Tag: ant

Talks at DNS-OARC 61

Post author By Wes Hardaker
Post date 2019-11-02

Wes Hardaker gave two presentations at DNS-OARC on November 1st, 2019. The first was a presentation about the previously announced “Cache me if you can” paper, which is on youtube, and the slides are available as well. The second talk presented Haoyu Jiang’s work during the summer of 2018 on analyzing DNS B-Root traffic during the 2018 DITL data for levels of traffic sent by the Chrome web browser, levels of traffic associated with different languages, and levels of traffic sent by different label lengths. It is available on youtube with the slides here.

Tags ant, b-root, DNS, DNS-OARC, isi, lacanic, talks, usc

Announcements

reblogging: the diurnal Internet and DNS backscatter

Post author By johnh
Post date 2019-09-19

We are happy to share that two of our older topics have appeared more recently in other venues.

Our animations of the diurnal Internet, originally seen in our 2014 ACM IMC paper and our blog posts, was noticed by Gerald Smith who used it to start a discussion with seventh-grade classes in Mahe, India and (I think) Indiana, USA as part of his Fullbright work. It’s great to see research work that useful to middle-schoolers!

Kensuke Fukuda recently posted about our work on identifying IPv6 scanning with DNS backscatter at the APNIC blog. This work was originally published at the 2018 ACM IMC and posted in our blog. It’s great to see that work get out to a new audience.

Tags animations, ant, apnic, backscatter, blog, diurnal, impact, Internet address usage, Internet Measurement Conference, isi, k12, lacanic, nii, outage detection, outreach, papers, security, usc, visualization

Papers Publications

new paper “Precise Detection of Content Reuse in the Web” to appear in ACM SIGCOMM Computer Communication Review

Post author By calvin
Post date 2019-05-22

We have published a new paper “Precise Detection of Content Reuse in the Web” by Calvin Ardi and John Heidemann, in the ACM SIGCOMM Computer Communication Review (Volume 49 Issue 2, April 2019) newsletter.

From the abstract:

With vast amount of content online, it is not surprising that unscrupulous entities “borrow” from the web to provide content for advertisements, link farms, and spam. Our insight is that cryptographic hashing and fingerprinting can efficiently identify content reuse for web-size corpora. We develop two related algorithms, one to automatically discover previously unknown duplicate content in the web, and the second to precisely detect copies of discovered or manually identified content. We show that bad neighborhoods, clusters of pages where copied content is frequent, help identify copying in the web. We verify our algorithm and its choices with controlled experiments over three web datasets: Common Crawl (2009/10), GeoCities (1990s–2000s), and a phishing corpus (2014). We show that our use of cryptographic hashing is much more precise than alternatives such as locality-sensitive hashing, avoiding the thousands of false-positives that would otherwise occur. We apply our approach in three systems: discovering and detecting duplicated content in the web, searching explicitly for copies of Wikipedia in the web, and detecting phishing sites in a web browser. We show that general copying in the web is often benign (for example, templates), but 6–11% are commercial or possibly commercial. Most copies of Wikipedia (86%) are commercialized (link farming or advertisements). For phishing, we focus on PayPal, detecting 59% of PayPal-phish even without taking on intentional cloaking.

Tags acm sigcomm ccr, ant, ccr, datasets, gawseed, hashing, isi, lacanic, measurement, newsletter, papers, phishing, security, usc, web, www

Announcements Projects

new project “Plannning for Anycast as Anti-DDoS” (PAADDoS)

Post author By johnh
Post date 2018-12-12

We are happy to announce a new project Plannning for Anycast as Anti-DDoS (PAADDoS).

The PAADDoS project’s goal is to defend against large-scale DDoS attacks by making anycast-based capacity more effective than it is today.

We will work toward this goal by (1) developing tools to map anycast catchments and baseline load, (2) develop methods to plan changes and their effects on catchments, (3) develop tools to estimate attack load and assist anycast reconfiguration during an attack. and (4) evaluate and integration of these tools with traditional DoS defenses.

We expect these innovations to improve service resilience in the face of DDoS attacks. Our tools will improve anycast agility during an attack, allowing capacity to be used effectively.

PAADDoS is a joint effort of the ANT Lab involving USC/ISI (PI: John Heidemann) and the Design and Analysis of Communication Systems group at the University of Twente (PI: Aiko Pras).

PAADDoS is supported by the DHS HSARPA Cyber Security Division via contract number HSHQDC-17-R-B0004-TTA.02-0006-I, and by NWO.

Tags ant, anycast, dhs, isi, nwo, paaddos, project, usc, utwente

Publications Technical Report

new technical report “Plumb: Efficient Processing of Multi-Users Pipelines (Extended)”

Post author By aqadeer
Post date 2018-10-03

We released a new technical report “Plumb: Efficient Processing of Multi-Users Pipelines (Extended)”, by Abdul Qadeer and John Heidemann, as ISI-TR-727. It is available at https://www.isi.edu/publications/trpublic/pdfs/isi-tr-727.pdf

From the abstract:

Services such as DNS and websites often produce streams of data that are consumed by analytics pipelines operated by multiple teams. Often this data is processed in large chunks (megabytes) to allow analysis of a block of time or to amortize costs. Such pipelines pose two problems: first, duplication of computation and storage may occur when parts of the pipeline are operated by different groups. Second, processing can be lumpy, with structural lumpiness occurring when different stages need different amounts of resources, and data lumpiness occurring when a block of input requires increased resources. Duplication and structural lumpiness both can result in inefficient processing. Data lumpiness can cause pipeline failure or deadlock, for example if differences in DDoS traffic compared to normal can require 6× CPU. We propose Plumb, a framework to abstract file processing for a multi-stage pipeline. Plumb integrates pipelines contributed by multiple users, detecting and eliminating duplication of computation and intermediate storage. It tracks and adjusts computation of each stage, accommodating both structural and data lumpiness. We exercise Plumb with the processing pipeline for B-Root DNS traffic, where it will replace a hand-tuned system to provide one third the original latency by utilizing 22% fewer CPU and will address limitations that occur as multiple users process data and when DDoS traffic causes huge shifts in performance.

Tags ant, bigdata, block-stream processing, isi, lacanic, retrofuturebridge, software, streaming, tech report, usc

Papers Publications

New workshop paper “IP-Based IoT Device Detection”

Post author By hangguo
Post date 2018-06-14

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.

Tags ant, datasets, impact, iot, iotsp, isi, lacanic, measurement systems, network datasets, network traffic, papers, retrofuturebridge, security, usc, workshop

Papers Publications

new workshop paper “BotDigger: Detecting DGA Bots in a Single Network” in TMA 2016

Post author By Han
Post date 2016-04-18

The paper “BotDigger: Detecting DGA Bots in a Single Network” has appeared at the TMA Workshop on April 8, 2016 in Louvain La Neuve, Belgium (available at http://www.cs.colostate.edu/~hanzhang/papers/BotDigger-TMA16.pdf).

The code of BotDigger is available on GitHub at: https://github.com/hanzhang0116/BotDigger

From the abstract:

To improve the resiliency of communication between bots and C&C servers, bot masters began utilizing Domain Generation Algorithms (DGA) in recent years. Many systems have been introduced to detect DGA-based botnets. However, they suffer from several limitations, such as requiring DNS traffic collected across many networks, the presence of multiple bots from the same botnet, and so forth. These limitations make it very hard to detect individual bots when using traffic collected from a single network. In this paper, we introduce BotDigger, a system that detects DGA-based bots using DNS traffic without a priori knowledge of the domain generation algorithm. BotDigger utilizes a chain of evidence, including quantity, temporal and linguistic evidence to detect an individual bot by only monitoring traffic at the DNS servers of a single network. We evaluate BotDigger’s performance using traces from two DGA-based botnets: Kraken and Conflicker. Our results show that BotDigger detects all the Kraken bots and 99.8% of Conficker bots. A one-week DNS trace captured from our university and three traces collected from our research lab are used to evaluate false positives. The results show that the false positive rates are 0.05% and 0.39% for these two groups of background traces, respectively.

The work in this paper is by Han Zhang, Manaf Gharaibeh, Spiros Thanasoulas, and Christos Papadopoulos (Colorado State University).

Tags algorithms, ant, csu, DNS, lacrend, lander, measurement systems, network traffic, papers, retro-future, security, software

Publications Technical Report

new technical report “BotDigger: Detecting DGA Bots in a Single Network”

Post author By Han
Post date 2016-02-01

We have released a new technical report “BotDigger: Detecting DGA Bots in a Single Network”, CS-16-101, available at http://www.cs.colostate.edu/~hanzhang/papers/BotDigger-techReport.pdf

The code of BotDigger is available on GitHub at: https://github.com/hanzhang0116/BotDigger

From the abstract:

To improve the resiliency of communication between bots and C&C servers, bot masters began utilizing Domain Generation Algorithms (DGA) in recent years. Many systems have been introduced to detect DGA-based botnets. However, they suffer from several limitations, such as requiring DNS traffic collected across many networks, the presence of multiple bots from the same botnet, and so forth. These limitations make it very hard to detect individual bots when using traffic collected from a single network. In this paper, we introduce BotDigger, a system that detects DGA-based bots using DNS traffic without a priori knowledge of the domain generation algorithm. BotDigger utilizes a chain of evidence, including quantity, temporal and linguistic evidence
to detect an individual bot by only monitoring traffic at the DNS servers of a single network. We evaluate BotDigger’s performance using traces from two DGA-based botnets: Kraken and Conflicker. Our results show that BotDigger detects all the Kraken bots and 99.8% of Conficker bots. A one-week DNS trace captured from our university and three traces collected from our research lab are used to evaluate false positives. The results show that the false positive rates are 0.05% and 0.39% for these two groups of background traces, respectively.

This work is by Han Zhang, Manaf Gharaibeh, Spiros Thanasoulas and Christos Papadopoulos (Colorado State University).

Tags algorithms, ant, csu, DNS, lacrend, lander, measurement systems, network traffic, papers, retro-future, security, software, tech report