Prof. Laurent Vanbever
Group Leader
I am an associate professor at ETH Zurich. 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.
To find out more about my work, check out my resume, activity reports (2022, 2021, 2020), research and teaching statements.
You can also find me on the Fediverse / Mastodon: @laurent@vanbever.ch.
Selected Publications
Taming the transient while reconfiguring BGP
ACM SIGCOMM 2023. New York City, NY, USA (September 2023).
Enhancing Global Network Monitoring with Magnifier
USENIX NSDI 2023. Boston, MA, USA (April 2023).
Monitoring where traffic enters and leaves a network is a routine task for network operators. In order to scale with Tbps of traffic, large Internet Service Providers (ISPs) mainly use traffic sampling for such global monitoring. Sampling either provides a sparse view or generates unreasonable overhead. While sampling can be tailored and optimized to specific contexts, this coverage–overhead trade-off is unavoidable.
Rather than optimizing sampling, we propose to “magnify” the sampling coverage by complementing it with mirroring. Magnifier enhances the global network view using a two-step approach: based on sampling data, it first infers traffic ingress and egress points using a heuristic, then it uses mirroring to validate these inferences efficiently. The key idea behind Magnifier is to use negative mirroring rules; i.e., monitor where traffic should not go. We implement Magnifier on commercial routers and demonstrate that it indeed enhances the global network view with negligible traffic overhead. Finally, we observe that monitoring based on our heuristics also allows to detect other events, such as certain failures and DDoS attacks.
xBGP: Faster Innovation in Routing Protocols
USENIX NSDI 2023. Boston, MA, USA (April 2023).
Internet Service Providers use routers from multiple ven- dors that support standardized routing protocols. Network operators deploy new services by tuning these protocols. Un- fortunately, while standardization is necessary for interoper- ability, this is a slow process. As a consequence, new features appear very slowly in routing protocols.
We propose a new implementation model for BGP, called xBGP, that enables ISPs to innovate by easily deploying BGP extensions in their multivendor network. We define a vendor- neutral xBGP API which can be supported by any BGP im- plementation and an eBPF Virtual Machine that allows ex- ecuting extension code within these BGP implementations. We demonstrate the feasibility of our approach by extending both FRRouting and BIRD.
We demonstrate seven different use cases showing the ben- efits that network operators can obtain using xBGP programs. We propose a verification toolchain that enables operators to compile and verify the safety properties of xBGP programs before deploying them. Our testbed measurements show that the performance impact of xBGP is reasonable compared to native code.
Learning to Configure Computer Networks with Neural Algorithmic Reasoning
NeurIPS 2022. New Orleans, LA, USA (November 2022).
We present a new method for scaling automatic configuration of computer networks. The key idea is to relax the computationally hard search problem of finding a configuration that satisfies a given specification into an approximate objective amenable to learning-based techniques. Based on this idea, we train a neural algorithmic model which learns to generate configurations likely to (fully or partially) satisfy a given specification under existing routing protocols. By relaxing the rigid satisfaction guarantees, our approach (i) enables greater flexibility: it is protocol-agnostic, enables cross-protocol reasoning, and does not depend on hardcoded rules; and (ii) finds configurations for much larger computer networks than previously possible. Our learned synthesizer is up to 490× faster than state-of-the-art SMT-based methods, while producing configurations which on average satisfy more than 92% of the provided requirements.
Generating representative, live network traffic out of millions of code repositories
ACM HotNets 2022. Austin, Texas, USA (November 2022).
In theory, any network operator, developer, or vendor should have access to large amounts of live network traffic for testing their solutions. In practice, though, that is not the case. Network actors instead have to use packet traces or synthetic traffic, which is highly suboptimal: today's generated traffic is unrealistic. We propose a system for generating live application traffic leveraging massive codebases such as GitHub.
Our key observation is that many repositories have now become "orchestrable" thanks to the rise of container technologies. To showcase the practicality of the approach, we iterate through >293k GitHub repositories and manage to capture >74k traces containing meaningful and diverse network traffic. Based on this first success, we outline the design of a system, DYNAMO, which analyzes these traces to select and orchestrate open-source projects to automatically generate live application traffic matching a user's specification.
A New Hope for Network Model Generalization
ACM HotNets 2022. Austin, Texas, USA (November 2022).
Generalizing machine learning (ML) models for network traffic dynamics tends to be considered a lost cause. Hence for every new task, we design new models and train them on model-specific datasets closely mimicking the deployment environments. Yet, an ML architecture called Transformer has enabled previously unimaginable generalization in other domains. Nowadays, one can download a model pre-trained on massive datasets and only fine-tune it for a specific task and context with comparatively little time and data. These fine-tuned models are now state-of-the-art for many benchmarks.
We believe this progress could translate to networking and propose a Network Traffic Transformer (NTT), a transformer adapted to learn network dynamics from packet traces. Our initial results are promising: NTT seems able to generalize to new prediction tasks and environments. This study suggests there is still hope for generalization through future research.
On the Complexity of Network-Wide Configuration Synthesis
IEEE ICNP 2022. Lexington, KY, USA (November 2022).
Configuration Synthesis promises to increase automation in network hardware configuration but is generally assumed to constitute a computationally hard problem. We conduct a formal analysis of the computational complexity of network-wide Configuration Synthesis to establish this claim formally. To that end, we consider Configuration Synthesis as a decision problem, whether or not the selected routing protocol(s) can implement a given set of forwarding properties.
We find the complexity of Configuration Synthesis heavily depends on the combination of the forwarding properties that need to be implemented in the network, as well as the employed routing protocol(s). Our analysis encompasses different forwarding properties that can be encoded as path constraints, and any combination of distributed destination-based hop-by-hop routing protocols. Many of these combinations yield NP-hard Configuration Synthesis problems; in particular, we show that the satisfiability of a set of arbitrary waypoints for any hop-by-hop routing protocol is NP-complete. Other combinations, however, show potential for efficient, scalable Configuration Synthesis.
Aggregate-Based Congestion Control for Pulse-Wave DDoS Defense
ACM SIGCOMM 2022. Amsterdam, Netherlands (August 2022).
Pulse-wave DDoS attacks are a new type of volumetric attack consisting of short, high-rate traffic pulses. Such attacks target the Achilles' heel of state-of-the-art DDoS defenses: their reaction time. By continuously adapting their attack vectors, pulse-wave attacks manage to render existing defenses ineffective.
In this paper, we leverage programmable switches to build an in-network DDoS defense effective against pulse-wave attacks. To do so, we revisit Aggregate-based Congestion Control (ACC): a mechanism proposed twenty years ago to manage congestion events caused by high-bandwidth traffic aggregates. While ACC proved efficient in inferring and controlling DoS attacks, it cannot keep up with the speed requirements of pulse-wave attacks.
We propose ACC-Turbo, a renewed version of ACC, which infers attack patterns by applying online-clustering techniques in the network and mitigates them by using programmable packet scheduling. By doing so, ACC-Turbo can infer attacks at line rate and in real-time; and rate-limit attack traffic on a per-packet basis.
We fully implement ACC-Turbo in P4 and evaluate it on a wide range of attack scenarios. Our evaluation shows that ACC-Turbo autonomously identifies DDoS attack vectors in an unsupervised manner and rapidly mitigates pulse-wave DDoS attacks. We also show that ACC-Turbo runs on existing hardware (Intel Tofino).
FAst In-Network GraY Failure Detection for ISPs
ACM SIGCOMM 2022. Amsterdam, Netherlands (August 2022).
Avoiding packet loss is crucial for ISPs. Unfortunately, malfunctioning hardware at ISPs can cause long-lasting packet drops, also known as gray failures, which are undetectable by existing monitoring tools.
In this paper, we describe the design and implementation of FANcY, an ISP-targeted system that detects and localizes gray failures quickly and accurately. FANcY complements previous monitoring approaches, which are mainly tailored for low-delay networks such as data center networks and do not work at ISP scale. We experimentally confirm FANcY’s capability to accurately detect gray failures in seconds, as long as only tiny fractions of traffic experience losses. We also implement FANcY in an Intel Tofino switch, demonstrating how it enables fine-grained fast rerouting.
ABM: Active Buffer Management in Datacenters
ACM SIGCOMM 2022. Amsterdam, Netherlands (August 2022).
Today’s network devices share buffer across queues to avoid drops during transient congestion and absorb bursts. As the buffer-perbandwidth-unit in datacenter decreases, the need for optimal buffer utilization becomes more pressing. Typical devices use a hierarchical packet admission control scheme: First, a Buffer Management (BM) scheme decides the maximum length per queue at the device level and then an Active Queue Management (AQM) scheme decides which packets will be admitted at the queue level. Unfortunately, the lack of cooperation between the two control schemes leads to (i) harmful interference across queues, due to the lack of isolation; (ii) increased queueing delay, due to the obliviousness to the per-queue drain time; and (iii) thus unpredictable burst tolerance. To overcome these limitations, we propose ABM, Active Buffer Management which incorporates insights from both BM and AQM. Concretely, ABM accounts for both total buffer occupancy (typically used by BM) and queue drain time (typically used by AQM). We analytically prove that ABM provides isolation, bounded buffer drain time and achieves predictable burst tolerance without sacrificing throughput. We empirically find that ABM improves the 99th percentile FCT for short flows by up to 94% compared to the state-of-the-art buffer management. We further show that ABM improves the performance of advanced datacenter transport protocols in terms of FCT by up to 76% compared to DCTCP, TIMELY and PowerTCP under bursty workloads even at moderate load conditions.
ditto: WAN Traffic Obfuscation at Line Rate
NDSS Symposium 2022. San Diego, CA, USA (April 2022).
Many large organizations operate dedicated wide area networks (WANs) distinct from the Internet to connect their data centers and remote sites through high-throughput links. While encryption generally protects these WANs well against content eavesdropping, they remain vulnerable to traffic analysis attacks that infer visited websites, watched videos or contents of VoIP calls from analysis of the traffic volume, packet sizes or timing information. Existing techniques to obfuscate Internet traffic are not well suited for WANs as they are either highly inefficient or require modifications to the communication protocols used by end hosts.
This paper presents ditto, a traffic obfuscation system adapted to the requirements of WANs: achieving high-throughput traffic obfuscation at line rate without modifications of end hosts. ditto adds padding to packets and introduces chaff packets to make the resulting obfuscated traffic independent of production traffic with respect to packet sizes, timing and traffic volume.
We evaluate a full implementation of ditto running on programmable switches in the network data plane. Our results show that ditto runs at 100 Gbps line rate and performs with negligible performance overhead up to a realistic traffic load of 70 Gbps per WAN link.
Snowcap: Synthesizing Network-Wide Configuration Updates
ACM SIGCOMM 2021. Online (August 2021).
Large-scale reconfiguration campaigns tend to be nerve-racking for network operators as they can lead to significant network downtimes, decreased performance, and policy violations. Unfortunately, existing reconfiguration frameworks often fall short inpractice as they either only support a small set of reconfiguration scenarios or simply do not scale.
We address these problems with Snowcap, the first network reconfiguration framework which can synthesize configuration updates that comply with arbitrary hard and soft specifications, and involve arbitrary routing protocols. Our key contributionis an efficient search procedure which leverages counter-examples to efficiently navigate the space of configuration updates. Given a reconfiguration ordering which violates the desired specifications, our algorithm automatically identifies the problematic commands so that it can avoid this particular order in the next iteration.
We fully implemented Snowcap and extensively evaluated its scalability and effectiveness on real-world topologies and typical, large-scale reconfiguration scenarios. Even for large topologies, Snowcap finds a valid reconfiguration ordering with minimal side-effects (i.e., traffic shifts) within a few seconds at most.
Metha: Network Verifiers Need To Be Correct Too!
USENIX NSDI 2021. Online (April 2021).
Network analysis and verification tools are often a godsend for network operators as they free them from the fear of introducing outages or security breaches. As with any complex software though, these tools can (and often do) have bugs. For the operators, these bugs are not necessarily problematic except if they affect the precision of the model as it applies to their specific network. In that case, the tool output might be wrong: it might fail to detect actual configuration errors and/or report non-existing ones.
In this paper, we present Metha, a framework that systematically tests network analysis and verification tools for bugs in their network models. Metha automatically generates syntactically- and semantically-valid configurations; compares the tool’s output to that of the actual router software; and detects any discrepancy as a bug in the tool’s model. The challenge in testing network analyzers this way is that a bug may occur very rarely and only when a specific set of configuration statements is present. We address this challenge by leveraging grammar-based fuzzing together with combinatorial testing to ensure thorough coverage of the search space and by identifying the minimal set of statements triggering the bug through delta debugging.
We implemented Metha and used it to test three well-known tools. In all of them, we found multiple (new) bugs in their models, most of which were confirmed by the developers.
xBGP: When you can’t wait for the IETF and vendors
ACM HotNets 2020. Chicago, Illinois, USA (November 2020).
Thanks to the standardization of routing protocols such as BGP, OSPF or IS-IS, Internet Service Providers (ISP) and enterprise networks can deploy routers from various vendors. This prevents them from vendor-lockin problems. Unfortunately, this also slows innovation since any new feature must be standardized and implemented by all vendors before being deployed.
We propose a paradigm shift that enables network operators to program the routing protocols used in their networks. We demonstrate the feasibility of this approach with xBGP. xBGP is a vendor neutral API that exposes the key data structures and functions of any BGP implementation. Each xBGP compliant implementation includes an eBPF virtual machine that executes the operator supplied programs. We extend FRRouting and BIRD to support this new paradigm and demonstrate the flexibility of xBGP with four different use cases. Finally, we discuss how xBGP could affect future research on future routing protocols.
P2GO: P4 Profile-Guided Optimizations
ACM HotNets 2020. Chicago, Illinois, USA (November 2020).
Programmable devices allow the operator to specify the data-plane behavior of a network device in a high-level language such as P4. The compiler then maps the P4 program to the hardware after applying a set of optimizations to minimize resource utilization. Yet, the lack of context restricts the compiler to conservatively account for all possible inputs -- including unrealistic or infrequent ones -- leading to sub-optimal use of the resources or even compilation failures. To address this inefficiency, we propose that the compiler leverages insights from actual traffic traces, effectively unlocking a broader spectrum of possible optimizations.
We present a system working alongside the compiler that uses traffic-awareness to reduce the allocated resources of a P4 program by: (i) removing dependencies that do not manifest; (ii) adjusting table and register sizes to reduce the pipeline length; and (iii) offloading parts of the program that are rarely used to the controller. Our prototype implementation on the Tofino switch automatically profiles the P4 program, detects opportunities and performs optimizations to improve the pipeline efficiency.
Our work showcases the potential benefit of applying profiling techniques used to compile general-purpose languages to compiling P4 programs.
Probabilistic Verification of Network Configurations
ACM SIGCOMM 2020. New York, USA (August 2020).
Not all important network properties need to be enforced all the time. Often, what matters instead is the fraction of time / probability these properties hold. Computing the probability of a property in a network relying on complex inter-dependent routing protocols is challenging and requires determining all failure scenarios for which the property is violated. Doing so at scale and accurately goes beyond the capabilities of current network analyzers.
In this paper, we introduce NetDice, the first scalable and accurate probabilistic network configuration analyzer supporting BGP, OSPF, ECMP, and static routes. Our key contribution is an inference algorithm to efficiently explore the space of failure scenarios. More specifically, given a network configuration and a property phi, our algorithm automatically identifies a set of links whose failure is provably guaranteed not to change whether phi holds. By pruning these failure scenarios, NetDice manages to accurately approximate P(phi). NetDice supports practical properties and expressive failure models including correlated link failures.
We implement NetDice and evaluate it on realistic configurations. NetDice is practical: it can precisely verify probabilistic properties in few minutes, even in large networks.
An Open Platform to Teach How the Internet Practically Works
ACM SIGCOMM CCR 2020. Volume 50 Issue 2 (April 2020).
Each year at ETH Zurich, around 100 students collectively build and operate their very own Internet infrastructure composed of hundreds of routers and dozens of Autonomous Systems (ASes). Their goal? Enabling Internet-wide connectivity.
We find this class-wide project to be invaluable in teaching our students how the Internet infrastructure practically works. Among others, our students have a much deeper understanding of Internet operations alongside their pitfalls. Besides students tend to love the project: clearly the fact that all of them need to cooperate for the entire Internet to work is empowering.
In this paper, we describe the overall design of our teaching platform, how we use it, and interesting lessons we have learnt over the years. We also make our platform openly available.
Config2Spec: Mining Network Specifications from Network Configurations
USENIX NSDI 2020. Santa Clara, California, USA (February 2020).
Network verification and configuration synthesis are promising approaches to make networks more reliable and secure by enforcing a set of policies. However, these approaches require a formal and precise description of the intended network behavior, imposing a major barrier to their adoption: network operators are not only reluctant to write formal specifications, but often do not even know what these specifications are.
We present Config2Spec, a system that automatically synthesizes a formal specification (a set of policies) of a network given its configuration and a failure model (e.g., up to two link failures). A key technical challenge is to design a synthesis algorithm which can efficiently explore the large space of possible policies. To address this challenge, Config2Spec relies on a careful combination of two well-known methods: data plane analysis and control plane verification.
Experimental results show that Config2Spec scales to mining specifications of large networks (>150 routers).
SP-PIFO: Approximating Push-In First-Out Behaviors using Strict-Priority Queues
USENIX NSDI 2020. Santa Clara, California, USA (February 2020).
Push-In First-Out (PIFO) queues are hardware primitives which enable programmable packet scheduling by allowing to perfectly reorder packets at line rate. While promising, implementing PIFO queues in hardware and at scale is not easy: only hardware designs (not implementations) exist and they can only support about 1000 flows.
In this paper, we introduce SP-PIFO, a programmable packet scheduler which closely approximates the behavior of PIFO queues using strict-priority queues—at line rate, at scale, and on existing devices. The key insight behind SP-PIFO is to dynamically adapt the mapping between packet ranks and available queues to minimize the scheduling errors. We present a mathematical formulation of the problem and derive an adaptation technique which closely approximates the optimal queue mapping without any traffic knowledge.
We fully implement SP-PIFO in P4 and evaluate it on real workloads. We show that SP-PIFO: (i) closely matches ideal PIFO performance, with as little as 8 priority queues; (ii) arbitrarily scales to large amount of flows and ranks; and (iii) quickly adapts to traffic variations. We also show that SP-PIFO runs at line rate on existing programmable data planes.
(Self) Driving Under the Influence: Intoxicating Adversarial Network Inputs
ACM HotNets 2019. Princeton, NJ, USA (November 2019).
Traditional network control planes can be slow and require manual tinkering from operators to change their behavior. There is thus great interest in a faster, data-driven approach that uses signals from real-time traffic instead. However, the promise of fast and automatic reaction to data comes with new risks: malicious inputs designed towards negative outcomes for the network, service providers, users, and operators.
Adversarial inputs are a well-recognized problem in other areas; we show that networking applications are susceptible to them too. We characterize the attack surface of data-driven networks and examine how attackers with different privileges—from infected hosts to operator-level access—may target network infrastructure, applications, and protocols. To illustrate the problem, we present case studies with concrete attacks on recently proposed data-driven systems.
Our analysis urgently calls for a careful study of attacks and defenses in data-driven networking, with a view towards ensuring that their promise is not marred by oversights in robust design.
Blink: Fast Connectivity Recovery Entirely in the Data Plane
USENIX NSDI 2019. Boston, Massachusetts, USA (February 2019).
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.
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.
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.
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.
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).
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).
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).
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).
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).
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).
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).
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.
Network-wide Configuration Synthesis.
CAV 2017. Heidelberg, Germany (July 2017).
Computer networks are hard to manage. Given a set of highlevel requirements (e.g., reachability, security), operators have to manually figure out the individual configuration of potentially hundreds of devices running complex distributed protocols so that they, collectively, compute a compatible forwarding state. Not surprisingly, operators often make mistakes which lead to downtimes.
To address this problem, we present a novel synthesis approach that automatically computes correct network configurations that comply with the operator’s requirements. We capture the behavior of existing routers along with the distributed protocols they run in stratified Datalog. Our key insight is to reduce the problem of finding correct input configurations to the task of synthesizing inputs for a stratified Datalog program. To solve this synthesis task, we introduce a new algorithm that synthesizes inputs for stratified Datalog programs. This algorithm is applicable beyond the domain of networks.
We leverage our synthesis algorithm to construct the first network-wide configuration synthesis system, called SyNET, that support multiple interacting routing protocols (OSPF and BGP) and static routes. We show that our system is practical and can infer correct input configurations, in a reasonable amount time, for networks of realistic size (>50 routers) that forward packets for multiple traffic classes.
Hijacking Bitcoin: Routing Attacks on Cryptocurrencies.
IEEE Symposium on Security and Privacy 2017. San Jose, CA, USA (May 2017).
As the most successful cryptocurrency to date, Bitcoin constitutes a target of choice for attackers. While many attack vectors have already been uncovered, one important vector has been left out though: attacking the currency via the Internet routing infrastructure itself. Indeed, by manipulating routing advertisements (BGP hijacks) or by naturally intercepting traffic, Autonomous Systems (ASes) can intercept and manipulate a large fraction of Bitcoin traffic.
This paper presents the first taxonomy of routing attacks and their impact on Bitcoin, considering both small-scale attacks, targeting individual nodes, and large-scale attacks, targeting the network as a whole. While challenging, we show that two key properties make routing attacks practical: (i) the efficiency of routing manipulation; and (ii) the significant centralization of Bitcoin in terms of mining and routing. Specifically, we find that any network attacker can hijack few (<100) BGP prefixes to isolate 50% of the mining power—even when considering that mining pools are heavily multi-homed. We also show that on-path network attackers can considerably slow down block propagation by interfering with few key Bitcoin messages.
We demonstrate the feasibility of each attack against the deployed Bitcoin software. We also quantify their effectiveness on the current Bitcoin topology using data collected from a Bitcoin supernode combined with BGP routing data.
The potential damage to Bitcoin is worrying. By isolating parts of the network or delaying block propagation, attackers can cause a significant amount of mining power to be wasted, leading to revenue losses and enabling a wide range of exploits such as double spending. To prevent such effects in practice, we provide both short and long-term countermeasures, some of which can be deployed immediately.
Mille-Feuille: Putting ISP traffic under the scalpel.
ACM HotNets 2016. Atlanta, Georgia, USA (November 2016).
For Internet Service Provider (ISP) operators, getting an accurate picture of how their network behaves is challenging. Given the traffic volumes that their networks carry and the impossibility to control end-hosts, ISP operators are typically forced to randomly sample traffic, and rely on aggregated statistics. This provides coarse-grained visibility, at a time resolution that is far from ideal (seconds or minutes).
In this paper, we present Mille-Feuille, a novel monitoring architecture that provides fine-grained visibility over ISP traffic. Mille-Feuille schedules activation and deactivation of traffic-mirroring rules, that are then provisioned networkwide from a central location, within milliseconds. By doing so, Mille-Feuille combines the scalability of sampling with the visibility and controllability of traffic mirroring. As a result, it supports a set of monitoring primitives, ranging from checking key performance indicators (e.g., one-way delay) for single destinations to estimating traffic matrices in subseconds. Our preliminary measurements on existing routers confirm that Mille-Feuille is viable in practice.
SDNRacer: Concurrency Analysis for Software-Defined Networks.
ACM PLDI 2016. Santa Barbara, CA, USA (June 2016).
An Industrial-Scale Software Defined Internet Exchange Point.
Usenix NSDI 2016. Santa Clara, CA, USA (March 2016).
Media coverage: Open Networking Foundation, CloudRouter
Destroying networks for fun (and profit).
ACM HotNets 2015. Philadelphia, PA, USA (November 2015).
Central Control Over Distributed Routing.
ACM SIGCOMM 2015. London, UK (August 2015).
Media coverage: ipSpace
RAPTOR: Routing Attacks on Privacy in Tor.
USENIX Security 2015. Washington, D. C. , USA (August 2015).
Media coverage: ACM TechNews, The Register, Computer Business Review,
Help Net Security
DRAGON: Distributed Route Aggregation on the Global Network.
ACM CoNEXT 2014. Sydney, Australia (December 2014).
The Internet routing system faces serious scalability challenges, due to the growing number of IP prefixes it needs to propagate throughout the network. For example, the Internet suffered significant outages in August 2014 when the number of globally routable prefixes went past 512K, the default size of the forwarding tables in many older routers. Although IP prefixes are assigned hierarchically, and roughly align with geographic regions, today's Border Gateway Protocol (BGP) and operational practices do not exploit opportunities to aggregate routes. We present a distributed route-aggregation technique (called DRAGON) where nodes analyze BGP routes across different prefixes to determine which of them can be filtered while respecting the routing policies for forwarding data-packets. DRAGON works with BGP, can be deployed incrementally, and offers incentives for ASs to upgrade their router software. We present a theoretical model of route-aggregation, and the design and analysis of DRAGON. Our experiments with realistic assignments of IP prefixes, network topologies, and routing policies show that DRAGON reduces the number of prefixes in each AS by about 80% and significantly curtails the number of routes exchanged during transient periods of convergence.
Anonymity on QuickSand: Using BGP to Compromise Tor.
ACM HotNets 2014. Los Angeles, CA, USA (October 2014).
Anonymity systems like Tor are known to be vulnerable to malicious relay nodes. Another serious threat comes from the Autonomous Systems (ASes) that carry Tor traffic due to their powerful eavesdropping capabilities. Indeed, an AS (or set of colluding ASes) that lies between the client and the first relay, and between the last relay and the destination, can perform timing analysis to compromise user anonymity. In this paper, we show that AS-level adversaries are much more powerful than previously thought. First, routine BGP routing changes can significantly increase the number of ASes that can analyze a user's traffic successfully. Second, ASes can actively manipulate BGP announcements to put themselves on the paths to and from relay nodes. Third, an AS can perform timing analysis even when it sees only one direction of the traffic at both communication ends. Actually, asymmetric routing increases the fraction of ASes able to analyze a user's traffic. We present a preliminary evaluation of our attacks using measurements of BGP and Tor. Our findings motivate the design of approaches for anonymous communication that are resilient to AS-level adversaries.
Sweet Little Lies: Fake Topologies for Flexible Routing.
ACM HotNets 2014. Los Angeles, CA, USA (October 2014).
Link-state routing protocols (e.g., OSPF and IS-IS) are widely used because they are scalable, robust, and based on simple abstractions. Unfortunately, these protocols are also relatively inflexible, since they direct all traffic over shortest paths. In contrast, Software Defined Networking (SDN) offers fine-grained control over routing, at the expense of controller overhead, failover latency, and deployment challenges.
We argue that future networks can achieve the benefits of both approaches through central control over the distributed route computation. The key idea, which we call Fibbing, is to have the controller trick the routers into seeing a fake topology that is carefully constructed to achieve the desired Forwarding Information Base (FIB). Given an acyclic forwarding graph for each destination, the controller computes an augmented topology with fake nodes (and destinations to announce there) and fake links (and link weights). The controller injects these "lies" into the link-state routing protocol, and the routers simply compute the paths accordingly. The controller can also select an augmented topology that triggers the use of specific backup paths when real links and routers fail. To reduce router load, our Fibbing algorithms compute augmented topologies of minimal size. Our preliminary evaluation on realistic ISP topologies shows that Fibbing works well in practice.
SDX: A Software Defined Internet Exchange.
ACM SIGCOMM 2014. Chicago, IL, USA (August 2014).
BGP severely constrains how networks can deliver traffic over the Internet. Today's networks can only forward traffic based on the destination IP prefix, by selecting among routes offered by their immediate neighbors. We believe Software Defined Networking (SDN) could revolutionize wide-area traffic delivery, by offering direct control over packet-processing rules that match on multiple header fields and perform a variety of actions. Internet exchange points (IXPs) are a compelling place to start, given their central role in interconnecting many networks and their growing importance in bringing popular content closer to end users.
To realize a Software Defined IXP (an "SDX"), we must create compelling applications, such as "application-specific peering"---where two networks peer only for (say) streaming video traffic. We also need new programming abstractions that allow participating networks to create and run these applications and a runtime that both behaves correctly when interacting with BGP and ensures that applications do not interfere with each other. Finally, we must ensure that the system scales, both in rule-table size and computational overhead. In this paper, we tackle these challenges and demonstrate the flexibility and scalability of our solutions through controlled and in-the-wild experiments. Our experiments demonstrate that our SDX implementation can implement representative policies for hundreds of participants who advertise full routing tables while achieving sub-second convergence in response to configuration changes and routing updates.
SoftCell: Scalable and Flexible Cellular Core Network Architecture.
ACM CoNEXT 2013. Santa Barbara, CA, USA (December 2013).
Cellular core networks suffer from inflexible and expensive equipment, as well as from complex control-plane protocols. To address these challenges, we present SoftCell, a scalable architecture that supports fine-grained policies for mobile devices in cellular core networks, using commodity switches and servers. SoftCell enables operators to realize high-level service policies that direct traffic through sequences of middleboxes based on subscriber attributes and applications. To minimize the size of the forwarding tables, SoftCell aggregates traffic along multiple dimensions---the service policy, the base station, and the mobile device---at different switches in the network. Since most traffic originates from mobile devices, SoftCell performs fine-grained packet classification at the access switches, next to the base stations, where software switches can easily handle the state and bandwidth requirements. SoftCell guarantees that packets belonging to the same connection traverse the same sequence of middleboxes in both directions, even in the presence of mobility. We demonstrate that SoftCell improves the scalability and flexibility of cellular core networks by analyzing real LTE workloads, performing micro-benchmarks on our prototype controller as well as large-scale simulations.
Using Routers to Build Logic Circuits: How Powerful is BGP?
IEEE ICNP 2013. Göttingen, Germany (October 2013).
Fun: Our paper is listed on Accidentally Turing-Complete
Because of its practical relevance, the Border Gateway Protocol (BGP) has been the target of a huge research effort since more than a decade. In particular, many contributions aimed at characterizing the computational complexity of BGP-related problems. In this paper, we answer computational complexity questions by unveiling a fundamental mapping between BGP configurations and logic circuits. Namely, we describe simple networks containing routers with elementary BGP configurations that simulate logic gates, clocks, and flip-flops, and we show how to interconnect them to simulate arbitrary logic circuits. We then investigate the implications of such a mapping on the feasibility of solving BGP fundamental problems, and prove that, under realistic assumptions, BGP has the same computing power as a Turing Machine. We also investigate the impact of restrictions on the expressiveness of BGP policies and route propagation (e.g., route propagation rules in iBGP and Local Transit Policies in eBGP) and the impact of different message timing models. Finally, we show that the mapping is not limited to BGP and can be applied to generic routing protocols that use several metrics.
Improving Network Agility with Seamless BGP Reconfigurations
IEEE/ACM Transactions on Networking. Volume 21, Issue 3, pp. 990-1002 (June 2013)
The network infrastructure of Internet Service Providers (ISPs) undergoes constant evolution. Whenever new requirements arise (e.g., the deployment of a new Point of Presence, or a change in the business relationship with a neighboring ISP), operators need to change the configuration of the network. Due to the complexity of BGP and to the lack of methodologies and tools, maintaining service availability during reconfigurations that involve BGP is a challenge for operators. In this paper, we show that the current best practices to reconfigure BGP do not provide guarantees with respect to traffic disruptions. Then, we study the problem of finding an operational ordering of BGP reconfiguration steps which guarantees no packet loss. Unfortunately, finding such an operational ordering, when it exists, is computationally hard. To enable lossless reconfigurations, we propose a framework that extends current features of carrier-grade routers to run two BGP control planes in parallel. We present a prototype implementation and we show the effectiveness of our framework through a case study.
When the Cure is Worse than the Disease: the Impact of Graceful IGP Operations on BGP.
IEEE INFOCOM 2013. Turin, Italy (April 2013).
Network upgrades, performance optimizations and traffic engineering activities often force network operators to adapt their IGP configuration. Recently, several techniques have been proposed to change an IGP configuration (e.g., link weights) in a disruption-free manner. Unfortunately, none of these techniques considers the impact of IGP changes on BGP correctness. In this paper, we show that known reconfiguration techniques can trigger various kinds of BGP anomalies. First, we illustrate the relevance of the problem by performing simulations on a Tier-1 network. Our simulations highlight that even a few link weight changes can produce long-lasting BGP anomalies affecting a significant part of the BGP routing table. Then, we study the problem of finding a reconfiguration ordering which maintains both IGP and BGP correctness. Unfortunately, we show examples in which such an ordering does not exist. Furthermore, we prove that deciding if such an ordering exists is NP-hard. Finally, we provide sufficient conditions and configuration guidelines that enable graceful operations for both IGP and BGP.
iBGP Deceptions: More Sessions, Fewer Routes.
IEEE INFOCOM 2012. Orlando, FL, USA (March 2012).
Internal BGP (iBGP) is used to distribute interdomain routes within a single ISP. The interaction between iBGP and the underlying IGP can lead to routing and forwarding anomalies. For this reason, several research contributions aimed at defining sufficient conditions to guarantee anomaly-free configurations and providing design guidelines for network operators. In this paper, we show several anomalies caused by defective dissemination of routes in iBGP. We define the dissemination correctness property, which models the ability of routers to learn at least one route to each destination. By distinguishing between dissemination correctness and existing correctness properties, we show counterexamples that invalidate some results in the literature. Further, we prove that deciding whether an iBGP configuration is dissemination correct is computationally intractable. Even worse, determining whether the addition of a single iBGP session can adversely affect dissemination correctness of an iBGP configuration is also computationally intractable. Finally, we provide sufficient conditions that ensure dissemination correctness, and we leverage them to both formulate design guidelines and revisit prior results.
Seamless Network-Wide IGP Migrations.
ACM SIGCOMM 2011. Toronto, ON, Canada (August 2011).
Network-wide migrations of a running network, such as the replacement of a routing protocol or the modification of its configuration, can improve the performance, scalability, manageability, and security of the entire network. However, such migrations are an important source of concerns for network operators as the reconfiguration campaign can lead to long and service-affecting outages.
In this paper, we propose a methodology which addresses the problem of seamlessly modifying the configuration of commonly used link-state Interior Gateway Protocols (IGP). We illustrate the benefits of our methodology by considering several migration scenarios, including the addition or the removal of routing hierarchy in an existing IGP and the replacement of one IGP with another. We prove that a strict operational ordering can guarantee that the migration will not create IP transit service outages. Although finding a safe ordering is NP complete, we describe techniques which efficiently find such an ordering and evaluate them using both real-world and inferred ISP topologies. Finally, we describe the implementation of a provisioning system which automatically performs the migration by pushing the configurations on the routers in the appropriate order, while monitoring the entire migration process.
