arXiv subjects

Xenofontas Dimitropoulos

Publications and source records attributed to Xenofontas Dimitropoulos.

36 records · Page 2Linked to original sources

arXiv2016

A Comparative Look into Public IXP Datasets

Internet eXchange Points (IXPs) are core components of the Internet infrastructure where Internet Service Providers (ISPs) meet and exchange traffic. During the last few years, the number and size of IXPs have increased rapidly, driving the flattening and shortening of Internet paths. However, understanding the present status of the IXP ecosystem and its potential role in shaping the future Internet requires rigorous data about IXPs, their presence, status, participants, etc. In this work, we do the first cross-comparison of three well-known publicly available IXP databases, namely of PeeringDB, Euro-IX, and PCH. A key challenge we address is linking IXP identifiers across databases maintained by different organizations. We find different AS-centric versus IXP-centric views provided by the databases as a result of their data collection approaches. In addition, we highlight differences and similarities w.r.t. IXP participants, geographical coverage, and co-location facilities. As a side-product of our linkage heuristics, we make publicly available the union of the three databases, which includes 40.2 % more IXPs and 66.3 % more IXP participants than the commonly-used PeeringDB. We also publish our analysis code to foster reproducibility of our experiments and shed preliminary insights into the accuracy of the union dataset.

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arXiv2016

Control Exchange Points: Providing QoS-enabled End-to-End Services via SDN-based Inter-domain Routing Orchestration

This paper presents the vision of the Control Exchange Point (CXP) architectural model. The model is motivated by the inflexibility and ossification of today's inter-domain routing system, which renders critical QoS-constrained end-to-end (e2e) network services difficult or simply impossible to provide. CXPs operate on slices of ISP networks and are built on basic Software Defined Networking (SDN) principles, such as the clean decoupling of the routing control plane from the data plane and the consequent logical centralization of control. The main goal of the architectural model is to provide e2e services with QoS constraints across domains. This is achieved through defining a new type of business relationship between ISPs, which advertise partial paths (so-called pathlets) with specific properties, and the orchestrating role of the CXPs, which dynamically stitch them together and provision e2e QoS. Revenue from value-added services flows from the clients of the CXP to the ISPs participating in the service. The novelty of the approach is the combination of SDN programmability and dynamic path stitching techniques for inter-domain routing, which extends the value proposition of SDN over multiple domains. We first describe the challenges related to e2e service provision with the current inter-domain routing and peering model, and then continue with the benefits of our approach. Subsequently, we describe the CXP model in detail and report on an initial feasibility analysis.

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arXiv2016

Stitching Inter-Domain Paths over IXPs

Modern Internet applications, from HD video-conferencing to health monitoring and remote control of power-plants, pose stringent demands on network latency, bandwidth and availability. An approach to support such applications and provide inter-domain guarantees, enabling new avenues for innovation, is using centralized inter-domain routing brokers. These entities centralize routing control for mission-critical traffic across domains, working in parallel to BGP. In this work, we propose using IXPs as natural points for stitching inter-domain paths under the control of inter-domain routing brokers. To evaluate the potential of this approach, we first map the global substrate of inter-IXP pathlets that IXP members could offer, based on measurements for 229 IXPs worldwide. We show that using IXPs as stitching points has two useful properties. Up to 91 % of the total IPv4 address space can be served by such inter-domain routing brokers when working in concert with just a handful of large IXPs and their associated ISP members. Second, path diversity on the inter-IXP graph increases by up to 29 times, as compared to current BGP valley-free routing. To exploit the rich path diversity, we introduce algorithms that inter-domain routing brokers can use to embed paths, subject to bandwidth and latency constraints. We show that our algorithms scale to the sizes of the measured graphs and can serve diverse simulated path request mixes. Our work highlights a novel direction for SDN innovation across domains, based on logically centralized control and programmable IXP fabrics.

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arXiv2016

A Novel Framework for Modeling and Mitigating Distributed Link Flooding Attacks

Distributed link-flooding attacks constitute a new class of attacks with the potential to segment large areas of the Internet. Their distributed nature makes detection and mitigation very hard. This work proposes a novel framework for the analytical modeling and optimal mitigation of such attacks. The detection is modeled as a problem of relational algebra, representing the association of potential attackers (bots) to potential targets. The analysis seeks to optimally dissolve all but the malevolent associations. The framework is implemented at the level of online Traffic Engineering (TE), which is naturally triggered on link-flooding events. The key idea is to continuously re-route traffic in a manner that makes persistent participation to link-flooding events highly improbable for any benign source. Thus, bots are forced to adopt a suspicious behavior to remain effective, revealing their presence. The load-balancing objective of TE is not affected at all. Extensive simulations on various topologies validate our analytical findings.

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arXiv2016

On the Interplay of Link-Flooding Attacks and Traffic Engineering

Link-flooding attacks have the potential to disconnect even entire countries from the Internet. Moreover, newly proposed indirect link-flooding attacks, such as 'Crossfire', are extremely hard to expose and, subsequently, mitigate effectively. Traffic Engineering (TE) is the network's natural way of mitigating link overload events, balancing the load and restoring connectivity. This work poses the question: Do we need a new kind of TE to expose an attack as well? The key idea is that a carefully crafted, attack-aware TE could force the attacker to follow improbable traffic patterns, revealing his target and his identity over time. We show that both existing and novel TE modules can efficiently expose the attack, and study the benefits of each approach. We implement defense prototypes using simulation mechanisms and evaluate them extensively on multiple real topologies.

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arXiv2016

Monitor, Detect, Mitigate: Combating BGP Prefix Hijacking in Real-Time with ARTEMIS

The Border Gateway Protocol (BGP) is globally used by Autonomous Systems (ASes) to establish route paths for IP prefixes in the Internet. Due to the lack of authentication in BGP, an AS can hijack IP prefixes owned by other ASes (i.e., announce illegitimate route paths), impacting thus the Internet routing system and economy. To this end, a number of hijacking detection systems have been proposed. However, existing systems are usually third party services that -inherently- introduce a significant delay between the hijacking detection (by the service) and its mitigation (by the network administrators). To overcome this shortcoming, in this paper, we propose ARTEMIS, a tool that enables an AS to timely detect hijacks on its own prefixes, and automatically proceed to mitigation actions. To evaluate the performance of ARTEMIS, we conduct real hijacking experiments. To our best knowledge, it is the first time that a hijacking detection/mitigation system is evaluated through extensive experiments in the real Internet. Our results (a) show that ARTEMIS can detect (mitigate) a hijack within a few seconds (minutes) after it has been launched, and (b) demonstrate the efficiency of the different control-plane sources used by ARTEMIS, towards monitoring routing changes.

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arXiv2016

Analysing the Effects of Routing Centralization on BGP Convergence Time

Software-defined networking (SDN) has improved the routing functionality in networks like data centers or WANs. Recently, several studies proposed to apply the SDN principles in the Internet's inter-domain routing as well. This could offer new routing opportunities and improve the performance of BGP, which can take minutes to converge to routing changes. Previous works have demonstrated that centralization can benefit the functionality of BGP, and improve its slow convergence that causes severe packet losses and performance degradation. However, due to (a) the fact that previous works mainly focus on system design aspects, and (b) the lack of real deployments, it is not clearly understood yet to what extent inter-domain SDN can improve performance. To this end, in this work, we make the first effort towards analytically studying the effects of routing centralization on the performance of inter-domain routing, and, in particular, the convergence time of BGP. Specifically, we propose a Markovian model for inter-domain networks, where a subset of nodes (domains) coordinate to centralize their inter-domain routing. We then derive analytic results that quantify the BGP convergence time under various network settings (like, SDN penetration, topology, BGP configuration, etc.). Our analysis and results facilitate the performance evaluation of inter-domain SDN networks, which have been studied (till now) only through simulations/emulations that are known to suffer from high time/resource requirements and limited scalability.

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arXiv2014

Towards Defeating the Crossfire Attack using SDN

In this work, we propose online traffic engineering as a novel approach to detect and mitigate an emerging class of stealthy Denial of Service (DoS) link-flooding attacks. Our approach exploits the Software Defined Networking (SDN) paradigm, which renders the management of network traffic more flexible through centralised flow-level control and monitoring. We implement a full prototype of our solution on an emulated SDN environment using OpenFlow to interface with the network devices. We further discuss useful insights gained from our preliminary experiments as well as a number of open research questions which constitute work in progress.

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arXiv2014

Lost in Space: Improving Inference of IPv4 Address Space Utilization

One challenge in understanding the evolution of Internet infrastructure is the lack of systematic mechanisms for monitoring the extent to which allocated IP addresses are actually used. In this paper we try to advance the science of inferring IPv4 address space utilization by analyzing and correlating results obtained through different types of measurements. We have previously studied an approach based on passive measurements that can reveal used portions of the address space unseen by active approaches. In this paper, we study such passive approaches in detail, extending our methodology to four different types of vantage points, identifying traffic components that most significantly contribute to discovering used IPv4 network blocks. We then combine the results we obtained through passive measurements together with data from active measurement studies, as well as measurements from BGP and additional datasets available to researchers. Through the analysis of this large collection of heterogeneous datasets, we substantially improve the state of the art in terms of: (i) understanding the challenges and opportunities in using passive and active techniques to study address utilization; and (ii) knowledge of the utilization of the IPv4 space.

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arXiv2010

SEPIA: Security through Private Information Aggregation

Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that are practical in terms of computation and communication cost is still a major challenge. In this paper, we investigate the practical usefulness of MPC for multi-domain network security and monitoring. We first optimize MPC comparison operations for processing high volume data in near real-time. We then design privacy-preserving protocols for event correlation and aggregation of network traffic statistics, such as addition of volume metrics, computation of feature entropy, and distinct item count. Optimizing performance of parallel invocations, we implement our protocols along with a complete set of basic operations in a library called SEPIA. We evaluate the running time and bandwidth requirements of our protocols in realistic settings on a local cluster as well as on PlanetLab and show that they work in near real-time for up to 140 input providers and 9 computation nodes. Compared to implementations using existing general-purpose MPC frameworks, our protocols are significantly faster, requiring, for example, 3 minutes for a task that takes 2 days with general-purpose frameworks. This improvement paves the way for new applications of MPC in the area of networking. Finally, we run SEPIA's protocols on real traffic traces of 17 networks and show how they provide new possibilities for distributed troubleshooting and early anomaly detection.

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arXiv2009

Graph Annotations in Modeling Complex Network Topologies

The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some non-trivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of network applications and protocols, or any other simulations involving complex network topologies, including modeling and simulation of network evolution. We apply our approach to the Autonomous System (AS) topology of the Internet annotated with business relationships between ASs. This topology captures the large-scale structure of the Internet. In depth understanding of this structure and tools to model it are cornerstones of research on future Internet architectures and designs. We find that our techniques are able to accurately capture the structure of annotation correlations within this topology, thus reproducing a number of its important properties in synthetically-generated random graphs.

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arXiv2008

On Cycles in AS Relationships

Several users of our AS relationship inference data (http://www.caida.org/data/active/as-relationships/), released with cs/0604017, asked us why it contained AS relationship cycles, e.g., cases where AS A is a provider of AS B, B is a provider of C, and C is a provider of A, or other cycle types. Having been answering these questions in private communications, we have eventually decided to write down our answers here for future reference.

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arXiv2006

AS Relationships: Inference and Validation

Research on performance, robustness, and evolution of the global Internet is fundamentally handicapped without accurate and thorough knowledge of the nature and structure of the contractual relationships between Autonomous Systems (ASs). In this work we introduce novel heuristics for inferring AS relationships. Our heuristics improve upon previous works in several technical aspects, which we outline in detail and demonstrate with several examples. Seeking to increase the value and reliability of our inference results, we then focus on validation of inferred AS relationships. We perform a survey with ASs' network administrators to collect information on the actual connectivity and policies of the surveyed ASs. Based on the survey results, we find that our new AS relationship inference techniques achieve high levels of accuracy: we correctly infer 96.5% customer to provider (c2p), 82.8% peer to peer (p2p), and 90.3% sibling to sibling (s2s) relationships. We then cross-compare the reported AS connectivity with the AS connectivity data contained in BGP tables. We find that BGP tables miss up to 86.2% of the true adjacencies of the surveyed ASs. The majority of the missing links are of the p2p type, which highlights the limitations of present measuring techniques to capture links of this type. Finally, to make our results easily accessible and practically useful for the community, we open an AS relationship repository where we archive, on a weekly basis, and make publicly available the complete Internet AS-level topology annotated with AS relationship information for every pair of AS neighbors.

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arXiv2006

Revealing the Autonomous System Taxonomy: The Machine Learning Approach

Although the Internet AS-level topology has been extensively studied over the past few years, little is known about the details of the AS taxonomy. An AS "node" can represent a wide variety of organizations, e.g., large ISP, or small private business, university, with vastly different network characteristics, external connectivity patterns, network growth tendencies, and other properties that we can hardly neglect while working on veracious Internet representations in simulation environments. In this paper, we introduce a radically new approach based on machine learning techniques to map all the ASes in the Internet into a natural AS taxonomy. We successfully classify 95.3% of ASes with expected accuracy of 78.1%. We release to the community the AS-level topology dataset augmented with: 1) the AS taxonomy information and 2) the set of AS attributes we used to classify ASes. We believe that this dataset will serve as an invaluable addition to further understanding of the structure and evolution of the Internet.

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arXiv2005

The Internet AS-Level Topology: Three Data Sources and One Definitive Metric

We calculate an extensive set of characteristics for Internet AS topologies extracted from the three data sources most frequently used by the research community: traceroutes, BGP, and WHOIS. We discover that traceroute and BGP topologies are similar to one another but differ substantially from the WHOIS topology. Among the widely considered metrics, we find that the joint degree distribution appears to fundamentally characterize Internet AS topologies as well as narrowly define values for other important metrics. We discuss the interplay between the specifics of the three data collection mechanisms and the resulting topology views. In particular, we show how the data collection peculiarities explain differences in the resulting joint degree distributions of the respective topologies. Finally, we release to the community the input topology datasets, along with the scripts and output of our calculations. This supplement should enable researchers to validate their models against real data and to make more informed selection of topology data sources for their specific needs.

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arXiv2005

Lessons from Three Views of the Internet Topology

Network topology plays a vital role in understanding the performance of network applications and protocols. Thus, recently there has been tremendous interest in generating realistic network topologies. Such work must begin with an understanding of existing network topologies, which today typically consists of a relatively small number of data sources. In this paper, we calculate an extensive set of important characteristics of Internet AS-level topologies extracted from the three data sources most frequently used by the research community: traceroutes, BGP, and WHOIS. We find that traceroute and BGP topologies are similar to one another but differ substantially from the WHOIS topology. We discuss the interplay between the properties of the data sources that result from specific data collection mechanisms and the resulting topology views. We find that, among metrics widely considered, the joint degree distribution appears to fundamentally characterize Internet AS-topologies: it narrowly defines values for other important metrics. We also introduce an evaluation criteria for the accuracy of topology generators and verify previous observations that generators solely reproducing degree distributions cannot capture the full spectrum of critical topological characteristics of any of the three topologies. Finally, we release to the community the input topology datasets, along with the scripts and output of our calculations. This supplement should enable researchers to validate their models against real data and to make more informed selection of topology data sources for their specific needs.

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arXiv2005

Inferring AS Relationships: Dead End or Lively Beginning?

Recent techniques for inferring business relationships between ASs have yielded maps that have extremely few invalid BGP paths in the terminology of Gao. However, some relationships inferred by these newer algorithms are incorrect, leading to the deduction of unrealistic AS hierarchies. We investigate this problem and discover what causes it. Having obtained such insight, we generalize the problem of AS relationship inference as a multiobjective optimization problem with node-degree-based corrections to the original objective function of minimizing the number of invalid paths. We solve the generalized version of the problem using the semidefinite programming relaxation of the MAX2SAT problem. Keeping the number of invalid paths small, we obtain a more veracious solution than that yielded by recent heuristics.

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arXiv2005

Revisiting Internet AS-level Topology Discovery

The development of veracious models of the Internet topology has received a lot of attention in the last few years. Many proposed models are based on topologies derived from RouteViews BGP table dumps (BTDs). However, BTDs do not capture all AS-links of the Internet topology and most importantly the number of the hidden AS-links is unknown, resulting in AS-graphs of questionable quality. As a first step to address this problem, we introduce a new AS-topology discovery methodology that results in more complete and accurate graphs. Moreover, we use data available from existing measurement facilities, circumventing the burden of additional measurement infrastructure. We deploy our methodology and construct an AS-topology that has at least 61.5% more AS-links than BTD-derived AS-topologies we examined. Finally, we analyze the temporal and topological properties of the augmented graph and pinpoint the differences from BTD-derived AS-topologies.

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