Loqman Salamatian

2026

1. ACM SIGCOMM

   A Global Inference and Assessment of Large Shared IP Addresses

   Vasileios Giotsas,  Loqman Salamatian, Antoine Cordelle, Nick Wood, and Marwan Fayed

   Proceedings of the ACM SIGCOMM 2026 Conference, 2026
2. 

   ACM SIGCOMM

   HERMES: Repurposing User-Driven Speed Tests to Monitor the Internet

   Loqman Salamatian, Kevin Vermeulen, David Choffnes, Ethan Katz-Bassett, and Phillipa Gill

   Proceedings of the ACM SIGCOMM 2026 Conference, 2026

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   Internet observatories are essential for monitoring network health and performance. Diagnosing performance degradation and pinpointing its source is crucial for operators to make informed routing decisions and for policymakers and researchers to assess the Internet’s stability, yet no publicly available system currently provides this capability. Existing solutions rely on coarse-grained signals that fail to capture end-user performance, while proprietary solutions, in addition to being inaccessible, offer limited attribution for identifying the source of a problem. We introduce HERMES, the first open system to fill this gap. HERMES uses publicly available M-Lab speed tests—data that has existed for years but has never been used to automatically detect and explain end-user performance degradations at scale. To achieve these goals, HERMES combines robust statistical techniques to detect performance degradation with novel tomography methods and forward and reverse path measurements to localize the source of a problem. Despite relying on sparse public data, HERMES attains precision comparable to a proprietary CDN system and surfaces 12×more publicly discussed events than existing public observatories. We demonstrate HERMES’s ability to (i) track the impact of weather and cable cuts, (ii) diagnose routing inefficiencies, and (iii) identify persistently congested links.

2024

1. 

   ACM IMC

   What’s in the Dataset? Unboxing the APNIC per AS User Population Dataset

   Loqman Salamatian, Calvin Ardi, Vasileios Giotsas, Matt Calder, Ethan Katz-Bassett, and Todd Arnold

   Proceedings of the 2024 ACM on Internet Measurement Conference, 2024

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   The research measurement community needs methods and datasets to identify user concentrations and to accurately weight ASes against each other for analyzing measurements’ coverage. However, academic researchers traditionally lack visibility into how many users are in each network or how much traffic flows to each network and so often fall back on treating all IP addresses or networks equally. As an alternative, some recent studies have used the APNIC per AS Population Estimates dataset, but it is unvalidated and its methodology is not fully public. In this work, we validate its use as a fairly reliable user population indicator. Our approach includes a detailed comparative analysis using a global CDN dataset, providing concrete evidence of the APNIC dataset’s accuracy. We find that the APNIC per-AS user estimates closely align with the Content Delivery Network (CDN) per-AS user estimates in 51.2% of countries and correctly identify the largest networks in 93.9% of cases. When we investigate the agreement with CDN traffic volume, the APNIC dataset closely aligns in 36.5% of countries, increasing to 91.0% when focusing only on larger networks. We also evaluate the limitations of the APNIC dataset, particularly its inability to accurately identify user populations for ASes in certain countries. To address this, we introduce new methods to improve its usability by focusing on the statistical representativeness of the underlying data collection process and ensuring consistency across several public datasets.

2. 

   ACM IMC

   metAScritic: Reframing AS-Level Topology Discovery as a Recommendation System

   Loqman Salamatian, Kevin Vermeulen, Italo Cunha, Vasilis Giotsas, and Ethan Katz-Bassett

   Proceedings of the 2024 ACM on Internet Measurement Conference, 2024

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   Despite prior efforts, the vast majority of the AS-level topology of the Internet remains hidden from BGP and traceroute vantage points. In this work, we introduce metAScritic, a novel system inspired by recommender system literature, designed to infer interconnections within a given metro. metAScritic uses the intuition that the connectivity matrix at a given metro is a low-rank system, since ASes employ similar peering strategies according to their infrastructures, traffic profiles, and business models. This approach allows metAScritic to accurately reconstruct the complete peering connectivity by measuring a strategic subset of interconnections that capture ASes’ underlying peering strategies. We evaluate metAScritic’s performance across six large metropolitan areas, achieving an average F-score of 0.88 on various validation datasets, including ground truth. metAScritic measures more than 86K edges and infers more than 368K edges, compared to the 13K edges observed for this subset of ASes in public BGP feeds – an increase of (24X) what is currently seen. We study the impact of our inferred links on Internet properties, illustrating the extent of the Internet’s flattening and demonstrating our ability to better predict the impact of route leaks and prefix hijacks, compared to relying only on the existing public view.

2023

1. 

   Communications of ACM

   A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers

   Loqman Salamatian, Scott Anderson, Joshua Mathews, Paul Barford, Walter Willinger, and Mark Crovella

   Commun. ACM, 2023

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   As hyperscalers such as Google, Microsoft, and Amazon play an increasingly important role in today’s Internet, they are also capable of manipulating probe packets that traverse their privately owned and operated backbones. As a result, standard traceroute-based measurement techniques are no longer a reliable means for assessing network connectivity in these global-scale cloud provider infrastructures. In response to these developments, we present a new empirical approach for elucidating connectivity in these private backbone networks. Our approach relies on using only "lightweight" (i.e., simple, easily interpretable, and readily available) measurements, but requires applying "heavyweight" mathematical techniques for analyzing these measurements. In particular, we describe a new method that uses network latency measurements and relies on concepts from Riemannian geometry (i.e., Ricci curvature) to assess the characteristics of the connectivity fabric of a given network infrastructure. We complement this method with a visualization tool that generates a novel manifold view of a network’s delay space. We demonstrate our approach by utilizing latency measurements from available vantage points and virtual machines running in datacenters of three large cloud providers to study different aspects of connectivity in their private backbones and show how our generated manifold views enable us to expose and visualize critical aspects of this connectivity.

2021

1. 

   Journal of Cybersecurity

   The geopolitics behind the routes data travel: a case study of Iran

   Loqman Salamatian, Frédérick Douzet, Kavé Salamatian, and Kévin Limonier

   Journal of Cybersecurity, 2021

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   In November 2019, in the wake of political demonstrations against the regime, Iran managed to selectively cut off most traffic from the global Internet while fully operating its own domestic network. It seemingly confirmed the main hypothesis our research had led us to, based on prior observation of data routing: Iran’s architecture of connectivity enables selective censorship of international traffic. This paper examines, through the case of Iran, how states can leverage the Border Gateway Protocol (BGP) as a tool of geopolitical control and what are the trade-offs they face. This question raises a methodological question that we also address: how the analysis of BGP can infer and document these strategies of territorialization of cyberspace. The Internet is a network of networks where each network is an autonomous system. Autonomous systems (ASes) are independent administrative entities controlled by a variety of actors such as governments, companies and universities. Their administrators have to agree and communicate on the path followed by packets travelling across the Internet, which is made possible by BGP. Agreements between ASes are often confidential but BGP requires neighbouring ASes to interact with each other in order to coordinate routing through the constant release of connectivity update messages. These messages announce the availability (or withdrawal) of a sequence of ASes that can be followed to reach an IP address prefix. In our study, we inferred the structure of Iran’s connectivity through the capture and analysis of these BGP announcements. We show how the particularities of Iran’s BGP and connectivity structure can enable active measures, such as censorship, both internally and externally throughout the network. We argue that Iran has found a way to reconcile a priori conflicting strategic goals: developing a self-sustaining and resilient domestic Internet, but with tight control at its borders. It thus enables the regime to leverage connectivity as a tool of censorship in the face of social instability and as a tool of regional influence in the context of strategic competition.