17 citations · 24 across the 14 of their papers we have counts for
15 papers
An Internet for the KV Cache: Rethinking Classical Infrastructure Boundaries in the LLM Inference Age
Siddhant Ray, Nick Feamster, Junchen Jiang
LLM inference has become a global-scale, heterogeneous workload spanning agents, retrieval, tool-use, code execution and multi-modal reasoning. These workloads naturally enable con…
Quantifying the Privacy Implications of High-Fidelity Synthetic Network Traffic
Van Tran, Shinan Liu, Tian Li +1
To address the scarcity and privacy concerns of network traffic data, various generative models have been developed to produce synthetic traffic. However, synthetic traffic is not…
Characterizing the Impact of Active Queue Management on Speed Test Measurements
Siddhant Ray, Taveesh Sharma, Jonatas Marques +3
Present day speed test tools measure peak throughput, but often fail to capture the user-perceived responsiveness of a network connection under load. Recently, platforms such as ND…
WiFinger: Fingerprinting Noisy IoT Event Traffic Using Packet-level Sequence Matching
Ronghua Li, Shinan Liu, Haibo Hu +2
IoT environments such as smart homes are susceptible to privacy inference attacks, where attackers can analyze patterns of encrypted network traffic to infer the state of devices a…
NetSSM: Multi-Flow and State-Aware Network Trace Generation using State Space Models
Andrew Chu, Xi Jiang, Shinan Liu +4
Access to raw network traffic data is essential for many computer networking tasks, from traffic modeling to performance evaluation. Unfortunately, this data is scarce due to high…
Algorithmic Data Minimization for Machine Learning over Internet-of-Things Data Streams
Ted Shaowang, Shinan Liu, Jonatas Marques +2
Machine learning can analyze vast amounts of data generated by IoT devices to identify patterns, make predictions, and enable real-time decision-making. By processing sensor data,…
Generative Active Adaptation for Drifting and Imbalanced Network Intrusion Detection
Ragini Gupta, Shinan Liu, Ruixiao Zhang +7
Machine learning has shown promise in network intrusion detection systems, yet its performance often degrades due to concept drift and imbalanced data. These challenges are compoun…
Towards On-Device Evidence Gathering for Intimate Partner Infiltration: A Feasibility Study for Joint Identity-Action Detection
Weisi Yang, Shinan Liu, Feng Xiao +2
Intimate Partner Infiltration (IPI) refers to phone-side privacy infiltration in intimate or close relationships, often enabled by physical access to a person's smartphone and disc…
CAIP: Detecting Router Misconfigurations with Context-Aware Iterative Prompting of LLMs
Xi Jiang, Aaron Gember-Jacobson, Nick Feamster
Model checkers and consistency checkers detect critical errors in router configurations, but these tools require significant manual effort to develop and maintain. LLM-based Q&A mo…
SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing
Siddhant Ray, Xi Jiang, Jack Luo +2
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 assigns ea…
Feasibility of State Space Models for Network Traffic Generation
Andrew Chu, Xi Jiang, Shinan Liu +4
Many problems in computer networking rely on parsing collections of network traces (e.g., traffic prioritization, intrusion detection). Unfortunately, the availability and utility…
Beyond Data Points: Regionalizing Crowdsourced Latency Measurements
Taveesh Sharma, Paul Schmitt, Francesco Bronzino +2
Despite significant investments in access network infrastructure, universal access to high-quality Internet connectivity remains a challenge. Policymakers often rely on large-scale…
CATO: End-to-End Optimization of ML-Based Traffic Analysis Pipelines
Gerry Wan, Shinan Liu, Francesco Bronzino +2
Machine learning has shown tremendous potential for improving the capabilities of network traffic analysis applications, often outperforming simpler rule-based heuristics. However,…
FlowWise: Stateful Fast-Slow Model Serving for Streaming Traffic Intelligence
Shinan Liu, Ted Shaowang, Gerry Wan +4
Network traffic analysis in cloud and internet service provider (ISP) networks increasingly relies on machine learning (ML) models, as encryption and service consolidation make rul…
VidPlat: A Tool for Fast Crowdsourcing of Quality-of-Experience Measurements
Xu Zhang, Hanchen Li, Paul Schmitt +3
For video or web services, it is crucial to measure user-perceived quality of experience (QoE) at scale under various video quality or page loading delays. However, fast QoE measur…