Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment.
The performance of Internet services is intrinsically tied to propagation delays between end points (i.e., network latency). Standard active probe-based or passive host-based methods for measuring end-to-end latency are difficult to deploy at scale and typically offer limited precision and accuracy. In this paper, we investigate a novel but non-obvious source of latency measurement---logs from network time protocol (NTP) servers. Using NTP-derived data for studying latency is compelling due to NTP's pervasive use in the Internet and its inherent focus on accurate end-to-end delay estimation. We consider the efficacy of an NTP-based approach for studying propagation delays by analyzing logs collected from 10 NTP servers distributed across the United States. These logs include over 73M latency measurements to 7.4M worldwide clients (as indicated by unique IP addresses) collected over the period of one day. Our initial analysis of the general characteristics of propagation delays derived from the log data reveals that delay measurements from NTP must be carefully filtered in order to extract accurate results. We develop a filtering process that removes measurements that are likely to be inaccurate. After applying our filter to NTP measurements, we report on the scope and reach for US-based clients and the characteristics of the end-to-end latency for those clients.  Network operators often apply policy-based traffic filtering at the egress of edge networks. These policies can be detected by performing active measurements; however, doing so involves instrumenting every network one wishes to study. We investigate a methodology for detecting policy-based service-level traffic filtering from passive observation of traffic markers within darknets. Such markers represent traffic we expect to arrive and, therefore, whose absence is suggestive of network filtering. We study the approach with data from five large darknets over the course of one week. While we show the approach has utility to expose filtering in some cases, there are also limits to the methodology. The monitoring of packets destined for routeable, yet unused, Internet addresses has proved to be a useful technique for measuring a variety of specific Internet phenomenon (e.g., worms, DDoS). In 2004, stepped beyond these targeted uses and provided one of the first generic characterizations of this non-productive traffic, demonstrating both its significant size and diversity. However, the six years that followed this study have seen tremendous changes in both the types of malicious activity on the Internet and the quantity and quality of unused address space. In this paper, we revisit the state of Internet "background radiation" through the lens of two unique data-sets: a five-year collection from a single unused 8 network block, and week-long collections from three recently allocated 8 network blocks. Through the longitudinal study of the long-lived block, comparisons between blocks, and extensive case studies of traffic in these blocks, we characterize the current state of background radiation specifically highlighting those features that remain invariant from previous measurements and those which exhibit significant differences. Of particular interest in this work is the exploration of address space pollution, in which significant non uniform behavior is observed. However, unlike previous observations of differences between unused blocks, we show that increasingly these differences are the result of environmental factors (e.g., misconfiguration, location), rather than algorithmic factors. Where feasible, we offer suggestions for clean up of these polluted blocks and identify those blocks whose allocations should be withheld.  In the first months of 2011, Internet communications were disrupted in several North African countries in response to civilian protests and threats of civil war. In this paper we analyze episodes of these disruptions in two countries: Egypt and Libya. Our analysis relies on multiple sources of large-scale data already available to academic researchers: BGP interdomain routing control plane data; unsolicited data plane traffic to unassigned address space; active macroscopic traceroute measurements; RIR delegation files; and MaxMind's geolocation database. We used the latter two data sets to determine which IP address ranges were allocated to entities within each country, and then mapped these IP addresses of interest to BGP-announced address ranges (prefixes) and origin ASes using publicly available BGP data repositories in the U.S. and Europe. We then analyzed observable activity related to these sets of prefixes and ASes throughout the censorship episodes. Using both control plane and data plane data sets in combination allowed us to narrow down which forms of Internet access disruption were implemented in a given region over time. Among other insights, we detected what we believe were Libya's attempts to test firewall-based blocking before they executed more aggressive BGP-based disconnection. Our methodology could be used, and automated, to detect outages or similar macroscopically disruptive events in other geographic or topological regions.