1 citations · 1 across the 10 of their papers we have counts for
10 papers
BGPay: An Incentive-Compatible Mechanism for BGP Hijack Filtering
Tomasz Sadowy, Constantine Doumanidis, Maria Apostolaki
BGP hijacking remains a persistent threat as existing defenses, including RPKI/ROV suffer from a fundamental incentive misalignment: the networks best positioned to filter maliciou…
The Frontier LLM Trap in Network Automation
Minhao Jin, Sean Wang, Aarti Gupta +1
Large LLMs are powerful tools for network automation, but they are expensive, slow to serve, hard to audit, poorly tailored to individual networks, and create long-term dependencie…
Let AI Agents Translate Networks, Not Reason About Them
Hongyu Hè, Maria Apostolaki
A formal model enables verifying reachability, localizing an outage, or anticipating the blast radius of a change. Yet, virtually no production network has one, since writing a mod…
Invariant Discovery for Networked Systems
Hongyu Hè, Alexander Krentsel, Sylvia Ratnasamy +1
Invariants, the relations expected to hold among measured signals of a network, underpin applications from verification to traffic generation, telemetry imputation, and input valid…
HOWLR: A Client-Driven Approach to BGP Hijack Detection
Constantine Doumanidis, Anya Kalogerakos, Maria Apostolaki
BGP hijacking enables impersonation attacks in which adversaries divert traffic at the prefix level and serve malicious content to unsuspecting clients. Detecting such attacks has…
Worst-Case Discovery and Runtime Protection for RL-Based Network Controllers
Hongyu Hè, Minhao Jin, Maria Apostolaki
RL-based controllers achieve strong average-case performance in networking tasks such as congestion control and adaptive bitrate streaming. Yet their performance can degrade severe…
Cross-Flow Correlations Survive Synthesis: Measuring Source-Level Privacy Leakage in Synthetic Network Traces
Minhao Jin, Hongyu Hè, Maria Apostolaki
Synthetic network data generators (SynNetGens) are increasingly used to share realistic traffic traces without exposing sensitive raw data. While substantial effort has gone into i…
Making Logic a First-Class Citizen in Generative ML for Networking
Hongyu Hè, Minhao Jin, Maria Apostolaki
Generative ML models are increasingly popular in networking for tasks such as telemetry imputation, prediction, and synthetic trace generation. Despite their capabilities, they suf…
Robustifying ML-powered Network Classifiers with PANTS
Minhao Jin, Maria Apostolaki
Multiple network management tasks, from resource allocation to intrusion detection, rely on some form of ML-based network traffic classification (MNC). Despite their potential, MNC…
Super-resolution on network telemetry time series
Fengchen Gong, Divya Raghunathan, Aarti Gupta +1
Fine-grained monitoring is crucial for multiple data-driven tasks such as debugging, provisioning, and securing networks. Yet, practical constraints in collecting, extracting, and…