A Hybrid Online Classifier System for Internet Traffic Based on Statistical Machine Learning Approach and Flow Port Number

Internet traffic classification is a beneficial technique in the direction of intrusion detection and network monitoring. After several years of searching, there are still many open problems in Internet traffic classification. The hybrid classifier combines more than one classification method to identify Internet traffic. Using only one method to classify Internet traffic poses many risks. In addition, an online classifier is very important in order to manage threats on traffic such as denial of service, flooding attack and other similar threats. Therefore, this paper provides some information to differentiate between real and live internet traffic. In addition, this paper proposes a hybrid online classifier (HOC) system. HOC is based on two common classification methods, port-base and ML-base. HOC is able to perform an online classification since it can identify live Internet traffic at the same time as it is generated. HOC was used to classify three common Internet application classes, namely web, WhatsApp and Twitter. HOC produces more than 90% accuracy, which is higher than any individual classifiers.

WCL: Client Selection in Federated Learning with a Combination of Model Weight Divergence and Client Training Loss for Internet Traffic Classification

Internet traffic classification (TC) is a critical technique in network management and is widely applied in various applications. In traditional TC problems, the edge devices need to send the raw traffic data to the server for centralized processing, which not only generates a lot of communication overhead but also leads to the privacy leakage and information security issues. Federated learning (FL) is a new distributed machine learning paradigm that allows multiple clients to train a global model collaboratively without raw traffic data sharing. The TC in a FL framework preserves the user privacy and data security by keeping the raw traffic data local. However, because of the different user behaviours and user preferences, traffic data heterogeneity emerges. The existing FL solutions introduce bias in model training by averaging the local model parameters from all heterogeneous clients, which degrades the classification accuracy of the learnt global classification model. To improve the classification accuracy in heterogeneous data environment, this paper proposes a novel client selection algorithm, namely, WCL, in federated paradigm based on a combination of model weight divergence and local model training loss. Extensive experiments on the public traffic dataset QUIC and ISCX have proved that the WCL algorithm obtains, compared to CMFL, superior performance in improving model accuracy and convergence speed on low heterogeneous traffic data and high heterogeneous traffic data, respectively.

Performance Evaluation of Routing Metrics for Community Wireless Mesh Networks

<p>With the growth of different types of Internet traffic there is a compelling need to provide better quality of service, especially, over the increasing number of wireless networks. Expected Transmission Count (ETX) is a high throughput route selection metric that measures link loss ratios. ETX of a path reflects the total number of packet transmissions (including retransmission) required to successfully deliver a data packet along that path. Expected Transmission Time (ETT) is an improvement of ETX. ETT of a path is a measure of the transmission time needed to successfully deliver a packet along the path. ETT measures the loss ratio and the bandwidth of the link. Both, ETX and ETT, in comparison to hop count, provide better route selection for routing protocols widely used in Wireless Mesh Networks (WMNs). Using minimum hop count to find the shortest path has been shown to be inadequate for WMNs, as the selected routes often include the weakest links. This thesis presents a performance evaluation comparing hop count, ETX and ETT when used with the Optimized Link State Routing version 2 (OLSRv2) protocol. This study is based on the wireless mesh topology of a suburban residential area in New Zealand, and analyses the performance of three common Internet traffic types in terms of throughput, end-to-end delay, jitter and packet loss ratio, and presents findings that are closer to the perspective of what an enduser experiences. Also, a grid network of 121 nodes was used to analyze how the metrics choose paths, the performance changes (for different path lengths) and other conditions that affect the performance of the three metrics.</p>

Performance Evaluation of Routing Metrics for Community Wireless Mesh Networks

<p>With the growth of different types of Internet traffic there is a compelling need to provide better quality of service, especially, over the increasing number of wireless networks. Expected Transmission Count (ETX) is a high throughput route selection metric that measures link loss ratios. ETX of a path reflects the total number of packet transmissions (including retransmission) required to successfully deliver a data packet along that path. Expected Transmission Time (ETT) is an improvement of ETX. ETT of a path is a measure of the transmission time needed to successfully deliver a packet along the path. ETT measures the loss ratio and the bandwidth of the link. Both, ETX and ETT, in comparison to hop count, provide better route selection for routing protocols widely used in Wireless Mesh Networks (WMNs). Using minimum hop count to find the shortest path has been shown to be inadequate for WMNs, as the selected routes often include the weakest links. This thesis presents a performance evaluation comparing hop count, ETX and ETT when used with the Optimized Link State Routing version 2 (OLSRv2) protocol. This study is based on the wireless mesh topology of a suburban residential area in New Zealand, and analyses the performance of three common Internet traffic types in terms of throughput, end-to-end delay, jitter and packet loss ratio, and presents findings that are closer to the perspective of what an enduser experiences. Also, a grid network of 121 nodes was used to analyze how the metrics choose paths, the performance changes (for different path lengths) and other conditions that affect the performance of the three metrics.</p>

ABOUT THE SECURİTY OF BRANCHCACHE TECHNOLOGY

Today, computers are mostly used online. In this regard, the loading of local networks and especially Internet traffic is observed. Optimization of local networks and especially Internet traffic is one of the most pressing issues of our time. The publication of this article is relevant because BranchCache technology is one of the tools for optimizing network traffic.

Futuristic Cyber-Twin Architecture for 6G Technology to Support Internet of Everything

With the rapid growth of Internet of Everything, there is a huge rise in the transportable Internet traffic due to which its associated resources have exceptional obstacles which include reliability, security, expandability, security, and portability which the current available network architectures are unable to deal with. In this paper, an IoT centric cyber-physical twin architecture has been proposed for 6G Technology. The cyber-twin technology helps out in serving stronger communication and also contains several features that help out in assisting communication like maintaining a log record of network data and managing all digital assets like images, audio, video, and so forth. These features of the cyber-twin technology enable the proposed network to deal with those exceptional obstacles and make the system more reliable, safe, workable, and adaptable.