Tag: papers

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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).

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Papers Publications

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

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 mBotDiggerOverviewake 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).

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Papers Publications

new workshop paper “AuntieTuna: Personalized Content-based Phishing Detection” in USEC 2016

The paper “AuntieTuna: Personalized Content-based Phishing Detection” will appear at the NDSS Usable Security Workshop on February 21, 2016 in San Diego, CA, USA (available at https://www.isi.edu/~calvin/papers/Ardi16a.pdf).

From the abstract:

Implementation diagram of the AuntieTuna anti-phishing plugin.Phishing sites masquerade as copies of legitimate sites (“targets”) to fool people into sharing sensitive information that can then be used for fraud. Current phishing defenses can be ineffective, with training ignored, blacklists of discovered, bad sites too slow to pick up new threats, and whitelists of known-good sites too limiting. We have developed a new technique that automatically builds personalized lists of target sites (candidates that may be copied by phish) and then tests sites as a user browses them. Our approach uses cryptographic hashing of each page’s rendered Document Object Model (DOM), providing a zero false positive rate and identifying more than half of detectable phish in a controlled study. Since each user develops a customized list of target sites, our approach presents a diverse defense against phishers. We have prototyped our approach as a Chrome browser plugin called AuntieTuna, emphasizing usability through automated and simple manual addition of target sites and clean reports of potential phish that include context about the targeted site. AuntieTuna does not slow web browsing time and presents alerts on phishing pages before users can divulge information. Our plugin is open-source and has been in use by a few users for months.

The work in this paper is by Calvin Ardi (USC/ISI) and John Heidemann (USC/ISI).

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Publications Technical Report

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

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. BotDiggerOverviewThese 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).

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Papers Publications

new conference paper “Measuring the Latency and Pervasiveness of TLS Certificate Revocation” in PAM 2016

The paper “Measuring the Latency and Pervasiveness of TLS Certificate Revocation” will appear at Passive and Active Measurements Conference in March 2016 in Heraklion, Crete, Greece  (available at http://www.isi.edu/~liangzhu/papers/Zhu16a.pdf)

From the abstract:

Today, Transport-Layer Security (TLS) is the bedrock of Internet security for the web and web-derived applications. TLS depends on the X.509 Public Key Infrastructure (PKI) to authenticate endpoint
identity. An essential part of a PKI is the ability to quickly revoke certificates, for example, after a key compromise. Today the Online Certificate Status Protocol (OCSP) is the most common way to quickly distribute revocation information. However, prior and current concerns about OCSP latency and privacy raise questions about its use. We examine OCSP using passive network monitoring of live traffic at the Internet uplink of a large research university and verify the results using active scans. Our measurements show that the median latency of OCSP queries is quite good: only 20 ms today, much less than the 291 ms observed in 2012. This improvement is because content delivery networks (CDNs) serve most OCSP traffic today; our measurements show 94% of queries are served by CDNs. We also show that OCSP use is ubiquitous today: it is used by all popular web browsers, as well as important non-web applications such as MS-Windows code signing.

The work in the paper is by Liang Zhu (USC/ISI), Johanna Amann (ICSI) and John Heidemann (USC/ISI). The active probe dataset in this paper is available upon request.

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Publications Technical Report

new technical report “Assessing Co-Locality of IP Blocks”

We have released a new technical report “Assessing Co-Locality of IP Blocks”, CSU TR15-103, available at http://www.cs.colostate.edu/TechReports/Reports/2015/tr15-103.pdf.

From the abstract:

isi_all_blocks_clustersCount_CDF
CDF of number of clusters per block, suggesting the number of potential multi-location blocks. (Figure 2 from [Gharaibeh15a].)

Many IP Geolocation services and applications assume that all IP addresses with the same /24 IPv4 prefix (a /24 block) are in the same location. For blocks that contain addresses in very different locations (such blocks identifying network backbones), this assumption can result in large geolocation error. This paper evaluates this assumption using a large dataset of 1.41M /24 blocks extracted from a delay measurements dataset for the entire
responsive IPv4 address space. We use hierarchal clustering to find clusters of IP addresses with similar observed delay measurements within /24 blocks. Blocks with multiple clusters often span different geographic locations. We evaluate this claim against two ground-truth datasets, confirming that 93% of identified multi-cluster blocks are true positives with multiple locations, while only 13% of blocks identified as single-cluster appear to be multi-location in ground truth. Applying the clustering process to the whole dataset suggests that about 17% (247K) of blocks are likely multi-location.

This work is by Manaf Gharaibeh, Han Zhang, Christos Papadopoulos (Colorado State University), and John Heidemann (USC/ISI). The datasets used in this work are new analysis of an existing geolocation dataset as collected by Hu et al. (http://www.isi.edu/~johnh/PAPERS/Hu12a.pdf).  These source datasets are available upon request from http://www.predict.org and via our website, and we expect trial datasets in our new work to also be available there and through PREDICT by the end of 2015.

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Papers Publications

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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Papers Publications

new conference paper “Connection-Oriented DNS to Improve Privacy and Security” in Oakland 2015

The paper “Connection-Oriented DNS to Improve Privacy and Security” will appear at the 36th IEEE Symposium on Security and Privacy in May 2015 in San Jose, CA, USA  (available at http://www.isi.edu/~liangzhu/papers/Zhu15b.pdf)

From the abstract:end_to_end_model_n_7

The Domain Name System (DNS) seems ideal for connectionless UDP, yet this choice results in challenges of eavesdropping that compromises privacy, source-address spoofing that simplifies denial-of-service (DoS) attacks on the server and third parties, injection attacks that exploit fragmentation, and reply-size limits that constrain key sizes and policy choices. We propose T-DNS to address these problems. It uses TCP to smoothly support large payloads and to mitigate spoofing and amplification for DoS. T-DNS uses transport-layer security (TLS) to provide privacy from users to their DNS resolvers and optionally to authoritative servers. TCP and TLS are hardly novel, and expectations about DNS suggest connections will balloon client latency and overwhelm server with state. Our contribution is to show that T-DNS significantly improves security and privacy: TCP prevents denial-of-service (DoS) amplification against others, reduces the effects of DoS on the server, and simplifies policy choices about key size. TLS protects against eavesdroppers to the recursive resolver. Our second contribution is to show that with careful implementation choices, these benefits come at only modest cost: end-to-end latency from TLS to the recursive resolver is only about 9% slower when UDP is used to the authoritative server, and 22% slower with TCP to the authoritative. With diverse traces we show that connection reuse can be frequent (60–95% for stub and recursive resolvers, although half that for authoritative servers), and after connection establishment, experiments show that TCP and TLS latency is equivalent to UDP. With conservative timeouts (20 s at authoritative servers and 60 s elsewhere) and estimated per-connection memory, we show that server memory requirements match current hardware: a large recursive resolver may have 24k active connections requiring about 3.6 GB additional RAM. Good performance requires key design and implementation decisions we identify: query pipelining, out-of-order responses, TCP fast-open and TLS connection resumption, and plausible timeouts.

The work in the paper is by Liang Zhu, Zi Hu and John Heidemann (USC/ISI), Duane Wessels and Allison Mankin (both of Verisign Labs), and Nikita Somaiya (USC/ISI).  Earlier versions of this paper were released as ISI-TR-688 and ISI-TR-693; this paper adds results and supercedes that work.

The data in this paper is available to researchers at no cost on request. Please see T-DNS-experiments-20140324 at dataset page.

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Papers Publications

new workshop paper “Privacy Principles for Sharing Cyber Security Data” in IWPE 15

The paper “Privacy Principles for Sharing Cyber Security Data” (available at https://www.isi.edu/~calvin/papers/Fisk15a.pdf) will appear at the International Workshop on Privacy Engineering (co-located with IEEE Symposium on Security and Privacy) on May 21, 2015 in San Jose, California.

From the abstract:

Sharing cyber security data across organizational boundaries brings both privacy risks in the exposure of personal information and data, and organizational risk in disclosing internal information. These risks occur as information leaks in network traffic or logs, and also in queries made across organizations. They are also complicated by the trade-offs in privacy preservation and utility present in anonymization to manage disclosure. In this paper, we define three principles that guide sharing security information across organizations: Least Disclosure, Qualitative Evaluation, and Forward Progress. We then discuss engineering approaches that apply these principles to a distributed security system. Application of these principles can reduce the risk of data exposure and help manage trust requirements for data sharing, helping to meet our goal of balancing privacy, organizational risk, and the ability to better respond to security with shared information.

The work in the paper is by Gina Fisk (LANL), Calvin Ardi (USC/ISI), Neale Pickett (LANL), John Heidemann (USC/ISI), Mike Fisk (LANL), and Christos Papadopoulos (Colorado State). This work is supported by DHS S&T, Cyber Security division.

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Papers Publications

new workshop paper “Assessing Affinity Between Users and CDN Sites” in TMA 2015

The paper “Assessing Affinity Between Users and CDN Sites” (available at http://www.isi.edu/~xunfan/research/Fan15a.pdf) will appear at the Traffic Monitoring and Analysis Workshop in April 2015 in Barcelona, Spain.

From the abstract:

count_cid_per_clientLarge web services employ CDNs to improve user performance. CDNs improve performance by serving users from nearby FrontEnd (FE) Clusters. They also spread users across FE Clusters when one is overloaded or unavailable and others have unused capacity. Our paper is the first to study the dynamics of the user-to-FE Cluster mapping for Google and Akamai from a large range of client prefixes. We measure how 32,000 prefixes associate with FE Clusters in their CDNs every 15 minutes for more than a month. We study geographic and latency effects of mapping changes, showing that 50–70% of prefixes switch between FE Clusters that are very distant from each other (more than 1,000 km), and that these shifts sometimes (28–40% of the time) result in large latency shifts (100 ms or more). Most prefixes see large latencies only briefly, but a few (2–5%) see high latency much of the time. We also find that many prefixes are directed to several countries over the course of a month, complicating questions of jurisdiction.

Citation: Xun Fan, Ethan Katz-Bassett and John Heidemann.Assessing Affinity Between Users and CDN Sites. To appear in Traffic Monitoring and Analysis Workshop. Barcelona, Spain. April, 2015.

All data in this paper is available to researchers at no cost on request. Please see our CDN affinity dataset webpage.

This research is partially sponsored by the Department of Homeland Security (DHS) Science and Technology Directorate, HSARPA, Cyber Security Division, BAA 11-01-RIKA and Air Force Re-search Laboratory, Information Directorate under agreement number FA8750-12-2-0344, NSF CNS-1351100, and via SPAWAR Systems Center Pacific under Contract No. N66001-13-C-3001. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwith-standing any copyright notation thereon. The views contained herein are those of the authors and
do not necessarily represent those of DHS or the U.S. Government.