June 2018 – ANT Research News

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.

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.

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.