Adversarial robustness of deep neural networks: A survey from a formal verification perspective

MH Meng, G Bai, SG Teo, Z Hou, Y Xiao… - … on Dependable and …, 2022 - ieeexplore.ieee.org
Neural networks have been widely applied in security applications such as spam and
phishing detection, intrusion prevention, and malware detection. This black-box method …

[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 …

Evaluation of synthetic data generation techniques in the domain of anonymous traffic classification

D Cullen, J Halladay, N Briner, R Basnet… - IEEE …, 2022 - ieeexplore.ieee.org
Anonymous network traffic is more pervasive than ever due to the accessibility of services
such as virtual private networks (VPN) and The Onion Router (Tor). To address the need to …

Toward identifying malicious encrypted traffic with a causality detection system

ZR Zeng, P Xun, W Peng, BK Zhao - Journal of Information Security and …, 2024 - Elsevier
The main methods for protecting user privacy and addressing cybersecurity problems
caused by encrypted traffic are non-decryption detection approaches. However, these …

Integrating Blockchain and Deep Learning for Enhanced Mobile VPN Forensics: A Comprehensive Framework

SS Alqahtany, TA Syed - Applied Sciences, 2024 - mdpi.com
In an era marked by technological advancement, the rising reliance on Virtual Private
Networks (VPNs) necessitates sophisticated forensic analysis techniques to investigate VPN …

Bidirectional statistical feature extraction based on time window for tor flow classification

H Yan, L He, X Song, W Yao, C Li, Q Zhou - Symmetry, 2022 - mdpi.com
The anonymous system Tor uses an asymmetric algorithm to protect the content of
communications, allowing criminals to conceal their identities and hide their tracks. This …

Encrypted network traffic classification with higher order graph neural network

Z Okonkwo, E Foo, Z Hou, Q Li, Z Jadidi - Australasian Conference on …, 2023 - Springer
Encryption protects internet users' data security and privacy but makes network traffic
classification a much harder problem. Network traffic classification is essential for identifying …

[PDF][PDF] 基于代价敏感卷积神经网络的加密流量分类

钟海龙, 何月顺, 何璘琳, 陈杰, 田鸣, 郑瑞银 - 计算机与现代化, 2024 - cam.org.cn
针对加密流量分类中由于不平衡数据导致的分类偏差和少数类识别率低的问题,
提出一种基于代价敏感卷积神经网络的加密流量分类方法. 鉴于传统卷积神经网络在处理不平衡 …

Security, Privacy and Trust for the Metaverse of Things

S Pal, A Vangala, Z Jadidi, Z Hou… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
In this paper, we present the need for security, privacy, and trust in the 'Metaverse of Things'.
We envision the context 'Metaverse of Things', where everything and anything within the …

CLASSIFYING OVER-THE-TOP NETWORK TRAFFIC USING DEEP LEARNING ALGORITHMS WITH DESIGN SCIENCE RESEARCH METHODOLOGY …

FIA Faisal, A Lawi… - Jurnal Teknologi Informasi …, 2024 - jtika.if.unram.ac.id
Classifying network traffic is the foundational step in analyzing diverse applications reliant
on network infrastructure, particularly focusing on identifying Over-The-Top (OTT) …