Results 31 to 40 of about 4,077 (204)

Encrypting network traffic [PDF]

, 1994
There are several possible explanations. Many people are unaware of the potential benefits of encrypting messages before transmission. Alternatively they may not be aware how insecure their computers are; for example most of the computers in use within the Computer Laboratory here in Cambridge transmit user's passwords unen.crypted so that they may be ...
openaire   +1 more source

Feature analysis of encrypted malicious traffic

Expert Systems with Applications, 2019
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation or communication. Antivirus software and firewalls typically will not have access to encryption keys, and therefore direct detection of malicious encrypted data is unlikely to succeed. However, previous work has shown
Shekhawat, Anish Singh, Di Troia, Fabio, Stamp, Mark   +2 more
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Transport Layer Security-Encrypted Abnormal Traffic Detection Based on Supervised Autoencoder [PDF]

Jisuanji gongcheng
As user awareness of privacy protection increases, an increasing number of websites and services are employing the Transport Layer Security (TLS) protocol to safeguard user data.
YANG Mingfen, GAN Yun, ZHANG Xingpeng
doaj   +1 more source

A framework for digital forensics of encrypted real-time network traffic, instant messaging, and VoIP application case study

Ain Shams Engineering Journal, 2023
Digital forensics is one of the prime professional fields for law enforcement forces. It is also a major active research topic in the cybersecurity field. Internet traffic and content analysis are leading tasks within this research area.
Soliman Abd Elmonsef Sarhan, Hassan A. Youness, Ayman M. Bahaa-Eldin   +2 more
doaj   +1 more source

Review and perspective on encrypted traffic identification research

Tongxin xuebao, 2016
Considering the importance of encrypted traffic identification technology and existing research work,first,the type of encrypted traffic identification according to the demand of traffic analysis were introduced,such as protocols,applications and ...
Wu-bin PAN, Guang CHENG, Xiao-jun GUO, Shun-xiang HUANG   +3 more
doaj   +2 more sources

VoIP Traffic Detection in Tunneled and Anonymous Networks Using Deep Learning

IEEE Access, 2021
Network management is facing a great challenge to analyze and identify encrypted network traffic with specific applications and protocols. A significant number of network users applying different encryption techniques to network applications and services
Faiz Ul Islam, Guangjie Liu, Jiangtao Zhai, Weiwei Liu   +3 more
doaj   +1 more source

Multi-feature fusion based encrypted malicious traffic detection method for coal mine network

Gong-kuang zidonghua, 2022
The coal mine network is faced with the threat of malicious traffic encrypted by the transport layer security protocol (TLS) generated by malicious software and the high false alarm rate of encrypted traffic during detection.
HUO Yuehua, ZHAO Faqi, WU Wenhao
doaj   +1 more source

MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification

Proceedings of the AAAI Conference on Artificial Intelligence
Network traffic includes data transmitted across a network, such as web browsing and file transfers, and is organized into packets (small units of data) and flows (sequences of packets exchanged between two endpoints). Classifying encrypted traffic is essential for detecting security threats and optimizing network management.
Chen, Xu-Yang, Han, Lu, Zhan, De-Chuan, Ye, Han-Jia   +3 more
openaire   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Encrypted Traffic Classification Model Based on Byte Coding and Pre-Training Tasks [PDF]

Jisuanji gongcheng
This study proposes a pre-training model that integrates byte-level encoding and improved pre-training tasks for encrypted traffic classification. The aim is to address the lack of coding methods and corresponding pre-training tasks in designing the ...
YAO Lifeng, CAI Manchun, ZHU Yi, CHEN Yonghao, ZHANG Yiwen
doaj   +1 more source