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new workshop report “Overcoming Measurement Barriers to Internet Research” (WOMBIR 2021) in ACM CCR

WOMBIR 2021 was the NSF-sponsored Workshop on Overcoming Measurement Barriers to Internet Research. This workshop was hold in two sessions over several days in January and April 2021, chaired by k.c. claffy, David Clark, Fabian Bustamente, John Heidemann, and Mattijs Monjker. The final report includes contributions from Aaron Schulman and Ellen Zegura as well as all the workshop participants.

From the abstract:

In January and April 2021 we held the Workshop on Overcoming Measurement Barriers to Internet Research (WOMBIR) with the goal of understanding challenges in network and security data set collection and sharing. Most workshop attendees provided white papers describing their perspectives, and many participated in short-talks and discussion in two virtual workshops over five days. That discussion produced consensus around several points. First, many aspects of the Internet are characterized by decreasing visibility of important network properties, which is in tension with the Internet’s role as critical infrastructure. We discussed three specific research areas that illustrate this tension: security, Internet access; and mobile networking. We discussed visibility challenges at all layers of the networking stack, and the challenge of gathering data and validating inferences. Important data sets require longitudinal (long-term, ongoing) data collection and sharing, support for which is more challenging for Internet research than other fields. We discussed why a combination of technical and policy methods are necessary to safeguard privacy when using or sharing measurement data. Workshop participant proposed several opportunities to accelerate progress, some of which require coordination across government, industry, and academia.

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Papers Publications

new workshop paper “Leveraging Controlled Information Sharing for Botnet Activity Detection”

We have published a new paper “Leveraging Controlled Information Sharing for Botnet Activity Detection” in the Workshop on Traffic Measurements for Cybersecurity (WTMC 2018) in Budapest, Hungary, co-located with ACM SIGCOMM 2018.

The sensitivity of BotDigger’s detection is im- proved with controlled data sharing. All three domain/IP sets meet or pass the detection threshold.

From the abstract of our paper:

Today’s malware often relies on DNS to enable communication with command-and-control (C&C). As defenses that block traffic improve, malware use sophisticated techniques to hide this traffic, including “fast flux” names and Domain-Generation Algorithms (DGAs). Detecting this kind of activity requires analysis of DNS queries in network traffic, yet these signals are sparse. As bot countermeasures grow in sophistication, detecting these signals increasingly requires the synthesis of information from multiple sites. Yet *sharing security information across organizational boundaries* to date has been infrequent and ad hoc because of unknown risks and uncertain benefits. In this paper, we take steps towards formalizing cross-site information sharing and quantifying the benefits of data sharing. We use a case study on DGA-based botnet detection to evaluate how sharing cybersecurity data can improve detection sensitivity and allow the discovery of malicious activity with greater precision.

The relevant software is open-sourced and freely available at https://ant.isi.edu/retrofuture.

This paper is joint work between Calvin Ardi and John Heidemann from USC/ISI, with additional support from collaborators and Colorado State University and Los Alamos National Laboratory.

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Papers Publications

New workshop paper “IP-Based IoT Device Detection”

We have published a new paper “IP-Based IoT Device Detection” in the Second ACM Workshop on Internet-of-Things Security and Privacy (IoTS&P 2018) in Budapest, Hungary, co-located with SIGCOMM 2018.

IoT devices we detect in use at a campus (Table 3 from [Guo18b])
From the abstract of our  paper:

Recent IoT-based DDoS attacks have exposed how vulnerable the Internet can be to millions of insufficiently secured IoT devices. To understand the risks of these attacks requires
learning about these IoT devices—where are they, how many are there, how are they changing? In this paper, we propose
a new method to find IoT devices in Internet to begin to assess this threat. Our approach requires observations of flow-level network traffic and knowledge of servers run by
the manufacturers of the IoT devices. We have developed our approach with 10 device models by 7 vendors and controlled
experiments. We apply our algorithm to observations from 6 days of Internet traffic at a college campus and partial traffic
from an IXP to detect IoT devices.

We make operational traffic we captured from 10 IoT devices we own public at https://ant.isi.edu/datasets/iot/. We also use operational traffic of 21 IoT devices shared by University of New South Wales at http://149.171.189.1/.

This paper is joint work of Hang Guo and  John Heidemann from USC/ISI.

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DNS Papers Presentations Publications

New paper and talk “Enumerating Privacy Leaks in DNS Data Collected above the Recursive” at NDSS DNS Privacy Workshop 2018

Basileal Imana presented the paper “Enumerating Privacy Leaks in DNS Data Collected  above the Recursive” at NDSS DNS Privacy Workshop in San Diego, California, USA on February 18, 2018. Talk slides are available at https://ant.isi.edu/~imana/presentations/Imana18b.pdf and paper is available at  https://ant.isi.edu/~imana/papers/Imana18a.pdf, or can be found at the DNS privacy workshop page.

From the abstract:

Threat model for enumerating leaks above the recursive (left). Percentage of four categories of queries containing IPv4 addresses in their QNAMEs. (right)

As with any information system consisting of data derived from people’s actions, DNS data is vulnerable to privacy risks. In DNS, users make queries through recursive resolvers to authoritative servers. Data collected below (or in) the recursive resolver directly exposes users, so most prior DNS data sharing focuses on queries above the recursive resolver. Data collected above a recursive resolver has largely been seen as posing a minimal privacy risk since recursive resolvers typically aggregate traffic for many users, thereby hiding their identity and mixing their traffic. Although this assumption is widely made, to our knowledge it has not been verified. In this paper we re-examine this assumption for DNS traffic above the recursive resolver. First, we show that two kinds of information appear in query names above the recursive resolver: IP addresses and sensitive domain names, such as those pertaining to health, politics, or personal or lifestyle information. Second, we examine how often these classes of potentially sensitive names appear in Root DNS traffic, using 48 hours of B-Root data from April 2017.

This is a joint work by Basileal Imana (USC), Aleksandra Korolova (USC) and John Heidemann (USC/ISI).

The DITL dataset (ITL_B_Root-20170411) used in this work is available from DHS IMPACT, the ANT project, and through DNS-OARC.

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Presentations

new talk “Infrastructure for Experimental Replay and Mutation of DNS Queries” at the AIMS Workshop 2017

John Heidemann gave the talk “Infrastructure for Experimental Replay and Mutation of DNS Queries” at CAIDA’s Active Internet Measurement (AIMS) Workshop in San Diego, California, USA on March 2, 2017.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Zhu17a.pdf.
From the abstract:

Emulating the DNS hierarchy both efficiently and correctly.

The DNS ecosystem today is revisiting basic design questions: should it encourage TCP? TLS? DTLS? Something completely new like QUIC or HTTP? While modeling and analysis help answer some of these questions, experimental evaluation is necessary for validation, and in some cases the only way to get accurate estimates of software memory use and performance. This talk will discuss our recent work in supporting experimental evaluation of DNS with components that support trace replay and evaluation. Trace replay is supported by a DNS data archive to prime replay with real data, and a query mutation system to support what-if evaluation using variations of that data.

The trace replay system is the work with Liang Zhu; this work is part of a larger system to support DNS experimentation, joint work with Wes Hardaker.

The software discussed in the talk is available at https://ant.isi.edu/software/ldplayer, and this work is part of our progress towards the NIPET testbed.

 

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Presentations

new talk “Collecting and Visualizing Outages Over the Long Haul” at the AIMS Workshop 2017

John Heidemann gave the talk “Collecting and Visualizing Outages Over the Long Haul” at CAIDA’s Active Internet Measurement (AIMS) Workshop in San Diego, California, USA on March 2, 2017.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann17b.pdf.
From the abstract:

Unmeasurable blocks over time, a challenge in long-haul outage measurement, from [Alwabel15a]
We have been collecting data about outages in the Internet since Oct. 2014. Our outage detection system, Trinocular, uses active probing from four sites to study about 4 million /24 IPv4 address blocks. Long-duration measurements bring challenges that don’t occur in short observations. Most importantly, our target (“the Internet”) changes as we measure it, as new blocks come on-line, old blocks are reused in different ways, and ISPs observe and sometimes block our traffic. Our measurement platform also sees occasional hardware failures. Visualization can assist detection of these problems, allowing human perception to detect changes in data collection that have not previously been anticipated. This talk will discuss the challenges of long-term outage measurement and describe our new algorithm that scales to support clustering of 4M blocks and 3 months of observations for visualization.
Our visualization is joint work with Yuri Pradkin, and analysis of our long-term outages includes work with Abdulla Alwabel.

This talk draws on work from [Alwabel15a].  Data from this talk is available at https://ant.isi.edu/datasets/outage/, and visualizations can be found at https://ant.isi.edu/outage/browse/.

Categories
Presentations

new talk “DNS Privacy, Service Management, and Research: Friends or Foes” at the NDSS DNS Privacy Workshop 2017

John Heidemann gave the talk “DNS Privacy, Service Management, and Research: Friends or Foes” at the NDSS DNS Privacy Workshop in San Diego, California, USA on Feburary 26, 2017.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann17a.pdf.
The talk does not have a formal abstract, but to summarize:

A slide from the [Heidemann17a] talk, looking at what different DNS stakeholders may want.
A slide from the [Heidemann17a] talk, looking at what different DNS stakeholders may want.

This invited talk is part of a panel on the tension between DNS privacy and service management.  In the talk I expand on that topic and discuss
the tension between DNS privacy, service management, and research.
I give suggestions about how service management and research can adapt to proceed while still providing basic privacy.

Although not discussed in the talks, we distribute some DNS datasets,  available at https://ant.isi.edu/datasets/ and at https://impactcybertrust.org.  We also provide dnsanon, a tool to anonymize DNS queries.

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Announcements Projects

new workshop program for DINR-2016 (DNS and Internet Naming Research Directions)

We’re happy to be hosting DINR-2016 (DNS and Internet Naming Research Directions).

The workshop program is now online; folks interested in joining us should contact the chairs.

We’re looking forward to an exciting day of many short talks!

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Presentations

new talk “Anycast Latency: How Many Sites are Enough?” at DNS-OARC

John Heidemann gave the talk “Anycast Latency: How Many Sites are Enough?” at DNS-OARC in Dallas, Texas, USA on October 16, 2016.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann16b.pdf.

Comparing actual (obtained) anycast latency against optimal possible anycast latency, for 4 different anycast deployments (each a Root Letter). From the talk [Heidemann16b], based on data from [Moura16b].
Comparing actual (obtained) anycast latency against optimal possible anycast latency, for 4 different anycast deployments (each a Root Letter). From the talk [Heidemann16b], based on data from [Moura16b].
From the abstract:

This talk will evaluate anycast latency. An anycast service uses multiple sites to provide high availability, capacity and redundancy, with BGP routing associating users to nearby anycast sites. Routing defines the catchment of the users that each site serves. Although prior work has studied how users associate with anycast services informally, in this paper we examine the key question how many anycast sites are needed to provide good latency, and the worst case latencies that specific deployments see. To answer this question, we must first define the optimal performance that is possible, then explore how routing, specific anycast policies, and site location affect performance. We develop a new method capable of determining optimal performance and use it to study four real-world anycast services operated by different organizations: C-, F-, K-, and L-Root, each part of the Root DNS service. We measure their performance from more than worldwide vantage points (VPs) in RIPE Atlas. (Given the VPs uneven geographic distribution, we evaluate and control for potential bias.) Key results of our study are to show that a few sites can provide performance nearly as good as many, and that geographic location and good connectivity have a far stronger effect on latency than having many nodes. We show how often users see the closest anycast site, and how strongly routing policy affects site selection.

This talk is based on the work in the technical report “Anycast Latency: How Many Sites Are Enough?” (ISI-TR-2016-708), by Ricardo de O. Schmidt, John Heidemann, and Jan Harm Kuipers.

Datasets from the paper are available at https://ant.isi.edu/datasets/anycast/

Categories
Papers Publications

new workshop paper “Assessing Co-Locality of IP Blocks” in GI 2016

The paper “Assessing Co-Locality of IP Blocks” appeared in the 19th IEEE  Global Internet Symposium on April 11, 2016 in San Francisco, CA, USA and is available at (http://www.cs.colostate.edu/~manafgh/publications/Assessing-Co-Locality-of-IP-Block-GI2016.pdf). The datasets are available at (https://ant.isi.edu/datasets/geolocation/).

From the abstract:

isi_all_blocks_clustersCountMany IP Geolocation services and applications assume that all IP addresses within the same /24 IPv4 prefix (a /24 block) reside in close physical proximity. For blocks that contain addresses in very different locations (such as blocks identifying network backbones), this assumption can result in a large geolocation error. In this paper we evaluate the co-location assumption. We first develop and validate a hierarchical clustering method to find clusters of IP addresses with similar observed delay measurements within /24 blocks. We validate our methodology against two ground-truth datasets, confirming that 93% of the identified multi-cluster blocks are true positives with multiple physical locations and an upper bound for false positives of only about 5.4%. We then apply our methodology to a large dataset of 1.41M /24 blocks extracted from a delay-measurement study of the entire responsive IPv4 address space. We find that about 247K (17%) out of 1.41M blocks are not co-located, thus quantifying the error in the /24 block co-location assumption.

The work in this paper is by Manaf Gharaibeh, Han Zhang, Christos Papadopoulos (Colorado State University) and John Heidemann (USC/ISI).