VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world.However,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and c...VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world.However,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork data.We present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service assaults.We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns.Next,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous actions.To effectively process and categorize encrypted packets,the neural network model has input,hidden,and output layers.We use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral properties.We also use cutting-edge optimizationmethods to optimize network characteristics and performance.The suggested ANN-based categorization method is extensively tested and analyzed.Results show the model effectively classifies VPN traffic types.We also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%accuracy.This study improves VPN security and protects against new cyberthreats.Classifying VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security problems.This study advances network security and lays the groundwork for ANN-based cybersecurity solutions.展开更多
The technology of Covert Channel is often used for communications between computers and the Internet with high sensitivity or security levels.Presently,some research were carried out on covert channel using computer s...The technology of Covert Channel is often used for communications between computers and the Internet with high sensitivity or security levels.Presently,some research were carried out on covert channel using computer screen light radiation,speakers,electromagnetic leakage,etc.In this paper,the technology of SoundHammer is studied.It is a technical bridgeware that use acoustic waves to transmit data from sound device into an air-gapped network.Firstly,an idea was proposed for data transmission by covert channel through acoustic waves.Then,this method was validated by experiment and the risks of the air-gapped network were confirmed.Finally,some countermeasures for detecting and eliminating such covert channels were listed.展开更多
文摘VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world.However,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork data.We present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service assaults.We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns.Next,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous actions.To effectively process and categorize encrypted packets,the neural network model has input,hidden,and output layers.We use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral properties.We also use cutting-edge optimizationmethods to optimize network characteristics and performance.The suggested ANN-based categorization method is extensively tested and analyzed.Results show the model effectively classifies VPN traffic types.We also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%accuracy.This study improves VPN security and protects against new cyberthreats.Classifying VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security problems.This study advances network security and lays the groundwork for ANN-based cybersecurity solutions.
基金through grants from the National Natural Science Foundation of China(No.61602491)the University fund of National University of Defense Technology(No.KY19A013)We also would like to thank the Institute of Psychology,Chinese Academy of Sciences for generously supporting our research.
文摘The technology of Covert Channel is often used for communications between computers and the Internet with high sensitivity or security levels.Presently,some research were carried out on covert channel using computer screen light radiation,speakers,electromagnetic leakage,etc.In this paper,the technology of SoundHammer is studied.It is a technical bridgeware that use acoustic waves to transmit data from sound device into an air-gapped network.Firstly,an idea was proposed for data transmission by covert channel through acoustic waves.Then,this method was validated by experiment and the risks of the air-gapped network were confirmed.Finally,some countermeasures for detecting and eliminating such covert channels were listed.
