[HTML][HTML] Large language models meet next-generation networking technologies: A review
The evolution of network technologies has significantly transformed global communication,
information sharing, and connectivity. Traditional networks, relying on static configurations …
information sharing, and connectivity. Traditional networks, relying on static configurations …
Advanced deep learning models for 6G: overview, opportunities and challenges
The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …
heightened demand for advanced network intelligence to tackle the challenges of an …
TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic
B Lin, Y Guo, H Luo, M Ding - Future Generation Computer Systems, 2024 - Elsevier
Abstract Hybrid Software Defined Networks (Hybrid SDNs), with a partial upgrade of legacy
routers to SDN switches in traditional distributed networks, currently stand as a prevailing …
routers to SDN switches in traditional distributed networks, currently stand as a prevailing …
netFound: Foundation model for network security
S Guthula, R Beltiukov, N Battula, W Guo… - ar** generalizable ML-based solutions for disparate learning problems in network
security is highly desired. However, despite a rich history of applying ML to network security …
security is highly desired. However, despite a rich history of applying ML to network security …
On Sample Selection for Continual Learning: a Video Streaming Case Study
Machine learning (ML) is a powerful tool to model the complexity of communication
networks. As networks evolve, we cannot only train once and deploy. Retraining models …
networks. As networks evolve, we cannot only train once and deploy. Retraining models …
[HTML][HTML] LogPrécis: Unleashing language models for automated malicious log analysis: Précis: A concise summary of essential points, statements, or facts
Security logs are the key to understanding attacks and diagnosing vulnerabilities. Often
coming in the form of text logs, their analysis remains a daunting challenge. Language …
coming in the form of text logs, their analysis remains a daunting challenge. Language …
RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command Explainer
Malicious shell commands are linchpins to many cyber-attacks, but may not be easy to
understand by security analysts due to complicated and often disguised code structures …
understand by security analysts due to complicated and often disguised code structures …
[HTML][HTML] DeX: Deep learning-based throughput prediction for real-time communications with emphasis on traffic eXtremes
Recent years have witnessed a remarkable upsurge in the global proliferation of Real-Time
Communications (RTC) applications, a trend propelled by the flourishing advancement of …
Communications (RTC) applications, a trend propelled by the flourishing advancement of …
Similarity-Based Fast Analysis of Data Center Networks
Similarity-Based Fast Analysis of Data Center Networks Page 1 1 Similarity-Based Fast
Analysis of Data Center Networks Shruti Yadav Narayana1, Emily Shriver2, Kenneth O’Neal2 …
Analysis of Data Center Networks Shruti Yadav Narayana1, Emily Shriver2, Kenneth O’Neal2 …
SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing
Low Latency, Low Loss, and Scalable Throughput (L4S), as an emerging router-queue
management technique, has seen steady deployment in the industry. An L4S-enabled router …
management technique, has seen steady deployment in the industry. An L4S-enabled router …