Complex application identification and private network mining algorithm based on traffic-aware model in large-scale networks

Tian, Rongyu; Zhu, Haiguang

doi:10.1007/s12083-019-00803-6

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…Mario et al [13] propose an enhanced detection method of encrypted Skype traffic by using an ad-hoc developed enhanced probe (ESkyPRO) which correlate the information received by ESkyPRO and other types of data obtained by an Intrusion Detection System (IDS) probe. Tian et al [14] put forwards to the effective behavior model, which can effectively identify complex applications. Huang et al [15] chooses Skype as the analysis object and propose the complex private network mining technology, which can solve many difficulties and challenges of CA identification.…”

Section: Related Workmentioning

confidence: 99%

Online Encrypted Skype Identification Based on an Updating Mechanism

Dong¹

2022

Preprint

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The machine learning algorithm is gaining prominence in traffic identification research as it offers a way to overcome the shortcomings of port-based and deep packet inspection, especially for P2Pbased Skype. However,recent studies have focused mainly on traffic identification based on a fullpacket dataset, which poses great challenges to identifying online network traffic. This study aims to provide a new flow identification algorithm by taking the sampled flow records as the object. The study constructs flow records from a Skype set as the dataset, considers the inherent NETFLOW and extended flow metrics as features, and uses a fast correlation-based filter algorithm to select highly correlated features. The study also proposes a new NFI method that adopts a Bayesian updating mechanism to improve the classifier model. The experimental results show that the proposed scheme can achieve much better identification performance than existing state-of-the-art traffic identification methods, and a typical feature metric is analyzed in the sampling environment. The NFI method improves identification accuracy and reduces false positives and false negatives compared to other methods.

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Section: Related Workmentioning

confidence: 99%

Online Encrypted Skype Identification Based on an Updating Mechanism

Dong¹

2022

Preprint

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Computer generated hologram-based image cryptosystem with multiple chaotic systems

et al. 2020

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Open VPN Application Under Campus Network

Zhou

Huang

2021

J. Phys.: Conf. Ser.

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For security and intellectual copyright considerations, colleges and universities generally have the same problem: non-campus residents cannot access many resources on the campus network. OpenVPN is an open source based on the SSL protocol, combined with the actual needs of campus network applications, it describes in detail how to use the open source OpenVPN technology on the LINUX operating platform to build a user access system. Users can quickly access campus resources by establishing a connection with the OpenVPN server through the client program. Without additional investment, the confidentiality of data is ensured. It allows users to break through the limitations of time and space, which not only facilitates users, but also improves the utilization rate of campus network information resources.

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Complex application identification and private network mining algorithm based on traffic-aware model in large-scale networks

Cited by 4 publications

References 18 publications

Online Encrypted Skype Identification Based on an Updating Mechanism

Online Encrypted Skype Identification Based on an Updating Mechanism

Computer generated hologram-based image cryptosystem with multiple chaotic systems

Open VPN Application Under Campus Network

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