerprinting (WF) attacks …

Robust adversarial attacks against DNN-based wireless communication systems

A Bahramali, M Nasr, A Houmansadr… - Proceedings of the …, 2021 - dl.acm.org
There is significant enthusiasm for the employment of Deep Neural Networks (DNNs) for
important tasks in major wireless communication systems: channel estimation and decoding …