Network Working Group A. Mohaisen
Internet-Draft SUNY Buffalo
Intended status: Informational A. Mankin
Expires: April 20, 2016 Verisign Labs
October 18, 2015

Evaluation of Privacy for DNS Private Exchange
draft-am-dprive-eval-02

Abstract

The set of DNS requests that an individual makes can provide a monitor with a large amount of information about that individual. DNS Private Exchange (DPRIVE) aims to deprive this actor of this information. This document describes methods for measuring the performance of DNS privacy mechanisms, particularly it provides methods for measuring effectiveness in the face of pervasive monitoring as defined in RFC7258. The document includes example evaluations for common use cases.

Status of This Memo

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This Internet-Draft will expire on April 20, 2016.

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Table of Contents

1. Motivation

One of the IETF’s core views is that protocols should be designed to enable security and privacy while online [RFC3552]. In light of the recent reported pervasive monitoring efforts, another goal is to design protocols and mechanisms to make such monitoring expensive or infeasible to conduct. As detailed in the DPRIVE problem statement [RFC7626], DNS resolution is an important arena for pervasive monitoring, and in some cases may be used for breaching the privacy of individuals. The set of DNS requests that an individual makes can provide a large amount of information about that individual. In some specific use cases, the sets of DNS requests from a DNS recursive resolver or other entity may also provide revealing information. This document describes methods for measuring the performance of DNS privacy mechanisms; in particular, it provides methods for measuring effectiveness in the face of pervasive monitoring as defined in [RFC7258]. The document includes example evaluations for common use cases.

The privacy threats associated with DNS monitoring are not new, however they were made more obvious by the issue described in [RFC7258]. The DPRIVE working group was formed to respond and at this time has several DNS private exchange mechanisms in consideration, including [dns-over-tls], [confidential-dns], [phb-dnse], and [privatedns]. There is also related work in other working groups, including DNSOP: [qname-minimisation] and (potentially) DANE [ipseca]. The recently published RFC on opportunistic security [RFC7435] also has relevance to DNS private exchange.

Each effort related to DNS privacy mechanisms asserts some privacy assurances and operational relevance. Metrics for these privacy assurances are needed and are in reach based on existing techniques from the general field of privacy engineering. Systematic evaluation of DNS privacy mechanisms will enhance the likely operational effectiveness of DNS private exchange.

Evaluating an individual mechanism for DNS privacy could be accomplished on a one-off basis, presumably as Privacy Considerations within each specification, but this will not address as much variation of operational contexts nor will it cover using multiple mechanisms together (in composition). Section 2 of [RFC6973] discussed both benefits and risks of using multiple mechanisms.

Definitions required for evaluating the privacy of stand-alone and composed design are not limited to privacy notions, but also need to include the risk model and some information about relationships among the entities in a given system. A mechanism for providing privacy to withstand the power and capabilities of a passive pervasive monitor may not withstand a more powerful actor using active monitoring by plugging itself into the path of individuals’ DNS requests as a forwarder . Having some standard models, and understanding how applicable they are to various designs is a part of evaluating the privacy.

Sections 2 and 3 present privacy terminology and some assumptions. Sections 4 and 5 cover the system model or setup and the risk models of interest. In Section 6, we review a list of DNS privacy mechanisms, including some which are not in scope of the DPRIVE working group. Section 7 tackles how to evaluate privacy mechanisms, in the form of templates and outcomes. Given a specific risk model, the guarantees with respect to privacy of an individual or an item of interest are quantified.

2. Privacy Evaluation Definitions

This section provides definitions to be used for privacy evaluation of DNS. The verbatim source of most of those definitions is from [RFC6973], which are included as an aid in reasability. In some definitions, text is added to apply them to the DNS case. Also, a new section of terms has been added to include several important practical or conventional terms that were not included in [RFC6973] such as PII. For the terms from [RFC6973], we include their definitions rather than simply referencing them as an aid to readability.

2.1. Entities

2.2. Data and Analysis

We assume the following definitions related to data and analysis from [RFC4949]: attacker, correlation, fingerprint, fingerprinting, item of interest (IOI), personal data, interaction, traffic analysis, undetectability, and unlinkability. We augment some of those definitions later in this document.

from [RFC4949], we relax the definition of IOI to exclude "the fact that a communication interaction has taken place" as this does not suite the evaluated context of DNS.

2.3. Identifiability

We assume the following definitions related to identifiability from [RFC4949]: anonymity, anonymity set, anonymous, attribute, identity provider, personal name, and relying party.

The following definitions are modified for the context of this document from those defined in [RFC4949]

NOTE: Identifiability Definitions in [RFC6973] also include some material not included here because the distinctions are not major for DNS Private Exchange, such as real and official names, and variant forms of Pseudonymity in its informal definition.

2.4. Other Central Definitions and Formalizations

Central to the presentation of this document is the definition of personally identifiable information (PII), as well as other definitions that supplement the definitions listed earlier or modify them for the context of this document. In this section, we outline such definitions we further notes on their indications.

NOTE: the definition above indicates that PII can be used on its own or in context. In DNS privacy, the items without additional context include IP(v4 or v6) addresses, qname, qtype, timings of queries, etc. The additional context includes organization-level attributes, such as a network prefix that can be associated with an organization. The definition of PII is complementary to the definition of items of interest.

Often it is desirable to reference alternative identifiers known as pseudonyms. A pseudonym is a name assumed by an individual in some context, unrelated to the names or identifiers known by others in that context.

As an example, in the DNS context, a randomly generated pseudonym might identify a set of query data with a shared context, such as geographic origin. Such pseudonymity enables another entity interested in breaching the privacy to link multiple queries on a long-term basis. Pseudonyms are assumed long-lived and their uniqueness may be a goal. There are many findings that indicate that pseudonymity is weaker than anonymity.

Two items of interest are said to be unlinkable if there is a small chance (beta, close to 0 probability) that the monitor identifies them as associated, and they are linkable if there is a sufficiently large probability (referred to as alpha).

Informally, given two items of interest (user attributes, DNS queries, users, etc.), unlinkability is defined as the inability of the monitor to sufficiently determine whether those items are related to one another. In the context of DNS, this refers typically but not only to a monitor relating queries to the same individual.

Note that undetectability implies unlinkability. As explained below, a way of ensuring undetectability is to use encryption that is secure under known ciphertext attacks, or randomized encryption.

In theory, there are many ways of ensuring unobservability by fulfilling both requirements. For example, undetectability requires that no party that is not invovled in the resolution of a DNS query shall know that query has existed or not. A mechanism to ensure this function is encryption secure under known ciphertext attacks, or randomized encryption for all other than stub resolvers, and pseudonyms for the stub resolver. An alternative mechanism to provide the anonymity property would be the use of mix networks for routing DNS queries.

3. Assumptions about Quantification of Privacy

The quantification of privacy is connected with the privacy goals. Is the desired privacy property unlinkability only, or is it undetectability? Is pseudonymity a sufficient property? Parameters and entire privacy mechanism choices are affected by the choice of privacy goals.

While a binary measure of privacy is sometimes possible, that is, being able to say that the transaction is anonymous, in this document, we assume that the binary is not frequently obtainable, and therefore we focus on methods for continuous quantification. Both are relevant to DNS Private Exchange. Another way to state this is that the quantification could be exactly the probabilities 1 and 0, corresponding to the binary, but the methods prefer to provide continuous values instead.

Here is an example of continuous quantification, related to identifiability of an individual or item of interest based on observing queries.

4. System Model

A DNS client (a DNS stub resolver) may resolve a domain name or address into the corresponding DNS record by contacting the authoritative name server responsible for that domain name (or address) directly. However, to improve the operation of DNS resolution, and reduce the round trip time required for resolving an address, both caching and recursive resolution are implemented. Caching is implemented at an intermediary between the stub and the authoritative name server. In practice, many caching servers also implement the recursive logic of DNS resolution for finding the name server authoritative for a domain, and are thus called DNS recursive resolvers. Another type of entity, DNS forwarders (or proxies), acts as intermediaries between stub resolvers and recursive resolvers, and recursive resolvers and authoritative resolvers. The system model for DNS privacy evaluation includes the four entities quickly sketched here: stub resolvers, recursive resolvers, authoritative name servers, and forwarders.

4.1. DNS Resolvers (System Model)

4.2. System Setup - Putting It Together

Evaluating various privacy protection mechanisms in relation to monitors such as the pervasive monitors defined next requires understanding links in the system setup. We define the following links. In relation to [RFC7258] these are the attack surface where a monitor (eavesdropper) can collect sets of query information.

Rather than notating in system setup that an entity is compromised, this is covered in the monitor model in Section 6, which has system elements as parameters.

In the system setup, there is a possibility that S and R exist on a single machine. The concept of the Unlucky Few relates S and R in this case. A monitor can monitor R-A and find the query traffic of the initiator individual. The same concept applies in the case where a recursive is serving a relatively small number of individuals. The query traffic of a subject group or organization (c.f. Subject in the definitions) is obtained by the monitor who monitors this system's R-A.

Because R-A is not in the DPRIVE scope, it is for future work to examine the Unlucky Few circumstance fully. The general system setup is that PII, the individual’s private identifying information, is not sent on R-A and is not seen by authoritative name server.

There could be one or more proxies between the stub resolver and a recursive. From a functionality point of view they can all be consolidated into a single proxy without affecting the system view. However, the behavior of such proxies may affect the size and shape of the attack surface. However, we believe that an additional treatment is needed for this case and it is not included in the discussion.

We also do not include in discussion proxies that exist along R-A, between a recursive and an authoritative name server. We do so in respect for the DPRIVE charter's scope at this time. According to recent work at [openresolverproject.org], there may be multiple intermediaries with poorly defined behavior.

The system setup here leaves out other realistic considerations for simplicity, such as the impact of shared caches in DNS entities.

5. Risk Model

The Definitions section defines observer, attack and monitor, but not a Risk Model, which is needed to actually evaluate privacy.

For consistency, we note that the only difference between an attacker and an obeserver is that an attacker is an unauthorized observer with all the capabilities it may have. We also stress that for the context of DNS privacy, the term attacker may implicitly assume an intent. To that end, active and passive observers are collectively referred to as actors.

In this document we focus on two risk models, namely a pervasive monitor and a malicious monitor.

5.1. Risk Type-1 – Passive Pervasive Monitor

This risk corresponds to the passive pervasive monitoring model described in [RFC7258]. This model relies on monitoring capabilities to breach the privacy of individuals from the DNS traffic at scale without decimation. An actor causing this risk is capable of eavesdropping or observing traffic between two end points, including traffic between any of the pairs of entities described in section 2.1. Per [RFC7258], this type of actor has the ability to eavesdrop pervasively on many links at once, which is a powerful form of attack. Type-1 monitors are passive. They do not modify traffic or insert traffic.

5.2. Risk Type-2 – Active Monitor

This risk corresponds to an actor with the same types of capabilities of monitoring links. Additionally, this model can select links in order to target specific individuals. A Type-2 monitor for instance might put into place intermediaries in order to obtain traffic on specific links.

Note that we exclude malicious monitoring from this document since, by definition, a malicious actor has an intent associated with his actions.

5.3. Risks in the System Setup

To evaluate the privacy provided by a given mechanism or mechanisms in a particular system model, we characterize the risk using a template where parameters from the system model in which the risk actor (eavesdropper or observer as monitors) is located are used. The general template is: Risk(Type, [Entities], [Links]). For example, the template Risk(Type-2, R, S-R) passed as a parameter in the evaluation of a privacy mechanism indicates a Type-2 monitor that controls a recursive resolver and has the capability of eavesdropping on the link between the stub and recursive resolvers (S-R). Other risk templates include the appropriate parameterizations based on the above description of those monitors, including monitors that have the capabilities of monitoring multiple links and controlling multiple pieces of infrastructure.

6. Privacy Mechanisms

Various mechanisms for enhancing privacy in networks are applicable to DNS private exchange. Some mechanisms common to privacy research include mix networks, dummy traffic, and private information retrieval techniques. Applicable protocol mechanisms include encryption-based techniques - encrypting the channel carrying the queries using IPSEC [ipseca], TLS [dns-over-tls] or special-purpose encryption [confidential-dns]. [privatedns] includes special-purpose encryption but also depends on a trusted service broker.

7. Privacy Evaluation

Now we turn our attention to the evaluation of privacy mechanisms in a standard form, given the risk models and system definitions, for some of the example mechanisms.

An evaluation takes multiple parameters as input. The output of the evaluation template is based on the analysis of the individual algorithms, settings, and parameters passed to this evaluation mechanism.

Here is the top level interface of the evaluation template:

Eval(Privacy_Mechanism(params),
      System_Setting(params), 
      Risk_Model(params)
      )
 

The output of the function is a privacy guarantee for the given settings, expressed through defined properties such as unlinkability and unobservability, for the specified system and risk model.

7.1 Dummy Traffic Example

Eval(Dummy_Traffic (k=10, distribution=uniform), 
    System_Setting([S, P, R, A], [S-P, P-R, R-A]), 
    Risk_Model(Type-1A, S-R))
 

The dummy traffic mechanism is not presented as a practical mechanism, though there's no way to know if there are deployments of this type of mechanism. This example evaluation uses k=10 to indicate that for every one query initiated by an individual, ten queries that disguise the query of interest are selected randomly from a pool of queries. In the parameters passed in the evaluation function, we indicate that the privacy assurances of interest concern the S-R link, with a Passive Pervasive Monitor (Type-1A) risk.

Here is a template format for the example:

Eval(Dummy_Traffic (k=10, distribution=uniform), 
    System_Setting([S, P, R, A], [S-P, P-R, R-A]), 
      Risk_Model(Type-1A, S-R)) {
        Privacy_Mechanism{
            Mechanism_name = Dummy_Traffic  
            Parameters{
                Queries = 10
                Query_distribution = uniform
        }
        System_settings{
            Entities = S, P, R and A;
            Links = S-P, P-R, R-A
        }
        Risk_Model{
            Type = Type-1A
            Links = S-R
        }
        Privacy_guarantee = undetectability
        Privacy_measure = 1-(1/(queries+1)).

        Return Privacy_guarantee, Privacy_measure

}
 

Undetectability is provided with 0.91 probability (though we know there are other weaknesses for dummy traffic) If the threat model is replaced with Type-2, so that responses to arbitrary requests can be injected, and tracked, the undetectability probability is decreased.

7.2 Mix Network Example

Here is an input for a mix network privacy mechanism:

Eval(Mix (u=10, distribution=uniform), System_Setting(link=S-R), threat_Model(Type-1A))

This indicates that the monitor resides between the stub and resolver. While queries are not undetectable, two queries are not linkable to the same individual; the provided guarantee is unlinkability. For a given number of individuals in the mix network, indicated by the parameter u, assuming that at any time, traffic from these individuals is uniformly random, the probability that one query is comes from a given individual is (1/10 = 0.1). The probability that two queries are issued by the same initiator is 0.1^2 = 0.01, which represents the linkability probability. The unlinkability probability is given as 1-0.01 = 0.99. Thus,

(unlinkability, 0.99) < Eval(Mix (u=10, distribution=uniform), System_Setting(link=S-R), Risk_Model(type-1)).

We note that even if there is a Type-2 Risk in recursive resolver R, the same results hold.

To sum up, the above example is represented in the following template:

Eval(Mix (u=10, distribution=uniform), 
    System_Setting([S, P, R, A], [S-P, P-R, R-A]), 
      Risk_Model(Type-1A, S-R)) {
        Privacy_Mechanism{
            Mechanism_name = mix    //mix network
            Parameters{
                Users = 10
                Query_distribution = uniform
        }
        System_settings{
            Entities = S, P, R and A;
            Links = S-P, P-R, R-A
        }
        Risk_Model{
            Type = Type-1A
            Links = P-R
        }

        Privacy_guarantee = unlinkability
        Privacy_measure = 1-(1/users)^2.

        Return privacy_guarantee, privacy_measure
}
 

7.3 Encrypted Channel (DNS-over-TLS) Example

For one of the encryption-based mechanisms, DNS-over-TLS [dns-over-tls], we have the following template (TLS parameters are from [RFC5246]):

  
Eval(TLS_enc (SHA256, ECDSA, port 53, uniform), 
    System_Setting([S, P, R, A], [S-P, P-R, RA]), 
        Risk_Model(Type-1B, S-R)) {
          Privacy_Mechanism{
            Mechanism_name = TLS-upgrade-based
              Parameters{
                Query_distribution = uniform
                Hash_algorithm = SHA256
                Sig_Algorithm = ECDSA
                Port 53
              }
              System_settings{
                Entities = S, P, R and A;
                Links = S-P, P-R, R-A
              }
              Risk_Model{
                Type = Type-1B
                Links = S-R
              }
              Privacy_guarantee = unlinkability, undetectability
              Privacy_measure (unlinkability) = 1
              Privacy_measure (undetectability) = 0 // port 53 indicates DNS used

              Return privacy_guarantee, privacy_measure
}

This template features an Active Monitor risk model (Type-2) in order to show how that the monitor might apply extra resources to an encrypted channel. Undetectability is an issue whether using upgrade-based TLS on port 53, or a port-based TLS on a dedicated port - both ports indicate the use of DNS. The source address of the individual is exposed in all cases. If this were a suitably parameterized use of [ipseca], the monitor would not be certain that all the traffic from S-R was DNS, and undetectability would be higher.

7.4 Encrypted Channel (IPSec) Example

In the following, we use the same template above to characterize the encryption capabilities provided by IPSec, as a potential mechanisms for enabling privacy in DNS exchanges.

  
Eval(IPSEc_enc([...]), 
    System_Setting([S, P, R, A], [S-P, P-R, RA]), 
      Risk_Model(Type-1B, S-R)) {
        Privacy_Mechanism{
          Mechanism_name = IPSec
          Parameters{
            Query_distribution = uniform
          }
          System_settings{
            Entities = S, P, R and A;
            Links = S-P, P-R, R-A
          }
          Risk_Model{
            Type = 2
            Links = S-R
          }
          Privacy_guarantee = unlinkability, undetectability
          Privacy_measure (unlinkability) = 1
          Privacy_measure (undetectability) = 1 

          Return privacy_guarantee, privacy_measure
}

We note that IPSec can provide better guarantees with respect to studied privacy notions. However, whether the technique itself is widely deployable or not is worth further investigation.

7.5 QName Minimization Example (R-A) Example

Analyzing the privacy assurances of QName minimization is a non-trivial problem, given that the notions introduced in this document are techniques that do not alter items of interest. This is, the notions of privacy as outlined above are concerned with a certain IOI that is modified by this technique. To this end, we modify the aforementioned notions in ordered to be able to analyze the technique. For example, we define linkability as the ability of an adversary to link two labels of (minimized) queries to each other, and relate them to original source of query. Assuming a reasonable use of a recursive resolver that minimizes queries on behalf of users, this task is non-trivial, although quantifying the probability would depend on the number of labels in queries, the number of queries issued, and the number of users using the studied recursive resolvers. The following template captures QName minimization as a template

  
Eval(Qname_minimisation ([...],
    System_Settings([S, P, R, A], [R-A]),
      Risk_Model(Type=2){
        Privacy_Mechanism{
          Mechanism_name = Qname_minimisation
          Parameters{
            Qtype_used = NS
        }
        System_settings{
          Entities = S, P, R and A;
          Links = R-A
        }
        Risk_model{
          Type = 2
          Links = R-A    
        }
        Privacy_guarantee =  unlinkability
        Privacy_measure = analytical 

        Return privacy_guarantee, privacy_measure
}

Note that QName minimization does not solve the problem of the privacy for a monitoring risk between the stub and recursive. Encrypting the channel between the recursive and the stub, utilizing other techniques such as TDNS or IPSec, can marginalize such risk. Furthermore, note that the risk on the link between the recursive and authority name servers is always mitigated by the fact that recursive name servers act as a mixer of queries, even when they are sent in full to the authority name servers.

7.7 Private-DNS (S-R) Example

The template for [privatedns] takes note of deployments in which in addition to S, R and A, there is another entity in the system, the function that authenticates the individual using S prior to permitting an encrypted channel to be formed to R or A. If the Private-DNS connection is with R, then identifiability of S as an individual may be similar to the identifiability of S from source address, or it may be stronger, depending on the nature of the account information required. If the Private-DNS connection is with A, source address PII is provided to A, and linkability of the queries from S has probability 1.

8. Other evaluation

This document does not address a lot of the evaluation aspects not associated with privacy. For example, some of the mechanisms discussed in the working group are built of well-understood and standardized technologies, whereas others use other non-standard and less widely deployed techniques. A comprehensive evaluation of such mechanisms should take into account such facts.

9. Security Considerations

The purpose of this document is to provide methods for those deploying or using DNS private exchange to assess the effectiveness of privacy mechanisms in depriving monitors of access to private information. Protecting privacy is one of the dimensions of an overall security strategy.

It is possible for privacy-enhancing mechanisms to be deployed in ways that are vulnerable to security risks, with the result of not achieving security gains. For the purposes of privacy evaluation, it is important for the person making an evaluation to also ensure close attention to the content of the Security Considerations section of each mechanism being evaluated, for instance, to ensure if TLS is used for encryption of a link against surveillance, that TLS best security practices [RFC7525] are in use.

10. IANA Considerations

No requests are made to IANA.

11. Acknowledgements

We wish to thank Scott Hollenbeck, Burt Kaliski, Minsuk Kang, Paul Livesay and Eric Osterweil for reviewing early versions. We wish to thank Stephane Bortzmeyer and Tim Wicinski for their detailed review and feedback on the previous versions of this document. We also wish to thank those who commented on presentations of this work ahead of publication, including Simson Garfinkel, Cathy Meadows, Paul Syverson, and Christine Task.

12. Informative References

[confidential-dns] Wijngaards, W. and G. Wiley, "Confidential DNS", Internet-Draft draft-wijngaards-dnsop-confidentialdns-03, March 2015.
[dns-over-tls] Zhu, L., Hu, Z., Heidemann, J., Wessels, D., Mankin, A. and P. Hoffman, "TLS for DNS: Initiation and Performance Considerations", Internet-Draft draft-ietf-dprive-dns-over-tls-01.txt, February 2015.
[ipseca] Osterweil, E., Wiley, G., Okubo, T., Lavu, R. and A. Mohaisen, "Opportunistic Encryption with DANE Semantics and IPsec: IPSECA", Internet-Draft draft-osterweil-dane-ipsec-03, March 2015.
[openresolverproject.org] Mauch, J., "The Open Resolver Project", April 2015.
[phb-dnse] Hallam-Baker, P., "DNS Privacy and Censorship: Use Cases and Requirements", Internet-Draft draft-hallambaker-dnse-02, November 2014.
[privatedns] Hallam-Baker, P., "Private-DNS", Internet-Draft draft-hallambaker-privatedns-01, November 2014.
[qname-minimisation] Bortzmeyer, S., "DNS query name minimisation to improve privacy", Internet-Draft draft-ietf-dnsop-qname-minimisation-07, March 2015.
[RFC3552] Rescorla, E. and B. Korver, "Guidelines for Writing RFC Text on Security Considerations", BCP 72, RFC 3552, DOI 10.17487/RFC3552, July 2003.
[RFC4949] Shirey, R., "Internet Security Glossary, Version 2", FYI 36, RFC 4949, DOI 10.17487/RFC4949, August 2007.
[RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security (TLS) Protocol Version 1.2", RFC 5246, DOI 10.17487/RFC5246, August 2008.
[RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., Morris, J., Hansen, M. and R. Smith, "Privacy Considerations for Internet Protocols", RFC 6973, DOI 10.17487/RFC6973, July 2013.
[RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an Attack", BCP 188, RFC 7258, DOI 10.17487/RFC7258, May 2014.
[RFC7435] Dukhovni, V., "Opportunistic Security: Some Protection Most of the Time", RFC 7435, DOI 10.17487/RFC7435, December 2014.
[RFC7525] Sheffer, Y., Holz, R. and P. Saint-Andre, "Recommendations for Secure Use of Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS)", BCP 195, RFC 7525, DOI 10.17487/RFC7525, May 2015.
[RFC7626] Bortzmeyer, S., "DNS Privacy Considerations", RFC 7626, DOI 10.17487/RFC7626, August 2015.

Authors' Addresses

Aziz Mohaisen SUNY Buffalo 323 Davis Hall Buffalo, NY 14260 US Phone: +1 716 645-1592 EMail: mohaisen@buffalo.edu
Allison Mankin Verisign Labs 12061 Bluemont Way Reston, VA 20190 US Phone: +1 703 948-3200 EMail: amankin@verisign.com