Categories
Publications Technical Report

new technical report “Detecting IoT Devices in the Internet (Extended)”

We have released a new technical report “Detecting IoT Devices in the Internet (Extended)” as ISI-TR-726.

ISP-Level Deployment for  26 IoT Device Types. From Figure 2 of [Guo18c].
From the abstract of our technical report:

Distributed Denial-of-Service (DDoS) attacks launched from compromised Internet-of-Things (IoT) devices have shown how vulnerable the Internet is to large-scale DDoS attacks. To understand the risks of these attacks requires learning about these IoT devices: where are they? how many are there? how are they changing? This paper describes three new methods to find IoT devices on the Internet: server IP addresses in traffic, server names in DNS queries, and manufacturer information in TLS certificates. Our primary methods (IP addresses and DNS names) use knowledge of servers run by the manufacturers of these devices. We have developed these approaches with 10 device models from 7 vendors. Our third method uses TLS certificates obtained by active scanning. We have applied our algorithms to a number of observations. Our IP-based algorithms see at least 35 IoT devices on a college campus, and 122 IoT devices in customers of a regional IXP. We apply our DNSbased algorithm to traffic from 5 root DNS servers from 2013 to 2018, finding huge growth (about 7×) in ISPlevel deployment of 26 device types. DNS also shows similar growth in IoT deployment in residential households from 2013 to 2017. Our certificate-based algorithm finds 254k IP cameras and network video recorders from 199 countries around the world.

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 technical report is joint work of Hang Guo and  John Heidemann from USC/ISI.

Categories
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.

Categories
Publications Technical Report

new technical report “When the Dike Breaks: Dissecting DNS Defenses During DDoS (extended)”

We released a new technical report “When the Dike Breaks: Dissecting DNS Defenses During DDoS (extended)”, ISI-TR-725, available at https://www.isi.edu/~johnh/PAPERS/Moura18a.pdf.

Moura18a Figure 6a, Answers received during a DDoS attack causing 100% packet loss with pre-loaded caches.

From the abstract:

The Internet’s Domain Name System (DNS) is a frequent target of Distributed Denial-of-Service (DDoS) attacks, but such attacks have had very different outcomes—some attacks have disabled major public websites, while the external effects of other attacks have been minimal. While on one hand the DNS protocol is a relatively simple, the system has many moving parts, with multiple levels of caching and retries and replicated servers. This paper uses controlled experiments to examine how these mechanisms affect DNS resilience and latency, exploring both the client side’s DNS user experience, and server-side traffic. We find that, for about about 30% of clients, caching is not effective. However, when caches are full they allow about half of clients to ride out server outages, and caching and retries allow up to half of the clients to tolerate DDoS attacks that result in 90% query loss, and almost all clients to tolerate attacks resulting in 50% packet loss. The cost of such attacks to clients are greater median latency. For servers, retries during DDoS attacks increase normal traffic up to 8x. Our findings about caching and retries can explain why some real-world DDoS cause service outages for users while other large attacks have minimal visible effects.

Datasets from this paper are available at no cost and are listed at https://ant.isi.edu/datasets/dns/#Moura18a_data.

 

Categories
Presentations

new talk “Internet Outages: Reliablity and Security” from U. of Oregon Cybersecurity Day 2018

John Heidemann gave the talk “Internet Outages: Reliablity and Security” at the University of Oregon Cybersecurity Day in Eugene, Oregon on April 23, 2018.  Slides are available at https://www.isi.edu/~johnh/PAPERS/Heidemann18e.pdf.

Network outages as a security problem.

From the abstract:

The Internet is central to our lives, but we know astoundingly little about it. Even though many businesses and individuals depend on it, how reliable is the Internet? Do policies and practices make it better in some places than others?

Since 2006, we have been studying the public face of the Internet to answer these questions. We take regular censuses, probing the entire IPv4 Internet address space. For more than two years we have been observing Internet reliability through active probing with Trinocular outage detection, revealing the effects of the Internet due to natural disasters like Hurricanes from Sandy to Harvey and Maria, configuration errors that sometimes affect millions of customers, and political events where governments have intervened in Internet operation. This talk will describe how it is possible to observe Internet outages today and what they are beginning to say about the Internet and about the physical world.

This talk builds on research over the last decade in IPv4 censuses and outage detection and includes the work of many of my collaborators.

Data from this talk is all available; see links on the last slide.

Categories
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.

Categories
Announcements Projects

new project LACANIC

We are happy to announce a new project, LACANIC, the Los Angeles/Colorado Application and Network Information Community.

The LACANIC project’s goal is to develop datasets to improve Internet security and readability. We distribute these datasets through the DHS IMPACT program.

As part of this work we:

  • provide regular data collection to collect long-term, longitudinal data
  • curate datasets for special events
  • build websites and portals to help make data accessible to casual users
  • develop new measurement approaches

We provide several types of datasets:

  • anonymized packet headers and network flow data, often to document events like distributed denial-of-service (DDoS) attacks and regular traffic
  • Internet censuses and surveys for IPv4 to document address usage
  • Internet hitlists and histories, derived from IPv4 censuses, to support other topology studies
  • application data, like DNS and Internet-of-Things mapping, to document regular traffic and DDoS events
  • and we are developing other datasets

LACANIC allows us to continue some of the data collection we were doing as part of the LACREND project, as well as develop new methods and ways of sharing the data.

LACANIC is a joint effort of the ANT Lab involving USC/ISI (PI: John Heidemann) and Colorado State University (PI: Christos Papadopoulos).

We thank DHS’s Cyber Security Division for their continued support!

 

Categories
Papers Publications

new conference paper “Do You See Me Now? Sparsity in Passive Observations of Address Liveness” in TMA 2017

The paper “Do You See Me Now? Sparsity in Passive Observations of Address Liveness” will appear in the 2017 Conference on Network Traffic Measurement and Analyais (TMA) July 21-23, 2017 in Dublin, Ireland.   The datasets from the paper that we can make public will be at https://ant.isi.edu/datasets/sparsity/.

Visibility of addresses and blocks from possible /24 virtual monitors (Figure 2 from [Mirkovic17a])
From the abstract of the paper:

Accurate information about address and block usage in the Internet has many applications in planning address allocation, topology studies, and simulations. Prior studies used active probing, sometimes augmented with passive observation, to study macroscopic phenomena, such as the overall usage of the IPv4 address space. This paper instead studies the completeness of passive sources: how well they can observe microscopic phenomena such as address usage within a given network. We define sparsity as the limitation of a given monitor to see a target, and we quantify the effects of interest, temporal, and coverage sparsity. To study sparsity, we introduce inverted analysis, a novel approach that uses complete passive observations of a few end networks (three campus networks in our case) to infer what of these networks would be seen by millions of virtual monitors near their traffic’s destinations. Unsurprisingly, we find that monitors near popular content see many more targets and that visibility is strongly influenced by bipartite traffic between clients and servers. We are the first to quantify these effects and show their implications for the study of Internet liveness from passive observations. We find that visibility is heavy-tailed, with only 0.5% monitors seeing more than 10\% of our targets’ addresses, and is most affected by interest sparsity over temporal and coverage sparsity. Visibility is also strongly bipartite. Monitors of a different class than a target (e.g., a server monitor observing a client target) outperform monitors of the same class as a target in 82-99% of cases in our datasets. Finally, we find that adding active probing to passive observations greatly improves visibility of both server and client target addresses, but is not critical for visibility of target blocks. Our findings are valuable to understand limitations of existing measurement studies, and to develop methods to maximize microscopic completeness in future studies.

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.

Categories
Presentations

new talk “Distributed Denial-of-Service: What Datasets Can Help?” at ACSAC 2016

John Heidemann gave the talk “Distributed Denial-of-Service: What Datasets Can Help?” at ACSAC 2016 in Universal City, California, USA on December 7, 2016.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann16d.pdf.

heidemann16d_iconFrom the abstract:

Distributed Denial-of-Service attacks are continuing threat to the Internet. Meeting this threat requires new approaches that will emerge from new research, but new research requires the support of dataset and experimental methods. This talk describes four different aspects of research on DDoS, privacy and security, and the datasets that have generated to support that research. Areas we consider are detecting low rate DDoS attacks, understanding the effects of DDoS on DNS infrastructure, evolving the DNS protocol to prevent DDoS and improve privacy, and ideas about experimental testbeds to evaluate new ideas in DDoS defense for DNS. Datasets described in this talk are available at no cost from the author and through the IMPACT Program.

This talk is based on the work with many prior collaborators: Terry Benzel, Wes Hardaker, Christian Hessleman, Zi Hu, Allison Mainkin, Urbashi Mitra, Giovane Moura, Moritz Müller, Ricardo de O. Schmidt, Nikita Somaiya, Gautam Thatte, Wouter de Vries, Lan Wei, Duane Wessels, Liang Zhu.

Datasets from the paper are available at https://ant.isi.edu/datasets/ and at https://impactcybertrust.org.

Categories
Presentations

new talk “Anycast vs. DDoS: Evaluating Nov. 30” at DNS-OARC

John Heidemann gave the talk “Anycast vs. DDoS: Evaluating Nov. 30” at DNS-OARC in Dallas, Texas, USA on October 16, 2016.  Slides are available at http://www.isi.edu/~johnh/PAPERS/Heidemann16c.pdf.

 

Possible outcomes of anycast under stress, a slide from a talk about the Nov. 30, 2015 Root DNS event.
Possible outcomes of anycast under stress, a slide from a talk about the Nov. 30, 2015 Root DNS event.

From the abstract:

Distributed Denial-of-Service (DDoS) attacks continue to be a major threat in the Internet today. DDoS attacks overwhelm target services with requests or other “bogus” traffic, causing requests from legitimate users to be shut out. A common defense against DDoS is to replicate the service in multiple physical locations or sites. If all sites announce a common IP address, BGP will associate users around the Internet with a nearby site, defining the catchment of that site. Anycast adds resilience against DDoS both by increasing capacity to the aggregate of many sites, and allowing each catchment to contain attack traffic leaving other sites unaffected. IP anycast is widely used for commercial CDNs and essential infrastructure such as DNS, but there is little evaluation of anycast under stress.

This talk will provide a first evaluation of several anycast services under stress with public data. Our subject is the Internet’s Root Domain Name Service, made up of 13 independently designed services (“letters”, 11 with IP anycast) running at more than 500 sites. Many of these services were stressed by sustained traffic at 100x normal load on Nov. 30 and Dec. 1, 2015. We use public data for most of our analysis to examine how different services respond to the these events. In our analysis we identify two policies by operators: (1) sites may absorb attack traffic, containing the damage but reducing service to some users, or (2) they may withdraw routes to shift both legitimate and bogus traffic to other sites. We study how these deployment policies result in different levels of service to different users, during and immediately after the attacks.

We also show evidence of collateral damage on other services located near the attack targets. The work is based on analysis of DNS response from around 9000 RIPE Atlas vantage points (or “probes”), agumented by RSSAC-002 reports from 5 root letters and BGP data from BGPmon. We examine DNS performance for each Root Letter, for anycast sites inside specific letters, and for specific servers at one site.

This talk is based on the work in the paper “Anycast vs. DDoS: Evaluating the November 2015 Root DNS Event” at appear at  IMC 2016, by Giovane C. M. Moura, Ricardo de O. Schmidt, John Heidemann, Wouter B. de Vries, Moritz Müller,  Lan Wei, and Christian Hesselman.

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