[HTML][HTML] Darknet traffic classification and adversarial attacks using machine learning
N Rust-Nguyen, S Sharma, M Stamp - Computers & Security, 2023 - Elsevier
The anonymous nature of darknets is commonly exploited for illegal activities. Previous
research has employed machine learning and deep learning techniques to automate the …
research has employed machine learning and deep learning techniques to automate the …
Discop: Provably secure steganography in practice based on" distribution copies"
Steganography is the act of disguising the transmission of secret information as seemingly
innocent. Although provably secure steganography has been proposed for decades, it has …
innocent. Although provably secure steganography has been proposed for decades, it has …
Exposing the rat in the tunnel: Using traffic analysis for tor-based malware detection
Tor~\citetor is the most widely used anonymous communication network with millions of
daily users~\citetormetrics. Since Tor provides server and client anonymity, hundreds of …
daily users~\citetormetrics. Since Tor provides server and client anonymity, hundreds of …
Darknet Traffic Analysis: A Systematic Literature Review
J Saleem, R Islam, Z Islam - IEEE Access, 2024 - ieeexplore.ieee.org
The primary objective of an anonymity tool is to protect the anonymity of its users through the
implementation of strong encryption and obfuscation techniques. As a result, it becomes …
implementation of strong encryption and obfuscation techniques. As a result, it becomes …
Darknet traffic analysis, and classification system based on modified stacking ensemble learning algorithms
A Almomani - Information Systems and e-Business Management, 2023 - Springer
Darknet, a source of cyber intelligence, refers to the internet's unused address space, which
people do not expect to interact with their computers. The establishment of security requires …
people do not expect to interact with their computers. The establishment of security requires …
Towards a conceptual typology of darknet risks
O Ogbanufe, J Wolfe, F Baucum - Journal of Computer Information …, 2024 - Taylor & Francis
Increased rewards and reduced risks drive illicit networks. Cybercriminals seek to avoid
risks, including detection, arrests, sanctions, and violence. Hence, they employ several …
risks, including detection, arrests, sanctions, and violence. Hence, they employ several …
[HTML][HTML] Detection of obfuscated tor traffic based on bidirectional generative adversarial networks and vision transform
Y Sanjalawe, S Fraihat - Computers & Security, 2023 - Elsevier
Abstract The Onion Router (TOR) network is a decentralized system of volunteer-run servers
that aims to protect the anonymity and privacy of users by routing their internet traffic through …
that aims to protect the anonymity and privacy of users by routing their internet traffic through …
Enhanced detection of obfuscated HTTPS tunnel traffic using heterogeneous information network
M Liu, G Gou, G **ong, J Shi, Z Guan, H Miao, Y Li - Computer Networks, 2025 - Elsevier
HTTPS tunnel-based VPN services are increasingly used for malicious activities, such as
remote control and data exfiltration. As detection mechanisms improve, some adversaries …
remote control and data exfiltration. As detection mechanisms improve, some adversaries …
Darknet traffic classification and adversarial attacks
N Rust-Nguyen, M Stamp - arxiv preprint arxiv:2206.06371, 2022 - arxiv.org
The anonymous nature of darknets is commonly exploited for illegal activities. Previous
research has employed machine learning and deep learning techniques to automate the …
research has employed machine learning and deep learning techniques to automate the …
Network traffic classification based on single flow time series analysis
Network traffic monitoring using IP flows is used to handle the current challenge of analyzing
encrypted network communication. Nevertheless, the packet aggregation into flow records …
encrypted network communication. Nevertheless, the packet aggregation into flow records …