Tag: algorithms

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new conference paper “Detecting Malicious Activity with DNS Backscatter”

The paper “Detecting Malicious Activity with DNS Backscatter” will appear at the ACM Internet Measurements Conference in October 2015 in Tokyo, Japan.  A copy is available at http://www.isi.edu/~johnh/PAPERS/Fukuda15a.pdf).

How newtork activity generates DNS backscatter that is visible at authority servers. (Figure 1 from [Fukuda15a]).
How newtork activity generates DNS backscatter that is visible at authority servers. (Figure 1 from [Fukuda15a]).
From the abstract:

Network-wide activity is when one computer (the originator) touches many others (the targets). Motives for activity may be benign (mailing lists, CDNs, and research scanning), malicious (spammers and scanners for security vulnerabilities), or perhaps indeterminate (ad trackers). Knowledge of malicious activity may help anticipate attacks, and understanding benign activity may set a baseline or characterize growth. This paper identifies DNS backscatter as a new source of information about network-wide activity. Backscatter is the reverse DNS queries caused when targets or middleboxes automatically look up the domain name of the originator. Queries are visible to the authoritative DNS servers that handle reverse DNS. While the fraction of backscatter they see depends on the server’s location in the DNS hierarchy, we show that activity that touches many targets appear even in sampled observations. We use information about the queriers to classify originator activity using machine-learning. Our algorithm has reasonable precision (70-80%) as shown by data from three different organizations operating DNS servers at the root or country-level. Using this technique we examine nine months of activity from one authority to identify trends in scanning, identifying bursts corresponding to Heartbleed and broad and continuous scanning of ssh.

The work in this paper is by Kensuke Fukuda (NII/Sokendai) and John Heidemann (USC/ISI) and was begun when Fukuda-san was a visiting scholar at USC/ISI.  Kensuke Fukuda’s work in this paper is partially funded by Young Researcher Overseas Visit Program by Sokendai, JSPS Kakenhi, and the Strategic International Collaborative R&D Promotion Project of the Ministry of Internal Affairs and Communication in Japan, and by the European Union Seventh Framework Programme.  John Heidemann’s work is partially supported by US DHS S&T, Cyber Security division.

Some of the datasets in this paper are available to researchers, either from the authors or through DNS-OARC.  We list DNS backscatter datasets and methods to obtain them at https://ant.isi.edu/datasets/dns_backscatter/index.html.

 

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new conference paper “Trinocular: Understanding Internet Reliability Through Adaptive Probing” in SIGCOMM 2013

The paper “Trinocular: Understanding Internet Reliability Through Adaptive Probing” was accepted by SIGCOMM’13 in Hong Kong, China (available at http://www.isi.edu/~johnh/PAPERS/Quan13c with cite and pdf, or direct pdf).

100% detection of outages one round or longer
100% detection of outages one round or longer (figure 3 from the paper)

From the abstract:

Natural and human factors cause Internet outages—from big events like Hurricane Sandy in 2012 and the Egyptian Internet shutdown in Jan. 2011 to small outages every day that go unpublicized. We describe Trinocular, an outage detection system that uses active probing to understand reliability of edge networks. Trinocular is principled: deriving a simple model of the Internet that captures the information pertinent to outages, and populating that model through long-term data, and learning current network state through ICMP probes. It is parsimonious, using Bayesian inference to determine how many probes are needed. On average, each Trinocular instance sends fewer than 20 probes per hour to each /24 network block under study, increasing Internet “background radiation” by less than 0.7%. Trinocular is also predictable and precise: we provide known precision in outage timing and duration. Probing in rounds of 11 minutes, we detect 100% of outages one round or longer, and estimate outage duration within one-half round. Since we require little traffic, a single machine can track 3.4M /24 IPv4 blocks, all of the Internet currently suitable for analysis. We show that our approach is significantly more accurate than the best current methods, with about one-third fewer false conclusions, and about 30% greater coverage at constant accuracy. We validate our approach using controlled experiments, use Trinocular to analyze two days of Internet outages observed from three sites, and re-analyze three years of existing data to develop trends for the Internet.

Citation: Lin Quan, John Heidemann and Yuri Pradkin. Trinocular: Understanding Internet Reliability Through Adaptive Probing. In Proceedings of the ACM SIGCOMM Conference. Hong Kong, China, ACM. August, 2013. <http://www.isi.edu/~johnh/PAPERS/Quan13c>.

Datasets (listed here) used in generating this paper are available or will be available before the conference presentation.

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New conference paper “Towards Geolocation of Millions of IP Addresses” at IMC 2012

The paper “Towards Geolocation of Millions of IP Addresses” was accepted by IMC 2012 in Boston, MA (available at http://www.isi.edu/~johnh/PAPERS/Hu12a.html).

From the abstract:

Previous measurement-based IP geolocation algorithms have focused on accuracy, studying a few targets with increasingly sophisticated algorithms taking measurements from tens of vantage points (VPs). In this paper, we study how to scale up existing measurement-based geolocation algorithms like Shortest Ping and CBG to cover the whole Internet. We show that with many vantage points, VP proximity to the target is the most important factor affecting accuracy. This observation suggests our new algorithm that selects the best few VPs for each target from many candidates. This approach addresses the main bottleneck to geolocation scalability: minimizing traffic into each target (and also out of each VP) while maintaining accuracy. Using this approach we have currently geolocated about 35% of the allocated, unicast, IPv4 address-space (about 85% of the addresses in the Internet that can be directly geolocated). We visualize our geolocation results on a web-based address-space browser.

Citation: Zi Hu and John Heidemann and Yuri Pradkin. Towards Geolocation of Millions of IP Addresses. In Proceedings of the ACM Internet Measurement Conference, p. to appear. Boston, MA, USA, ACM. 2012. <http://www.isi.edu/~johnh/PAPERS/Hu12a.html>

 

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new conference paper “Towards an AS-to-Organization Map” to appear at IMC

The paper “Towards an AS-to-Organization Map” was accepted by IMC’10 in Melbourne, Australia (available at http://www.isi.edu/~johnh/PAPERS/Cai10c.html).

From the abstract:

An understanding of Internet topology is central to answer various questions ranging from network resilience to peer selection or data center location. While much of prior work has examined AS-level connectivity, meaningful and relevant results from such an abstract view of Internet topology have been limited. For one, semantically, AS relationships capture business relationships and not physical connectivity. Additionally, many organizations often use multiple ASes, either to implement different routing policies, or as legacies from mergers and acquisitions. In this paper, we move beyond the traditional AS graph view of the Internet to define the problem of AS-to-organization mapping. We describe our initial steps at automating the capture of the rich semantics inherent in the AS-level ecosystem where routing and connectivity intersect with organizations. We discuss preliminary methods that identify multi-AS organizations from WHOIS data and illustrate the challenges posed by the quality of the available data and the complexity of real-world organizational relationships.

Citation: Xue Cai, John Heidemann, Balachander Krishnamurthy, and Walter Willinger. Towards an AS-to-Organization Map. In Proceedings of the ACM Internet Measurement Conference, p. to appear. Melbourne, Australia, ACM. November, 2010.