Re: Request for feedback on crypto privacy protections of geolocation data
On 9/9/13 6:13 PM, Brian Smith wrote: I assume by "prevents people from tracking individual access points" means the following: Some people have a personal access point on them (e.g. in their phone). If somebody knows the SSID and MAC of this personal access point, then they could track this person's location by polling the database for that (SSID, MAC) pair. Tracking a person's movements by polling the database would not be useful because we would probably update the database infrequently (days or weeks). The location database would be generated offline from analysis of many raw measurements submitted by the stumbler app. The tracking scenario that might be viable is a tracker who knows someones MAC address and current SSID and that person moves to a different city or state. The database delay wouldn't matter as much. The hash of hashes scheme tries to protect against that by requiring two neighboring APs. MAC addresses are 48 bits. SSIDs are often guessable or predictable. Therefore, using the H(MAC+SSID) instead of just the plain MAC+SSID is not buying you much in terms of privacy, IMO. Basically, if you are really trying to use this as a privacy mechanism then you should store the MAC+SSID according to best practices for storing passwords. For example, use PBKDF2 with a large number of iterations. Regardless of whether you use SHA1, SHA2, PBKDF2, or something else, I will still call whatever function you use H(x). But, I am not sure that switching to PBKDF2 even buys you much improved privacy protection. The primary motivation for hashing the MAC+SSID was to avoid uploading the SSID (which is considered private data in some European countries) while still using the SSID as sort of weak protection against "database pollution" from malicious stumblers reporting spoofed MAC addresses. Even if our database will filled with junk MAC address, real clients would probably not see the same combination of MAC and SSID in the real world when they sent a geolocation request to the server. Other layers of privacy protection include filtering out ad-hoc Wi-Fi networks; MAC addresses with vendor prefixes from mobile device manufacters (e.g. Apple and HTC); SSIDs commonly associated with mobile devices (e.g. "XXX's iPhone" and Google's "_nomap" opt-out); and APs reported in multiple locations. I think that these things are much more important than the protection offered by H(x). My concern is that if you store the data on the server as H(x) then you will not be able to do the above filtering on the server unless H(x) is ineffective. That seems bad, because the server will be much easier to update to improve the filtering than the clients will be, AFAICT. Also, you will not be able to measure the effectiveness of the privacy protections on the server, which is also very bad. Very good points. We are currently filtering on the stumbler client side. Today, the server just receives mystery hashes with latitude and longitude. Given just MAC addresess, the server could still filter out ad-hoc networks; vendor prefixes for known mobile device manufacturers; and unrecognized vendor prefixes (because some mobile devices supposedly generate a completely random MAC addresses). We would still need to rely on the stumbler to filter SSIDs. We can't upload SSIDs to the server because they are considered private data in some European countries (though MAC addresses, which are more unique, are apparently not considered private data, in a legal sense). We've compiled a list of about 70 SSID prefixes and suffixes we've seen from mobile devices (e.g. "Android*", "Verizon *", or "*'s iPhone"). Not all of these mobile devices use ad-hoc MAC addresses. Trivia: over a couple years of my own Wi-Fi stumbling/wardriving in three countries and six US states, I have recorded over 100K unique APs and only eight used Google's "_nomap" SSID opt-out suffix! chris ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
On 9/9/13 4:25 PM, R. Jason Cronk wrote:
On 9/9/2013 5:58 PM, Chris Peterson wrote:
Our private database maps access point hash IDs to locations (and
other metadata). Assuming:
H1 = Hash(AP1.MAC + AP1.SSID)
H2 = Hash(AP2.MAC + AP2.SSID)
I assume + means concatenate. I might suggest XORing the values. SSID
names are usually human readable, not meant to be secure and thus follow
predictable patterns. I also hope you're not using the patterned MAC
notation but rather the 48 bit address space representation.
We currently use concatenation, but I see how XOR would make more sense.
We are using the SSID as a weak protection against someone "polluting"
our database results by submitting random MAC addresses. Our database
still might have their junk data, but real location requests shouldn't
hit them.
We are using the MAC string notation like "45:67:89:ab:cd:ef", but I see
that this format has predictable patterns, too. I will recommend we use
the 48-bit binary representation.
What is the granularity of the lat/long?
This depends on the GPS of the device used to collect the data, but our
database stores 7 decimal places (less than one meter resolution).
Someone querying the published database would need to know the MAC
addresses and current SSIDs of two neighboring access points to look
up either's location.
When you say published, do you mean that the entire DB is published for
use by "researchers" or that it's just has a publicly exposed API that
responds to queries?
We are investigating both a web service API and a downloadable database.
We are collecting position data for both Wi-Fi access points and cell
towers. Depending on privacy protections, if we can't publish the whole
database to the world, we can publish just the cell tower data to the
world and possibly make the Wi-Fi data available only to trusted
researchers.
I'm assuming if AP3 through AP10 were all also in the vicinity that
Hash(H1+Hx) ==> Random1 where x is in {2,..,10}, correct?
If so, is whatever value Hy is the prefix in the concatenation will
correspond to APy's Random id?
In the proposed scheme, yes. Since AP1 and AP2 have different (but
close) latitude and longitude positions, Hash(H1+H2) would fetch the
random row id for AP1's location and Hash(H2+H1) would fetch the row id
for AP2's location.
chris
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Re: Request for feedback on crypto privacy protections of geolocation data
On 9/9/13 6:41 PM, Eric Rescorla wrote: 1. How do I bootstrap? I turn on my device and want to get the coordinates of the aps I see. That requires a lat long for neighbors. What now? The device would scan for nearby APs and send the hash of each AP's MAC and SSID to our location server. Our server would not need to worry about the hash of hashes pairs because that would only be used for published data. The server would return an estimated latitude, longitude, and accuracy (radius in meters) of the device among the APs. The simple approach for predicting the device's position is trilateration using a weighted average of the nearby APs' positions. A more robust approach is a grid-based approach where the server divides the world into squares and knows which APs have been seen from which squares. The device might be able to cache a portion of the geo data (e.g. part of the current city) to allow offline geolocation. 2. As asked previously will the db be published or query able? We are investigating both a web service API and a downloadable database. We are collecting position data for both Wi-Fi access points and cell towers. Depending on privacy protections, if we can't publish the whole database to the world, we can publish just the cell tower data to the world and possibly make the Wi-Fi data available only to trusted researchers. 3. What is the lat/long resolution? How is it measured? This depends on the GPS of the device used to collect the data, but our database stores 7 decimal places (less than one meter resolution). chris ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
On Mon, Sep 9, 2013 at 7:15 PM, Hanno Schlichting wrote: > On 09.09.2013, at 18:13 , Brian Smith wrote: >> On Mon, Sep 9, 2013 at 2:58 PM, Chris Peterson wrote: > [T]here's one crucial difference between Google and us: We would > like to make as much of this data public as possible, while Google will always > just provide a service without access to the underlying data. > We were looking for two things with using the sha1: > > - Make it possible for the end-user to change their unique value (they cannot > change the mac address, but they can change the ssid). This allows them to > "invalidate" historical records in the database. There is friction in changing SSIDs as it affects every device that would connect to that network. There will also probably not be much awareness among users of when/why/how to do this or what effect it will have. So, I think this is an aspect that sounds great in theory, but in practice will nearly never be used. > - Make it harder for spammers to "guess" actual unique keys and flood our > service. Mac addresses have a vendor prefix, which makes it rather easy to > generate lots of valid mac addresses. Taking the ssid into account makes it > harder to generate valid keys. Unfortunately the ssid itself is considered > private data in European countries, so you aren't allowed to store it without > the users consent. That's why Google and everyone else has stopped storing > them and only use mac addresses now. > > The sha1 scheme might be ineffective in doing this. If x is private data then SHA1(x), SHA2(x), PBKDF2(x), and even AES256(x, key) with a key known to you are all private data too. >> Therefore, I'd suggest that you avoid using any protection at all, and >> just use x instead of H(x) until we are very confident there is no way >> we can further improve the filtering. > > This sounds like good advice and I'm starting to lean into this direction. > > But this only helps us on the "we provide a service" side. It's still unclear > to me if and how we could share any of this data as database dumps. If you wanted to publish this data, and the data was stored in its raw state, then you could always apply whatever mapping (SHA2, PKBKFD2, AES256 with random and thrown-away key, etc.) right before you share the data. Even if you use AES256 with a random, thrown-away key, the data will be subject to reverse engineering. For example, one could correlate a subset of the data with a separate database of known (MAC,SSID,Location) triples, and/or attempt "traffic analysis" to see relationships in how (MAC,SSID) pairs interact with each other with respect to location. You have probably heard of the Netflix Prize privacy issues [1]; this is a very similar problem to the Netflix prize. Therefore, while it may be important to obscure the data before giving it to researchers, we should still consider the obscured data to be highly-sensitive confidential user data. [1] http://en.wikipedia.org/wiki/Netflix_Prize#Privacy_concerns Cheers, Brian -- Mozilla Networking/Crypto/Security (Necko/NSS/PSM) ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
On 09.09.2013, at 18:41 , Eric Rescorla wrote: > 1. How do I bootstrap? I turn on my device and want to get the coordinates of > the aps I see. That requires a lat long for neighbors. What now? We build the database by having people use a stumbler application to sent us observations. The stumbler app uses the mobile phones GPS sensor to know its location. It reports all cell towers and wifi APs it sees to us in a certain location. We crunch some data, then we make a search API available over this data. Later someone else asks us what their location is, based on seeing cell towers or APs. > 2. As asked previously will the db be published or query able? It will definitely be queryable, but with a lot of restrictions to enhance privacy. We would like to publish it or as much of it as possible, but it's unclear how to do that, when a lot of the individual records are considered personally identifiable information. > 3. What is the lat/long resolution? How is it measured? The resolution differs, but is generally "as precise as it gets". So GPS sensors often have 5 meter precision, Google aims to do 1 meter resolution for indoor locations based on Wifi access points. Internally we currently store things with centimeter precision and timestamps in milliseconds - so definitely all on the far side of "extremely detailed / private". Hanno ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
On 09.09.2013, at 18:13 , Brian Smith wrote: > On Mon, Sep 9, 2013 at 2:58 PM, Chris Peterson wrote: >> Google's Location Service prevents people from tracking individual access >> points by requiring requests to include at least 2-3 access points that >> Google knows are near each other. This "proves" the requester is near the >> access points. > > I assume by "prevents people from tracking individual access points" > means the following: Some people have a personal access point on them > (e.g. in their phone). If somebody knows the SSID and MAC of this > personal access point, then they could track this person's location by > polling the database for that (SSID, MAC) pair. Google tries to limit > this type of abuse as much as practical while providing still > providing a location service based on such crowdsourced data. Yes :) Though there's one crucial difference between Google and us: We would like to make as much of this data public as possible, while Google will always just provide a service without access to the underlying data. >> Unlike Google's Location Service, our server does not store MAC addresses or >> SSIDs. We identify access points by hash IDs, specifically SHA1(MAC+SSID). >> To query the location of an access point in the database, you must know both >> its MAC address and current SSID. > > MAC addresses are 48 bits. SSIDs are often guessable or predictable. > Therefore, using the H(MAC+SSID) instead of just the plain MAC+SSID is > not buying you much in terms of privacy, IMO. Basically, if you are > really trying to use this as a privacy mechanism then you should store > the MAC+SSID according to best practices for storing passwords. For > example, use PBKDF2 with a large number of iterations. Regardless of > whether you use SHA1, SHA2, PBKDF2, or something else, I will still > call whatever function you use H(x). But, I am not sure that switching > to PBKDF2 even buys you much improved privacy protection. We were looking for two things with using the sha1: - Make it possible for the end-user to change their unique value (they cannot change the mac address, but they can change the ssid). This allows them to "invalidate" historical records in the database. - Make it harder for spammers to "guess" actual unique keys and flood our service. Mac addresses have a vendor prefix, which makes it rather easy to generate lots of valid mac addresses. Taking the ssid into account makes it harder to generate valid keys. Unfortunately the ssid itself is considered private data in European countries, so you aren't allowed to store it without the users consent. That's why Google and everyone else has stopped storing them and only use mac addresses now. The sha1 scheme might be ineffective in doing this. >>H1 = Hash(AP1.MAC + AP1.SSID) >>H2 = Hash(AP2.MAC + AP2.SSID) >> >> Our private database's schema looks something like: >> >>Hash(AP1.MAC + AP1.SSID) ==> AP1.latitude, AP1.longitude, ... >>Hash(AP2.MAC + AP2.SSID) ==> AP2.latitude, AP2.longitude, ... >> >> Our published database would include two tables. The first table would map a >> random row id to metadata about an anonymous access point: >> >>Random1 ==> AP1.latitude, AP1.longitude, ... >>Random2 ==> AP2.latitude, AP2.longitude, ... >> >> The second table's primary key would be a hash of hashes. It would map a >> hash of two neighboring access points' hash IDs to a row id of the first >> table. Something like: >> >>Hash(H1 + H2) ==> Random1 >>Hash(H2 + H1) ==> Random2 >> >> Someone querying the published database would need to know the MAC addresses >> and current SSIDs of two neighboring access points to look up either's >> location. > > If you know the MAC+SSID of person X's personal access point and the > MAC+SSID of person Y's personal access point, then you can use this > database to ask the question "are person X and person Y in the same > location?" This seems bad. I see that you attempt to address this > below. On the service level, we can prevent this with adding extra thresholds. Like filtering out "moving" APs and only reporting APs which have been seen in the same location a number of times over a minimum time period. But this doesn't help us when publishing the underlying data. >> btw, should we use SHA-2 instead of SHA-1? > > There is no reason to use SHA-1 when you have SHA-2 available. > However, as I indicated above, it isn't clear it is a good idea to be > using any plain hash function as H(x). > >> Other layers of privacy protection include filtering out ad-hoc Wi-Fi >> networks; MAC addresses with vendor prefixes from mobile device manufacters >> (e.g. Apple and HTC); SSIDs commonly associated with mobile devices (e.g. >> "XXX's iPhone" and Google's "_nomap" opt-out); and APs reported in multiple >> locations. > > I think that these things are much more important than the protection > offered by H(x). My concern is that if you store the data on the > server as
Re: Request for feedback on crypto privacy protections of geolocation data
Chris, I have some basic and perhaps stupid questions. 1. How do I bootstrap? I turn on my device and want to get the coordinates of the aps I see. That requires a lat long for neighbors. What now? 2. As asked previously will the db be published or query able? 3. What is the lat/long resolution? How is it measured? Thanks Ekr On Sep 9, 2013, at 14:58, Chris Peterson wrote: > I'm looking for some feedback on crypto privacy protections for a geolocation > research project I'm working on with the Mozilla Services team. If you have > general questions or suggestions about the project, I'm happy to answer them, > but I'd like to focus this thread on crypto. > > Our team is prototyping a crowd-sourced version of Google's Street View cars > to correlate Wi-Fi access points and cell towers to GPS positions. Our > primary motivation is to provide non-proprietary location services for > Firefox OS devices. We would also like to publish this location data for > researchers or other projects that might have novel uses for it. > > Google's Location Service prevents people from tracking individual access > points by requiring requests to include at least 2-3 access points that > Google knows are near each other. This "proves" the requester is near the > access points. > > Below is a sketch of a scheme that I think will allow us to publish a > database of access point locations while still requiring knowledge of two > neighboring access points. > > Unlike Google's Location Service, our server does not store MAC addresses or > SSIDs. We identify access points by hash IDs, specifically SHA1(MAC+SSID). To > query the location of an access point in the database, you must know both its > MAC address and current SSID. > > Our private database maps access point hash IDs to locations (and other > metadata). Assuming: > >H1 = Hash(AP1.MAC + AP1.SSID) >H2 = Hash(AP2.MAC + AP2.SSID) > > Our private database's schema looks something like: > >Hash(AP1.MAC + AP1.SSID) ==> AP1.latitude, AP1.longitude, ... >Hash(AP2.MAC + AP2.SSID) ==> AP2.latitude, AP2.longitude, ... > > Our published database would include two tables. The first table would map a > random row id to metadata about an anonymous access point: > >Random1 ==> AP1.latitude, AP1.longitude, ... >Random2 ==> AP2.latitude, AP2.longitude, ... > > The second table's primary key would be a hash of hashes. It would map a hash > of two neighboring access points' hash IDs to a row id of the first table. > Something like: > >Hash(H1 + H2) ==> Random1 >Hash(H2 + H1) ==> Random2 > > Someone querying the published database would need to know the MAC addresses > and current SSIDs of two neighboring access points to look up either's > location. > > btw, should we use SHA-2 instead of SHA-1? In 2009, NIST recommended that > "Federal agencies should stop using SHA-1 for applications that require > collision resistance as soon as practical, and must use the SHA-2 family of > hash functions for these applications after 2010." > > Other layers of privacy protection include filtering out ad-hoc Wi-Fi > networks; MAC addresses with vendor prefixes from mobile device manufacters > (e.g. Apple and HTC); SSIDs commonly associated with mobile devices (e.g. > "XXX's iPhone" and Google's "_nomap" opt-out); and APs reported in multiple > locations. > > > thanks, > chris > ___ > dev-security mailing list > dev-security@lists.mozilla.org > https://lists.mozilla.org/listinfo/dev-security ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
On Mon, Sep 9, 2013 at 2:58 PM, Chris Peterson wrote: > Google's Location Service prevents people from tracking individual access > points by requiring requests to include at least 2-3 access points that > Google knows are near each other. This "proves" the requester is near the > access points. I assume by "prevents people from tracking individual access points" means the following: Some people have a personal access point on them (e.g. in their phone). If somebody knows the SSID and MAC of this personal access point, then they could track this person's location by polling the database for that (SSID, MAC) pair. Google tries to limit this type of abuse as much as practical while providing still providing a location service based on such crowdsourced data. > Unlike Google's Location Service, our server does not store MAC addresses or > SSIDs. We identify access points by hash IDs, specifically SHA1(MAC+SSID). > To query the location of an access point in the database, you must know both > its MAC address and current SSID. MAC addresses are 48 bits. SSIDs are often guessable or predictable. Therefore, using the H(MAC+SSID) instead of just the plain MAC+SSID is not buying you much in terms of privacy, IMO. Basically, if you are really trying to use this as a privacy mechanism then you should store the MAC+SSID according to best practices for storing passwords. For example, use PBKDF2 with a large number of iterations. Regardless of whether you use SHA1, SHA2, PBKDF2, or something else, I will still call whatever function you use H(x). But, I am not sure that switching to PBKDF2 even buys you much improved privacy protection. > H1 = Hash(AP1.MAC + AP1.SSID) > H2 = Hash(AP2.MAC + AP2.SSID) > > Our private database's schema looks something like: > > Hash(AP1.MAC + AP1.SSID) ==> AP1.latitude, AP1.longitude, ... > Hash(AP2.MAC + AP2.SSID) ==> AP2.latitude, AP2.longitude, ... > > Our published database would include two tables. The first table would map a > random row id to metadata about an anonymous access point: > > Random1 ==> AP1.latitude, AP1.longitude, ... > Random2 ==> AP2.latitude, AP2.longitude, ... > > The second table's primary key would be a hash of hashes. It would map a > hash of two neighboring access points' hash IDs to a row id of the first > table. Something like: > > Hash(H1 + H2) ==> Random1 > Hash(H2 + H1) ==> Random2 > > Someone querying the published database would need to know the MAC addresses > and current SSIDs of two neighboring access points to look up either's > location. If you know the MAC+SSID of person X's personal access point and the MAC+SSID of person Y's personal access point, then you can use this database to ask the question "are person X and person Y in the same location?" This seems bad. I see that you attempt to address this below. > btw, should we use SHA-2 instead of SHA-1? There is no reason to use SHA-1 when you have SHA-2 available. However, as I indicated above, it isn't clear it is a good idea to be using any plain hash function as H(x). > Other layers of privacy protection include filtering out ad-hoc Wi-Fi > networks; MAC addresses with vendor prefixes from mobile device manufacters > (e.g. Apple and HTC); SSIDs commonly associated with mobile devices (e.g. > "XXX's iPhone" and Google's "_nomap" opt-out); and APs reported in multiple > locations. I think that these things are much more important than the protection offered by H(x). My concern is that if you store the data on the server as H(x) then you will not be able to do the above filtering on the server unless H(x) is ineffective. That seems bad, because the server will be much easier to update to improve the filtering than the clients will be, AFAICT. Also, you will not be able to measure the effectiveness of the privacy protections on the server, which is also very bad. Therefore, I'd suggest that you avoid using any protection at all, and just use x instead of H(x) until we are very confident there is no way we can further improve the filtering. Cheers, Brian Smith -- Mozilla Networking/Crypto/Security (Necko/NSS/PSM), NSA plant ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
Re: Request for feedback on crypto privacy protections of geolocation data
I haven't done a full analysis but do have a few questions
On 9/9/2013 5:58 PM, Chris Peterson wrote:
Our private database maps access point hash IDs to locations (and
other metadata). Assuming:
H1 = Hash(AP1.MAC + AP1.SSID)
H2 = Hash(AP2.MAC + AP2.SSID)
I assume + means concatenate. I might suggest XORing the values. SSID
names are usually human readable, not meant to be secure and thus follow
predictable patterns. I also hope you're not using the patterned MAC
notation but rather the 48 bit address space representation.
Our private database's schema looks something like:
Hash(AP1.MAC + AP1.SSID) ==> AP1.latitude, AP1.longitude, ...
Hash(AP2.MAC + AP2.SSID) ==> AP2.latitude, AP2.longitude, ...
Is the data aged? What happens if I move? Does this give Mozilla the
ability to historically track me if I move my device? Is that a problem?
(I'm not saying it is, just an observation).
You mention below about filtering APs in multiple locations but clearly
they can move as people relocate.
What is the granularity of the lat/long?
Our published database would include two tables. The first table would
map a random row id to metadata about an anonymous access point:
Random1 ==> AP1.latitude, AP1.longitude, ...
Random2 ==> AP2.latitude, AP2.longitude, ...
I would be hesitant to use the word anonymous here. Latlong is easily
combine with other publicly available databases that could identify
individual address and thus individuals. Again, it comes down to
granularity of the data.
The second table's primary key would be a hash of hashes. It would map
a hash of two neighboring access points' hash IDs to a row id of the
first table. Something like:
Hash(H1 + H2) ==> Random1
Hash(H2 + H1) ==> Random2
Someone querying the published database would need to know the MAC
addresses and current SSIDs of two neighboring access points to look
up either's location.
When you say published, do you mean that the entire DB is published for
use by "researchers" or that it's just has a publicly exposed API that
responds to queries?
I'm assuming if AP3 through AP10 were all also in the vicinity that
Hash(H1+Hx) ==> Random1 where x is in {2,..,10}, correct?
If so, is whatever value Hy is the prefix in the concatenation will
correspond to APy's Random id?
btw, should we use SHA-2 instead of SHA-1? In 2009, NIST recommended
that "Federal agencies should stop using SHA-1 for applications that
require collision resistance as soon as practical, and must use the
SHA-2 family of hash functions for these applications after 2010."
Yes
*R. Jason Cronk, Esq., CIPP/US*
/Privacy Engineering Consultant/, *Enterprivacy Consulting Group*
* phone: (828) 4RJCESQ
* twitter: @privacymaverick.com
* blog: http://blog.privacymaverick.com
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Request for feedback on crypto privacy protections of geolocation data
I'm looking for some feedback on crypto privacy protections for a geolocation research project I'm working on with the Mozilla Services team. If you have general questions or suggestions about the project, I'm happy to answer them, but I'd like to focus this thread on crypto. Our team is prototyping a crowd-sourced version of Google's Street View cars to correlate Wi-Fi access points and cell towers to GPS positions. Our primary motivation is to provide non-proprietary location services for Firefox OS devices. We would also like to publish this location data for researchers or other projects that might have novel uses for it. Google's Location Service prevents people from tracking individual access points by requiring requests to include at least 2-3 access points that Google knows are near each other. This "proves" the requester is near the access points. Below is a sketch of a scheme that I think will allow us to publish a database of access point locations while still requiring knowledge of two neighboring access points. Unlike Google's Location Service, our server does not store MAC addresses or SSIDs. We identify access points by hash IDs, specifically SHA1(MAC+SSID). To query the location of an access point in the database, you must know both its MAC address and current SSID. Our private database maps access point hash IDs to locations (and other metadata). Assuming: H1 = Hash(AP1.MAC + AP1.SSID) H2 = Hash(AP2.MAC + AP2.SSID) Our private database's schema looks something like: Hash(AP1.MAC + AP1.SSID) ==> AP1.latitude, AP1.longitude, ... Hash(AP2.MAC + AP2.SSID) ==> AP2.latitude, AP2.longitude, ... Our published database would include two tables. The first table would map a random row id to metadata about an anonymous access point: Random1 ==> AP1.latitude, AP1.longitude, ... Random2 ==> AP2.latitude, AP2.longitude, ... The second table's primary key would be a hash of hashes. It would map a hash of two neighboring access points' hash IDs to a row id of the first table. Something like: Hash(H1 + H2) ==> Random1 Hash(H2 + H1) ==> Random2 Someone querying the published database would need to know the MAC addresses and current SSIDs of two neighboring access points to look up either's location. btw, should we use SHA-2 instead of SHA-1? In 2009, NIST recommended that "Federal agencies should stop using SHA-1 for applications that require collision resistance as soon as practical, and must use the SHA-2 family of hash functions for these applications after 2010." Other layers of privacy protection include filtering out ad-hoc Wi-Fi networks; MAC addresses with vendor prefixes from mobile device manufacters (e.g. Apple and HTC); SSIDs commonly associated with mobile devices (e.g. "XXX's iPhone" and Google's "_nomap" opt-out); and APs reported in multiple locations. thanks, chris ___ dev-security mailing list dev-security@lists.mozilla.org https://lists.mozilla.org/listinfo/dev-security
