Prof. Laurent Vanbever
Group Leader
My research interests lie at the crossroads of theory and practice, with a focus on network programmability. Overall, I aim at making networks both more performant and easier to manage.
I completed my PhD in computer science in 2012 at the University of Louvain under the guidance of Olivier Bonaventure. My thesis is entitled "Methods and Techniques for Disruption-Free Network Reconfiguration". After my PhD, I spent two years at Princeton University working with Jennifer Rexford as a postdoctoral researcher.
Prior to my PhD, I earned my master degree in computer science from the University of Louvain in 2008. I also earned a master degree in management from the Solvay Brussels School of Economics and Management in 2010.
Check my resume, research and teaching statements for further information.
Recent Selected Publications
Blink: Fast Connectivity Recovery Entirely in the Data Plane
USENIX NSDI 2019. Boston, Massachusetts, USA (February 2019).
@inproceedings {227629,
title = {Blink: Fast Connectivity Recovery Entirely in the Data Plane},
booktitle = {16th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 19)},
year = {2019},
address = {Boston, MA},
url = {https://www.usenix.org/conference/nsdi19/presentation/holterbach},
publisher = {{USENIX} Association},
}
<div></div>
<div>We present Blink, a data-driven system that leverages TCP-induced signals to detect failures directly in the data plane. The key intuition behind Blink is that a TCP flow exhibits a predictable behavior upon disruption: retransmitting the same packet over and over, at epochs exponentially spaced in time. When compounded over multiple flows, this behavior creates a strong and characteristic failure signal. Blink efficiently analyzes TCP flows to: (i) select which ones to track; (ii) reliably and quickly detect major traffic disruptions; and (iii) recover connectivity---all this, completely in the data plane. We present an implementation of Blink in P4 together with an extensive evaluation on real and synthetic traffic traces. Our results indicate that Blink: (i) achieves sub-second rerouting for large fractions of Internet traffic; and (ii) prevents unnecessary traffic shifts even in the presence of noise. We further show the feasibility of Blink by running it on an actual Tofino switch.</div>
SABRE: Protecting Bitcoin against Routing Attacks
NDSS Symposium 2019. San Diego, CA, USA (February 2019).
Nowadays Internet routing attacks remain practically effective as existing countermeasures either fail to provide protection guarantees or are not easily deployable. Blockchain systems are particularly vulnerable to such attacks as they rely on Internet-wide communications to reach consensus. In particular, Bitcoin---the most widely-used cryptocurrency---can be split in half by any AS-level adversary using BGP hijacking. <br /><br />In this paper, we present SABRE, a secure and scalable Bitcoin relay network which relays blocks worldwide through a set of connections that are resilient to routing attacks. SABRE runs alongside the existing peer-to-peer network and is easily deployable. As a critical system, SABRE design is highly resilient and can efficiently handle high bandwidth loads, including Denial of Service attacks. <br /><br />We built SABRE around two key technical insights. First, we leverage fundamental properties of inter-domain routing (BGP) policies to host relay nodes: (i) in networks that are inherently protected against routing attacks; and (ii) on paths that are economically-preferred by the majority of Bitcoin clients. These properties are generic and can be used to protect other Blockchain-based systems. Second, we leverage the fact that relaying blocks is communication-heavy, not computation-heavy. This enables us to offload most of the relay operations to programmable network hardware (using the P4 programming language). Thanks to this hardware/software co-design, SABRE nodes operate seamlessly under high load while mitigating the effects of malicious clients. <br /><br />We present a complete implementation of SABRE together with an extensive evaluation. Our results demonstrate that SABRE is effective at securing Bitcoin against routing attacks, even with deployments of as few as 6 nodes.
Hardware-Accelerated Network Control Planes
ACM HotNets 2018. Redmond, WA, USA (November 2018).
@inproceedings{costamolero_2018_hardware_accelerated_cps,
title={{Hardware-Accelerated Network Control Planes },
author={Costa Molero, Edgar and Vissicchio, Stefano and Vanbever, Laurent},
booktitle={Proceedings of the 17th ACM Workshop on Hot Topics in Networks},
year={2018},
organization={ACM}
}
One design principle of modern network architecture seems to be set in stone: a software-based control plane drives a hardware- or software-based data plane. We argue that it is time to revisit this principle after the advent of programmable switch ASICs which can run complex logic at line rate.
We explore the possibility and benefits of accelerating the control plane by offloading some of its tasks directly to the network hardware. We show that programmable data planes are indeed powerful enough to run key control plane tasks including: failure detection and notification, connectivity retrieval, and even policy-based routing protocols. We implement in P4 a prototype of such a “hardware-accelerated” control plane, and illustrate its benefits in a case study.
Despite such benefits, we acknowledge that offloading tasks to hardware is not a silver bullet. We discuss its tradeoffs and limitations, and outline future research directions towards hardware-software codesign of network control planes.
NetHide: Secure and Practical Network Topology Obfuscation
USENIX Security 2018. Baltimore, MD, USA (August 2018).
@inproceedings{meier18nethide,
title={NetHide: Secure and Practical Network Topology Obfuscation},
author={Meier, Roland and Tsankov, Petar and Lenders, Vincent and Vanbever, Laurent and Vechev, Martin},
booktitle={27th $\{$USENIX$\}$ Security Symposium ($\{$USENIX$\}$ Security 18)},
organization={USENIX$\}$ Association$\}$}
}
Simple path tracing tools such as traceroute allow malicious users to infer network topologies remotely and use that knowledge to craft advanced denial-of-service (DoS) attacks such as Link-Flooding Attacks (LFAs). Yet, despite the risk, most network operators still allow path tracing as it is an essential network debugging tool.
In this paper, we present NetHide, a network topology obfuscation framework that mitigates LFAs while preserving the practicality of path tracing tools. The key idea behind NetHide is to formulate network obfuscation as a multi-objective optimization problem that allows for a flexible tradeoff between security (encoded as hard constraints) and usability (encoded as soft constraints). While solving this problem exactly is hard, we show that NetHide can obfuscate topologies at scale by only considering a subset of the candidate solutions and without reducing obfuscation quality. In practice, NetHide obfuscates the topology by intercepting and modifying path tracing probes directly in the data plane. We show that this process can be done at line-rate, in a stateless fashion, by leveraging the latest generation of programmable network devices.
We fully implemented NetHide and evaluated it on realistic topologies. Our results show that NetHide is able to obfuscate large topologies (> 150 nodes) while preserving near-perfect debugging capabilities. In particular, we show that operators can still precisely trace back > 90% of link failures despite obfuscation.
Bayonet: Probabilistic Inference for Networks
PLDI 2018. Philadelphia, Pennsylvania, USA (June 2018).
Network operators often need to ensure that important probabilistic properties are met, such as that the probability of network congestion is below a certain threshold. Ensuring such properties is challenging and requires both a suitable language for probabilistic networks and an automated procedure for answering probabilistic inference queries. We present Bayonet, a novel approach that consists of: (i) a probabilistic network programming language and (ii) a system that performs probabilistic inference on Bayonet programs. The key insight behind Bayonet is to phrase the problem of probabilistic network reasoning as inference in existing probabilistic languages. As a result, Bayonet directly leverages existing probabilistic inference systems and offers a flexible and expressive interface to operators. We present a detailed evaluation of Bayonet on common network scenarios, such as network congestion, reliability of packet delivery, and others. Our results indicate that Bayonet can express such practical scenarios and answer queries for realistic topology sizes (with up to 30 nodes).
Stroboscope: Declarative Network Monitoring on a Budget
USENIX NSDI 2018. Renton, Washington, USA (April 2018).
@inproceedings {211289,
author = {Olivier Tilmans and Tobias B{\"u}hler and Ingmar Poese and Stefano Vissicchio and Laurent Vanbever},
title = {Stroboscope: Declarative Network Monitoring on a Budget},
booktitle = {15th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 18)},
year = {2018},
address = {Renton, WA},
url = {https://www.usenix.org/conference/nsdi18/presentation/tilmans},
publisher = {{USENIX} Association},
}
For an Internet Service Provider (ISP), getting an accurate picture of how its network behaves is challenging. Indeed, given the carried traffic volume and the impossibility to control end-hosts, ISPs often have no other choice but to rely on heavily sampled traffic statistics, which provide them with coarse-grained visibility at a less than ideal time resolution (seconds or minutes). We present Stroboscope, a system that enables fine-grained monitoring of any traffic flow by instructing routers to mirror millisecond-long traffic slices in a programmatic way. Stroboscope takes as input high-level monitoring queries together with a budget and automatically determines: (i) which flows to mirror; (ii) where to place mirroring rules, using fast and provably correct algorithms; and (iii) when to schedule these rules to maximize coverage while meeting the input budget. We implemented Stroboscope, and show that it scales well: it computes schedules for large networks and query sizes in few seconds, and produces a number of mirroring rules well within the limits of current routers. We also show that Stroboscope works on existing routers and is therefore immediately deployable.
NetComplete: Practical Network-Wide Configuration Synthesis with Autocompletion
USENIX NSDI 2018. Renton, Washington, USA (April 2018).
@inproceedings {211247,
author = {Ahmed El-Hassany and Petar Tsankov and Laurent Vanbever and Martin Vechev},
title = {NetComplete: Practical Network-Wide Configuration Synthesis with Autocompletion},
booktitle = {15th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 18)},
year = {2018},
address = {Renton, WA},
url = {https://www.usenix.org/conference/nsdi18/presentation/el-hassany},
publisher = {{USENIX} Association},
}
Network operators often need to adapt the configuration of a network in order to comply with changing routing policies. Evolving existing configurations, however, is a complex task as local changes can have unforeseen global effects. Not surprisingly, this often leads to mistakes that result in network downtimes. We present NetComplete, a system that assists operators in modifying existing network-wide configurations to comply with new routing policies. NetComplete takes as input configurations with “holes” that identify the parameters to be completed and “autocompletes” these with concrete values. The use of a partial configuration addresses two important challenges inherent to existing synthesis solutions: (i) it allows the operators to precisely control how configurations should be changed; and (ii) it allows the synthesizer to leverage the existing configurations to gain performance. To scale, NetComplete relies on powerful techniques such as counter-example guided inductive synthesis (for link-state protocols) and partial evaluation (for path-vector protocols). We implemented NetComplete and showed that it can autocomplete configurations using static routes, OSPF, and BGP. Our implementation also scales to realistic networks and complex routing policies. Among others, it is able to synthesize configurations for networks with up to 200 routers within few minutes.
Net2Text: Query-Guided Summarization of Network Forwarding Behaviors
USENIX NSDI 2018. Renton, Washington, USA (April 2018).
@inproceedings {211231,
author = {Rudiger Birkner and Dana Drachsler-Cohen and Laurent Vanbever and Martin Vechev},
title = {Net2Text: Query-Guided Summarization of Network Forwarding Behaviors},
booktitle = {15th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 18)},
year = {2018},
address = {Renton, WA},
url = {https://www.usenix.org/conference/nsdi18/presentation/birkner},
publisher = {{USENIX} Association},
}
Today network operators spend a significant amount of time struggling to understand how their network forwards traffic. Even simple questions such as "How is my network handling Google traffic?" often require operators to manually bridge large semantic gaps between low-level forwarding rules distributed across many routers and the corresponding high-level insights. We introduce Net2Text, a system which assists network operators in reasoning about network-wide forwarding behaviors. Out of the raw forwarding state and a query expressed in natural language, Net2Text automatically produces succinct summaries, also in natural language, which efficiently capture network-wide semantics. Our key insight is to pose the problem of summarizing ("captioning") the network forwarding state as an optimization problem that aims to balance coverage, by describing as many paths as possible, and explainability, by maximizing the information provided. As this problem is NP-hard, we also propose an approximation algorithm which generates summaries based on a sample of the forwarding state, with marginal loss of quality. We implemented Net2Text and demonstrated its practicality and scalability. We show that Net2Text generates high-quality interpretable summaries of the entire forwarding state of hundreds of routers with full routing tables, in few seconds only.
Integrating Verification and Repair into the Control Plane
ACM HotNets 2017. Palo Alto, California, USA (November 2017).
@inproceedings {AGJRV2017,
title = {{Integrating Verification and Repair into the Control Plane}},
author = {Aaron Gember-Jacobson and Costin Raiciu and Laurent Vanbever},
year = {2017},
booktitle = {Proceedings of HotNets-XVI},
}
Network verification has made great progress recently, yet existing solutions are limited in their ability to handle specific protocols or implementation quirks or to diagnose and repair the cause of policy violations. In this positioning paper, we examine whether we can achieve the best of both worlds: full coverage of control plane protocols and decision processes combined with the ability to diagnose and repair the cause of violations. To this end, we leverage the happens-before relationships that exist between control plane I/Os (e.g., route advertisements and forwarding updates). These relationships allow us to identify when it is safe to employ a data plane verifier and track the root-cause of problematic forwarding updates. We show how we can capture errors before they are installed, automatically trace down the source of the error and roll-back the updates whenever possible.
SWIFT: Predictive Fast Reroute.
ACM SIGCOMM 2017. Los Angeles, California, USA (August 2017).
@inproceedings{holterbach2017swift,
title={SWIFT: Predictive Fast Reroute},
author={Holterbach, Thomas and Vissicchio, Stefano and Dainotti, Alberto and Vanbever, Laurent},
booktitle={Proceedings of the Conference of the ACM Special Interest Group on Data Communication},
pages={460--473},
year={2017},
organization={ACM}
}
Network operators often face the problem of remote outages in transit networks leading to significant (sometimes on the order of minutes) downtimes. The issue is that BGP, the Internet routing protocol, often converges slowly upon such outages, as large bursts of messages have to be processed and propagated router by router. In this paper, we present SWIFT, a fast-reroute framework which enables routers to restore connectivity in few seconds upon remote outages. SWIFT is based on two novel techniques. First, SWIFT deals with slow outage notification by predicting the overall extent of a remote failure out of few control-plane (BGP) messages. The key insight is that significant inference speed can be gained at the price of some accuracy. Second, SWIFT introduces a new dataplane encoding scheme, which enables quick and flexible update of the affected forwarding entries. SWIFT is deployable on existing devices, without modifying BGP.
We present a complete implementation of SWIFT and demonstrate that it is both fast and accurate. In our experiments with real BGP traces, SWIFT predicts the extent of a remote outage in few seconds with an accuracy of ?90% and can restore connectivity for 99% of the affected destinations.
Lectures
Communication Networks
Spring 2019
Advanced Topics in Communication Networks
Autumn 2018
Discrete Event Systems
Autumn 2018
Communication Networks
Spring 2018
Discrete Event Systems
Autumn 2017
Communication Networks
Spring 2017
Discrete Event Systems
Autumn 2016
Communication Networks
Spring 2016
Discrete Event Systems
Autumn 2015
