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1. M2G: A Monitor of Monitoring Systems with Ground Truth Validation Features for Research-Oriented Residential Applications

   Ma, C.; Alam, R.; Bell, B.; de la Haye, K.; Spruijt-Metz, D.; Lach, J.; Stankovic, J. (January 2017, MASS)

   Research in the area of internet-of-things, cyber physical- systems, and smart health often employ sensor systems at residences for continuous monitoring. Such research oriented residential monitoring systems (RRMSs) usually face two major challenges, long-term reliable operation management and validation of system functionality with minimal human effort. Targeting these two challenges, this paper describes a monitor of monitoring systems with ground-truth validation capabilities, M2G. It consists of two subsystems, the Monitor2 system and the Ground-truth validation system. The Monitor2 system encapsulates a flexible set of general-purpose components to monitor the operation and connectivity of heterogeneous sensor devices (e.g. smart watches, smart phones, microphones, beacons, etc.), a local base-station, as well as a cloud server. It provides a user-friendly interface and supports different types of RRMSs in various contexts. The system also features a ground truth validation system to support obtaining ground truth in the field. Additionally, customized alerts can be sent to remote administrators and other personnel to report any dysfunction or inaccuracy of the system in real time. M2G is applied to three very different case studies: the M2FED system which monitors family eating dynamics, an in-home wireless sensing system for monitoring nighttime agitation, and the BESI system which monitors behavioral and environmental parameters to predict health events and to provide interventions. The results indicate that M2G is a comprehensive system that (i) requires small cost in time and effort to adapt to an existing RRMS, (ii) provides reliable data collection and reduction in data loss by detecting faults in real-time, and (iii) provides a convenient and timely ground truth validation facility. 

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2. Regulation When Platforms Are Layered

   https://doi.org/http://dx.doi.org/10.2139/ssrn.3427499  

   Lehr, W; Clark, D; Bauer, S; claffy, k (September 2019, Telecommunications Policy Research Conference (TPRC))

   In previous papers, Lehr and Sicker (2018a,b) argued that the changing character of our telecommunications infrastructure called for a new regulatory approach, with a new Communications Act to define the duties and authorities of a reconceptualized FCC (what we call newFCC in this paper). Today's Internet ecosystem is comprised of multiple digital network platforms organized into a multi-layer architecture. Lower layer IP platforms provided by access and backbone ISPs collectively support the Internet, on which complementors can build higher-layer platforms, such as the platforms provided by powerful firms such as Google, Microsoft, Amazon, Facebook and Apple. These firms control and operate multiple platforms within the larger Internet ecosystem. When dominant platform providers pursue multi-platform strategies in an effort to capture or control a market, such strategies confound current methods for defining markets and assessing market power. This paper draws on the layered platform nature of the Internet ecosystem, as described in Claffy and Clark (2014), to illustrate how this layered character of today’s Internet ecosystem calls for new regulatory authority. This paper draws on the layered platform model to scope the duties for an agency (or agencies) with sector-specific expertise. 

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3. Identifying Current Barriers in RPKI Adoption

   Testart, Cecilia; Wolff, Josephine; Gouda, Deepak; Fontugne, Romain (September 2024, Proceedings of the TPRC2024 The Research Conference on Communications, Information and Internet Policy)

   Society increasingly relies on the Internet as a critical infrastructure. Inter-domain routing is a core Internet protocol that enables trac to flow globally across independent networks. Concerns about Internet infrastructure security have prompted policymakers to promote stronger routing security and the Resource Public Key Infrastructure (RPKI) in particular. RPKI is a cryptographic framework to secure routing that was standardized in 2012. In 2024, almost 50% of routed IP address blocks are still not covered by RPKI certificates. It is unclear what barriers are preventing net- works from adopting RPKI. This paper investigates networks with low RPKI adoption to understand where and why adoption is low or non-existent. We find that networks’ geographical area of service, size, business category and complexity of address space delegation impact RPKI adoption. Our analysis may help direct policymakers’ efforts to promote RPKI adoption and improve the state of routing security. 

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4. From Scarcity to Opportunity: Examining Abuse of the IPv4 Leasing Market

   Degen, Bernhard; Du, Ben; Mok, Ricky; Sommese, Raffaele; Jonker, Mattijs; Martijn_van_Rijswijk-Deij, Roland; Claffy, kc (June 2025, IEEE)

   Since the exhaustion of unallocated IP addresses at the Internet Assigned Numbers Authority (IANA), a market for IPv4 addresses has emerged. In complement to purchasing address space, leasing IP addresses is becoming increasingly popular. Leasing provides a cost-effective alternative for organizations that seek to scale up without a high upfront investment. However, malicious actors also benefit from leasing as it enables them to rapidly cycle through different addresses, circumventing security measures such as IP blocklisting. We explore the emerging IP leasing market and its implications for Internet security. We examine leasing market data, leveraging blocklists as an indirect measure of involvement in various forms of network abuse. In February 2025, leased prefixes were 2.89× more likely to be flagged by blocklists compared to non-leased prefixes. This result raises questions about whether the IP leasing market should be subject to closer scrutiny. 

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5. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks

   https://doi.org/10.1145/3534678.3539049  

   Wang, Zhiyuan; Zhou, Fan; Zeng, Wenxuan; Trajcevski, Goce; Xiao, Chunjing; Wang, Yong; Chen, Kai (August 2022, The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining)

   Pinpointing the geographic location of an IP address is important for a range of location-aware applications spanning from targeted advertising to fraud prevention. The majority of traditional measurement-based and recent learning-based methods either focus on the efficient employment of topology or utilize data mining to find clues of the target IP in publicly available sources. Motivated by the limitations in existing works, we propose a novel framework named GraphGeo, which provides a complete processing methodology for street-level IP geolocation with the application of graph neural networks. It incorporates IP hosts knowledge and kinds of neighborhood relationships into the graph to infer spatial topology for high-quality geolocation prediction. We explicitly consider and alleviate the negative impact of uncertainty caused by network jitter and congestion, which are pervasive in complicated network environments. Extensive evaluations across three large-scale real-world datasets demonstrate that GraphGeo significantly reduces the geolocation errors compared to the state-of-the-art methods. Moreover, the proposed framework has been deployed on the web platform as an online service for 6 months. 

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