A survey of blockchain: Techniques, applications, and challenges

W Gao, WG Hatcher, W Yu - 2018 27th international conference …, 2018 - ieeexplore.ieee.org
Blockchain, as a mechanism to decentralize services, security, and verifiability, offers a peer-
to-peer system in which distributed nodes collaboratively affirm transaction provenance. In …

Didarknet: A contemporary approach to detect and characterize the darknet traffic using deep image learning

A Habibi Lashkari, G Kaur, A Rahali - Proceedings of the 2020 10th …, 2020 - dl.acm.org
Darknet traffic classification is significantly important to categorize real-time applications.
Although there are notable efforts to classify darknet traffic which rely heavily on existing …

Network flow watermarking: A survey

A Iacovazzi, Y Elovici - IEEE Communications Surveys & …, 2016 - ieeexplore.ieee.org
Traffic analysis (TA) is a useful tool aimed at understanding network traffic behavior. Basic
network administration often takes advantage of TA for purposes such as security, intrusion …

An automatic and efficient malware traffic classification method for secure Internet of Things

X Zhang, L Hao, G Gui, Y Wang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Malware traffic classification (MTC) plays an important role in cyber security and network
resource management for the secure Internet of Things (IoT). Many deep learning (DL) …

Torank: Identifying the most influential suspicious domains in the tor network

MW Al-Nabki, E Fidalgo, E Alegre… - Expert Systems with …, 2019 - Elsevier
The Tor network hosts a significant amount of hidden services related to suspicious
activities. Law Enforcement Agencies need to monitor and to investigate crimes hidden …

Exposing the rat in the tunnel: Using traffic analysis for tor-based malware detection

P Dodia, M AlSabah, O Alrawi, T Wang - Proceedings of the 2022 ACM …, 2022 - dl.acm.org
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 …

Machine learning approach for detection of nontor traffic

E Hodo, X Bellekens, E Iorkyase, A Hamilton… - Proceedings of the 12th …, 2017 - dl.acm.org
Intrusion detection has attracted a considerable interest from researchers and industries.
After many years of research the community still faces the problem of building reliable and …

Efficient fine-grained website fingerprinting via encrypted traffic analysis with deep learning

M Shen, Z Gao, L Zhu, K Xu - 2021 IEEE/ACM 29th …, 2021 - ieeexplore.ieee.org
Fine-grained website fingerprinting (WF) enables potential attackers to infer individual
webpages on a monitored website that victims are visiting, by analyzing the resulting traffic …

Black-box adversarial machine learning attack on network traffic classification

M Usama, A Qayyum, J Qadir… - 2019 15th International …, 2019 - ieeexplore.ieee.org
Deep machine learning techniques have shown promising results in network traffic
classification, however, the robustness of these techniques under adversarial threats is still …

Deep neural classification of darknet traffic

M Alimoradi, M Zabihimayvan, A Daliri… - Artificial intelligence …, 2022 - ebooks.iospress.nl
Darknet is an encrypted portion of the internet for users who intend to hide their identity.
Darknet's anonymous nature makes it an effective tool for illegal online activities such as …