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相关论文: Malware Traffic Classification: Evaluation of Algo…

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The constant growth in the number of malware - software or code fragment potentially harmful for computers and information networks - and the use of sophisticated evasion and obfuscation techniques have seriously hindered classic…

密码学与安全 · 计算机科学 2021-06-11 Nicola Loi , Claudio Borile , Daniele Ucci

Modern networks carry increasingly diverse and encrypted traffic types that demand classification techniques beyond traditional port-based and payload-based methods. This tutorial provides a practical, end-to-end guide to building…

网络与互联网体系结构 · 计算机科学 2026-01-08 Adrian Pekar , Richard Plny , Karel Hynek

Research and development of techniques which detect or remediate malicious network activity require access to diverse, realistic, contemporary data sets containing labeled malicious connections. In the absence of such data, said techniques…

As people's demand for personal privacy and data security becomes a priority, encrypted traffic has become mainstream in the cyber world. However, traffic encryption is also shielding malicious and illegal traffic introduced by adversaries,…

密码学与安全 · 计算机科学 2022-11-21 Zihao Wang , Kar-Wai Fok , Vrizlynn L. L. Thing

Malicious software (malware) poses an increasing threat to the security of communication systems as the number of interconnected mobile devices increases exponentially. While some existing malware detection and classification approaches…

机器学习 · 计算机科学 2021-06-07 Julian Busch , Anton Kocheturov , Volker Tresp , Thomas Seidl

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,…

密码学与安全 · 计算机科学 2023-12-11 Anish Singh Shekhawat , Fabio Di Troia , Mark Stamp

Encrypted tunneling protocols are widely used. Beyond business and personal uses, malicious actors also deploy tunneling to hinder the detection of Command and Control and data exfiltration. A common approach to maintain visibility on…

密码学与安全 · 计算机科学 2022-01-26 Johan Mazel , Matthieu Saudrais , Antoine Hervieu

Classifying network traffic is the basis for important network applications. Prior research in this area has faced challenges on the availability of representative datasets, and many of the results cannot be readily reproduced. Such a…

密码学与安全 · 计算机科学 2020-04-29 Onur Barut , Yan Luo , Tong Zhang , Weigang Li , Peilong Li

Malware abuses TLS to encrypt its malicious traffic, preventing examination by content signatures and deep packet inspection. Network detection of malicious TLS flows is an important, but challenging, problem. Prior works have proposed…

密码学与安全 · 计算机科学 2022-12-26 Gibran Gomez , Platon Kotzias , Matteo Dell'Amico , Leyla Bilge , Juan Caballero

Traffic classification, a technique for assigning network flows to predefined categories, has been widely deployed in enterprise and carrier networks. With the massive adoption of mobile devices, encryption is increasingly used in mobile…

网络与互联网体系结构 · 计算机科学 2025-09-03 Kun Qiu , Ying Wang , Baoqian Li , Wenjun Zhu

The popularity of encryption mechanisms poses a great challenge to malicious traffic detection. The reason is traditional detection techniques cannot work without the decryption of encrypted traffic. Currently, research on encrypted…

密码学与安全 · 计算机科学 2023-04-10 Zihao Wang , Vrizlynn L. L. Thing

Malware classification is a difficult problem, to which machine learning methods have been applied for decades. Yet progress has often been slow, in part due to a number of unique difficulties with the task that occur through all stages of…

密码学与安全 · 计算机科学 2020-11-17 Edward Raff , Charles Nicholas

Malwares are the key means leveraged by threat actors in the cyber space for their attacks. There is a large array of commercial solutions in the market and significant scientific research to tackle the challenge of the detection and…

密码学与安全 · 计算机科学 2022-11-21 Kar Wai Fok , Vrizlynn L. L. Thing

Machine learning is rapidly becoming one of the most important technology for malware traffic detection, since the continuous evolution of malware requires a constant adaptation and the ability to generalize. However, network traffic…

机器学习 · 计算机科学 2020-09-25 Ivan Letteri , Antonio Di Cecco , Giuseppe Della Penna

With the increasing prevalence of encrypted network traffic, cyber security analysts have been turning to machine learning (ML) techniques to elucidate the traffic on their networks. However, ML models can become stale as new traffic…

With the growing significance of network security, the classification of encrypted traffic has emerged as an urgent challenge. Traditional byte-based traffic analysis methods are constrained by the rigid granularity of information and fail…

密码学与安全 · 计算机科学 2025-01-08 Haozhen Zhang , Haodong Yue , Xi Xiao , Le Yu , Qing Li , Zhen Ling , Ye Zhang

Machine learning (ML) is promising in accurately detecting malicious flows in encrypted network traffic; however, it is challenging to collect a training dataset that contains a sufficient amount of encrypted malicious data with correct…

密码学与安全 · 计算机科学 2023-09-12 Yuqi Qing , Qilei Yin , Xinhao Deng , Yihao Chen , Zhuotao Liu , Kun Sun , Ke Xu , Jia Zhang , Qi Li

Malware attacks have become significantly more frequent and sophisticated in recent years. Therefore, malware detection and classification are critical components of information security. Due to the large amount of malware samples…

密码学与安全 · 计算机科学 2024-05-07 Olha Jurečková , Martin Jureček , Mark Stamp

Internet traffic classification has become more important with rapid growth of current Internet network and online applications. There have been numerous studies on this topic which have led to many different approaches. Most of these…

In contrast to previous surveys, the present work is not focused on reviewing the datasets used in the network security field. The fact is that many of the available public labeled datasets represent the network behavior just for a…

密码学与安全 · 计算机科学 2022-01-03 Jorge Guerra , Carlos Catania , Eduardo Veas
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