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Machine learning for wireless link quality estimation: A survey
Since the emergence of wireless communication networks, a plethora of research papers
focus their attention on the quality aspects of wireless links. The analysis of the rich body of …
focus their attention on the quality aspects of wireless links. The analysis of the rich body of …
Survey of protocol reverse engineering algorithms: Decomposition of tools for static traffic analysis
Knowledge about a network protocol to understand the communication between entities is
necessary for vulnerability research, penetration testing, malware analysis, network …
necessary for vulnerability research, penetration testing, malware analysis, network …
Detecting android malware leveraging text semantics of network flows
The emergence of malicious apps poses a serious threat to the Android platform. Most types
of mobile malware rely on network interface to coordinate operations, steal users' private …
of mobile malware rely on network interface to coordinate operations, steal users' private …
Byte segment neural network for network traffic classification
Network traffic classification, which can map network traffic to protocols in the application
layer, is a fundamental technique for network management and security issues such as …
layer, is a fundamental technique for network management and security issues such as …
EBSNN: Extended byte segment neural network for network traffic classification
Network traffic classification is important to intrusion detection and network management.
Most of existing methods are based on machine learning techniques and rely on the …
Most of existing methods are based on machine learning techniques and rely on the …
TCGNN: Packet-grained network traffic classification via Graph Neural Networks
Network traffic classification is the fundamental and vital function for network management,
network security and so on. With the traffic scenarios becoming more and more complex …
network security and so on. With the traffic scenarios becoming more and more complex …
Encrypted TLS traffic classification on cloud platforms
X Yun, Y Wang, Y Zhang, C Zhao… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
Nowadays, encryption technology has been widely used to protect user privacy. With the
explosive growth of mobile Internet, encrypted TLS traffic rises sharply and occupies a great …
explosive growth of mobile Internet, encrypted TLS traffic rises sharply and occupies a great …
Khaos: An adversarial neural network DGA with high anti-detection ability
X Yun, J Huang, Y Wang, T Zang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
A botnet is a network of remote-controlled devices that are infected with malware controlled
by botmasters in order to launch cyber attacks. To evade detection, the botmaster frequently …
by botmasters in order to launch cyber attacks. To evade detection, the botmaster frequently …
A multi-scale feature attention approach to network traffic classification and its model explanation
Y Wang, X Yun, Y Zhang, C Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network traffic classification, the task of associating network traffic with their generating
application protocols or applications, is valuable for the control, allocation, and management …
application protocols or applications, is valuable for the control, allocation, and management …
$ Bitcoding $: Network traffic classification through encoded bit level signatures
With many network protocols using obfuscation techniques to hide their identity, robust
methods of traffic classification are required. In traditional deep-packet-inspection (DPI) …
methods of traffic classification are required. In traditional deep-packet-inspection (DPI) …