Esteban Carisimo

We introduce Borges (Better ORGanizations Entities mappingS), a novel framework for improving AS-to-Organization mappings using Large Language Models (LLMs). Existing approaches, such as AS2Org and its extensions, rely on static WHOIS data and rule-based extraction from PeeringDB records, limiting their ability to capture complex, dynamic organizational structures. Borges overcomes these limitations by combining traditional sources with few-shot LLM prompting to extract sibling relationships from free-text fields in PeeringDB, and by introducing website-based inference using redirect chains, domain similarity, and favicon analysis. Our evaluation shows that Borges outperforms prior methods, achieving a 7% improvement in sibling ASN identification and an Organization Factor score of 0.3576. It also expands the recognized user base of large Internet conglomerates by 192 million users (approx. 5% of the global Internet population) and improves geographic footprint estimates across multiple regions.

Geolocating network devices is essential for various research areas. Yet, despite notable advancements, it continues to be one of the most challenging issues for experimentalists. An approach for geolocating that has proved effective is leveraging geolocating hints in PTR records associated with network devices. We argue that Large Language Models (LLMs), rather than humans, are better equipped to identify patterns in DNS PTR of tools like Hoiho. We introduce an approach that leverages LLMs to classify PTR records, and generate regular expressions for these classes, and hint-to-location mapping. We present preliminary results showing the applicability of using LLMs as a scalable approach to leverage PTR records for infrastructure geolocation.

The Venezuelan crisis, unfolding over the past decade, has garnered international attention due to its impact on various sectors of civil society. While studies have extensively covered the crisis’s effects on public health, energy, and water management, this paper delves into a previously unexplored area - the impact on Venezuela’s Internet infrastructure. Amidst Venezuela’s multifaceted challenges, understanding the repercussions of this critical aspect of modern society becomes imperative for the country’s recovery. Leveraging measurements from various sources, we present a comprehensive view of the changes undergone by the Venezuelan network in the past decade. Our study reveals the significant impact of the crisis captured by different signals, including bandwidth stagnation, limited growth on network infrastructure growth, and high latency compared to the Latin American average. Beyond offering a new perspective on the Venezuelan crisis, our study can help inform attempts at devising strategies for its recovery.