For many years, American businesses have enjoyed a bit of special treatment under European data privacy laws. The so-called "Safe Harbor" arrangement was negotiated by the Federal Communications Commission (FCC) so that companies could self-declare broad compliance with data security rules. Normally organisations are not permitted to move Personally Identifiable Information (PII) about Europeans beyond the EU unless the destination has equivalent privacy measures in place. The "Safe Harbor" arrangement was a shortcut around full compliance; as such it was widely derided by privacy advocates outside the USA, and for some years had been questioned by the more activist regulators in Europe. And so it seemed inevitable that the arrangement would be eventually annulled, as it was last October.
With the threat of most personal data flows from Europe into America being halted, US and EU trade officials have worked overtime for five months to strike a new deal. Today (January 29) the US Department of Commerce announced the "EU-US Privacy Shield".
The Privacy Shield is good news for commerce of course. But I hope that in the excitement, American businesses don't lose sight of the broader sweep of privacy law. Even better would be to look beyond compliance, and take the opportunity to rethink privacy, because there is more to it than security and regulatory short cuts.
The Privacy Shield and the earlier Safe Harbor arrangement are really only about satisfying one corner of European data protection laws, namely transborder flows. The transborder data flow rules basically say you must not move personal data from an EU state into a jurisdiction where the privacy protections are weaker than in Europe. Many countries actually have the same sort of laws, including Australia. Normally, as a business, you would have to demonstrate to a European data protection authority (DPA) that your information handling is complying with EU laws, either by situating your data centre in a similar jurisdiction, or by implementing legally binding measures for safeguarding data to EU standards. This is why so many cloud service providers are now building fresh infrastructure in the EU.
But there is more to privacy than security and data centre location. American businesses must not think that just because there is a new get-out-of-jail clause for transborder flows, their privacy obligations are met. Much more important than raw data security are the bedrocks of privacy: Collection Limitation, Usage Limitation, and Transparency.
Basic data privacy laws the world-over require organisations to exercise constraint and openness. That is, Personal Information must not be collected without a real demonstrated need (or without consent); once collected for a primary purpose, Personal Information should not be used for unrelated secondary purposes; and individuals must be given reasonable notice of what personal data is being collected about them, how it is collected, and why. It's worth repeating: general data protection is not unique to Europe; at last count, over 100 countries around the world had passed similar laws; see Prof Graham Greenleaf's Global Tables of Data Privacy Laws and Bills, January 2015.
Over and above Safe Harbor, American businesses have suffered some major privacy missteps. The Privacy Shield isn't going to make overall privacy better by magic.
For instance, Google in 2010 was caught over-collecting personal information through its StreetView cars. It is widely known (and perfectly acceptable) that mapping companies use the positions of unique WiFi routers for their geolocation databases. Google continuously collects WiFi IDs and coordinates via its StreetView cars. The privacy problem here was that some of the StreetView cars were also collecting unencrypted WiFi traffic (for "research purposes") whenever they came across it. In over a dozen countries around the world, Google admitted they had breached local privacy laws by colelcting excessive PII, apologised for the overreach, explained it as inadvertent, and deleted all the WiFi records in question. The matter was settled in just a few months in places like Korea, Japan and Australia. But in the US, where there is no general collection limitation privacy rule, Google has been defending what they did. Absent general data privacy protection, the strongest legislation that seems to apply to the StreetView case is wire tap law, but its application to the Internet is complex. And so the legal action has taken years and years, and it's still not resolved.
I don't know why Google doesn't see that a privacy breach in the rest of the world is a privacy breach in the US, and instead of fighting it, concede that the collection of WiFi traffic was unnecessary and wrong.
Other proof that European privacy law is deeper and broader than the Privacy Shield is found in social networking mishaps. Over the years, many of Facebook's business practices for instance have been found unlawful in the EU. Recently there was the final ruling against "Find Friends", which uploads the contact details of third parties without their consent. Before that there was the long running dispute over biometric photo tagging. When Facebook generates tag suggestions, what they're doing is running facial recognition algorithms over photos in their vast store of albums, without the consent of the people in those photos. Identifying otherwise anonymous people, without consent (and without restraint as to what might be done next with that new PII), seems to be an unlawful under the Collection Limitation and Usage Limitation principles.
In 2012, Facebook was required to shut down their photo tagging in Europe. They have been trying to re-introduce it ever since. Whether they are successful or not will have nothing to do with the "Privacy Shield".
The Privacy Shield comes into a troubled trans-Atlantic privacy environment. Whether or not the new EU-US arrangement fares better than the Safe Harbor remains to be seen. But in any case, since the Privacy Shield really aims to free up business access to data, sadly it's unlikely to do much good for true privacy.
The examples cited here are special cases of the collision of Big Data with data privacy, which is one of my special interest areas at Constellation Research. See for example "Big Privacy" Rises to the Challenges of Big Data.
The Biometrics Institute has received Australian government assistance to fund the next stage of the development of a new privacy Trust Mark. And Lockstep Consulting is again working with the Institute to bring this privacy initiative to fruition.
A detailed feasibility study was undertaken by Lockstep in the first half of 2015, involving numerous privacy advocates, regulators and vendors in Europe, the US, New Zealand and Australia.
We found strong demand for a reputable, non-trivial B2C biometrics certification.
Privacy advocates are generally supportive of a new Trust Mark, however they stress that a Trust Mark can be counter-productive if it is too easy to obtain, biased by industry interests, and/or poorly policed. There is general agreement that a credible trust mark should be non-trivial, and consequently, that the criteria be reasonably prescriptive. The reality of a strong Trust Mark is that not all architectures and solution instances will be compatible with the certification criteria.
The next stage of the Biometrics Institute project will deliver technical criteria for the award of the Trust Mark, and a PIA (Privacy Impact Assessment) template. A condition of the Trust Mark will be that a PIA is undertaken.
Please contact Steve Wilson at Lockstep email@example.com or Isabelle Moeller (Biometrics Institute CEO) firstname.lastname@example.org, if you'd like to receive further details of the Stage 1 findings, or would like to contribute to the technical research in Stage 2.
In 2002, a couple of Japanese visitors to Australia swapped passports with each other before walking through an automatic biometric border control gate being tested at Sydney airport. The facial recognition algorithm falsely matched each of them to the others' passport photo. These gentlemen were in fact part of an international aviation industry study group and were in the habit of trying to fool biometric systems then being trialed round the world.
When I heard about this successful prank, I quipped that the algorithms were probably written by white people - because we think all Asians look the same. Colleagues thought I was making a typical sick joke, but actually I was half-serious. It did seem to me that the choice of facial features thought to be most distinguishing in a facial recognition model could be culturally biased.
Since that time, border control face recognition has come a long way, and I have not heard of such errors for many years. Until today.
The San Francisco Chronicle of July 21 carries a front page story about the cloud storage services of Google and Flickr mislabeling some black people as gorillas (see updated story, online). It's a quite incredible episode. Google has apologized. Its Chief Architect of social, Yonatan Zunger, seems mortified judging by his tweets as reported, and is investigating.
The newspaper report quotes machine learning experts who suggest programmers with limited experience of diversity may be to blame. That seems plausible to me, although I wonder where exactly the algorithm R&D gets done, and how much control is to be had over the biometric models and their parameters along the path from basic research to application development.
So man has literally made software in his own image.
The public is now being exposed to Self Driving Cars, which are heavily reliant on machine vision, object recognition and artificial intelligence. If this sort of software can't tell people from apes in static photos given lots of processing time, how does it perform in real time, with fleeting images, subject to noise, and with much greater complexity? It's easy to imagine any number of real life scenarios where an autonomous car will have to make a split-second decision between two pretty similar looking objects appearing unexpectedly in its path.
The general expectation is that Self Driving Cars (SDCs) will be tested to exhaustion. And so they should. But if cultural partiality is affecting the work of programmers, it's possible that testers have suffer the same blind spots without knowing it. Maybe the offending photo labeling programs were never verified with black people. So how are the test cases for SDCs being selected? What might happen when an SDC ventures into environments and neighborhoods where its programmers have never been?
Everybody in image processing and artificial intelligence should be humbled by the racist photo labeling. With the world being eaten by software, we need to reflect really deeply on how such design howlers arise. And frankly double check if we're ready to let computer programs behind the wheel.
The State Of Identity Management in 2015
Constellation Research recently launched the "State of Enterprise Technology" series of research reports. These assess the current enterprise innovations which Constellation considers most crucial to digital transformation, and provide snapshots of the future usage and evolution of these technologies.
My second contribution to the state-of-the-state series is "Identity Management Moves from Who to What". Here's an excerpt from the report:
In spite of all the fuss, personal identity is not usually important in routine business. Most transactions are authorized according to someone’s credentials, membership, role or other properties, rather than their personal details. Organizations actually deal with many people in a largely impersonal way. People don’t often care who someone really is before conducting business with them. So in digital Identity Management (IdM), one should care less about who a party is than what they are, with respect to attributes that matter in the context we’re in. This shift in focus is coming to dominate the identity landscape, for it simplifies a traditionally multi-disciplined problem set. Historically, the identity management community has made too much of identity!
Six Digital Identity Trends for 2015
1. Mobile becomes the center of gravity for identity. The mobile device brings convergence for a decade of progress in IdM. For two-factor authentication, the cell phone is its own second factor, protected against unauthorized use by PIN or biometric. Hardly anyone ever goes anywhere without their mobile - service providers can increasingly count on that without disenfranchising many customers. Best of all, the mobile device itself joins authentication to the app, intimately and seamlessly, in the transaction context of the moment. And today’s phones have powerful embedded cryptographic processors and key stores for accurate mutual authentication, and mobile digital wallets, as Apple’s Tim Cook highlighted at the recent White House Cyber Security Summit.
2. Hardware is the key – and holds the keys – to identity. Despite the lure of the cloud, hardware has re-emerged as pivotal in IdM. All really serious security and authentication takes place in secure dedicated hardware, such as SIM cards, ATMs, EMV cards, and the new Trusted Execution Environment mobile devices. Today’s leading authentication initiatives, like the FIDO Alliance, are intimately connected to standard cryptographic modules now embedded in most mobile devices. Hardware-based identity management has arrived just in the nick of time, on the eve of the Internet of Things.
3. The “Attributes Push” will shift how we think about identity. In the words of Andrew Nash, CEO of Confyrm Inc. (and previously the identity leader at PayPal and Google), “Attributes are at least as interesting as identities, if not more so.” Attributes are to identity as genes are to organisms – they are really what matters about you when you’re trying to access a service. By fractionating identity into attributes and focusing on what we really need to reveal about users, we can enhance privacy while automating more and more of our everyday transactions.
The Attributes Push may recast social logon. Until now, Facebook and Google have been widely tipped to become “Identity Providers”, but even these giants have found federated identity easier said than done. A dark horse in the identity stakes – LinkedIn – may take the lead with its superior holdings in verified business attributes.
4. The identity agenda is narrowing. For 20 years, brands and organizations have obsessed about who someone is online. And even before we’ve solved the basics, we over-reached. We've seen entrepreneurs trying to monetize identity, and identity engineers trying to convince conservative institutions like banks that “Identity Provider” is a compelling new role in the digital ecosystem. Now at last, the IdM industry agenda is narrowing toward more achievable and more important goals - precise authentication instead of general identification.
5. A digital identity stack is emerging. The FIDO Alliance and others face a challenge in shifting and improving the words people use in this space. Words, of course, matter, as do visualizations. IdM has suffered for too long under loose and misleading metaphors. One of the most powerful abstractions in IT was the OSI networking stack. A comparable sort of stack may be emerging in IdM.
6. Continuity will shape the identity experience. Continuity will make or break the user experience as the lines blur between real world and virtual, and between the Internet of Computers and the Internet of Things. But at the same time, we need to preserve clear boundaries between our digital personae, or else privacy catastrophes await. “Continuous” (also referred to as “Ambient”) Authentication is a hot new research area, striving to provide more useful and flexible signals about the instantaneous state of a user at any time. There is an explosion in devices now that can be tapped for Continuous Authentication signals, and by the same token, rich new apps in health, lifestyle and social domains, running on those very devices, that need seamless identity management.
A snapshot at my report "Identity Moves from Who to What" is available for download at Constellation Research. It expands on the points above, and sets out recommendations for enterprises to adopt the latest identity management thinking.
I have just updated my periodic series of research reports on the FIDO Alliance. The fourth report, "FIDO Alliance Update: On Track to a Standard" is available at Constellation Research (for free for a time).
The Identity Management industry leader publishes its protocol specifications at v1.0, launches a certification program, and attracts support in Microsoft Windows 10.
The FIDO Alliance is the fastest-growing Identity Management (IdM) consortium we have seen. Comprising technology vendors, solutions providers, consumer device companies, and e-commerce services, the FIDO Alliance is working on protocols and standards to strongly authenticate users and personal devices online. With a fresh focus and discipline in this traditionally complicated field, FIDO envisages simply “doing for authentication what Ethernet did for networking”.
Launched in early 2013, the FIDO Alliance has now grown to over 180 members. Included are technology heavyweights like Google, Lenovo and Microsoft; almost every SIM and smartcard supplier; payments giants Discover, MasterCard, PayPal and Visa; several banks; and e-commerce players like Alibaba and Netflix.
FIDO is radically different from any IdM consortium to date. We all know how important it is to fix passwords: They’re hard to use, inherently insecure, and lie at the heart of most breaches. The Federated Identity movement seeks to reduce the number of passwords by sharing credentials, but this invariably confounds the relationships we have with services and complicates liability when more parties rely on fewer identities.
In contrast, FIDO’s mission is refreshingly clear: Take the smartphones and devices most of us are intimately connected to, and use the built-in cryptography to authenticate users to services. A registered FIDO-compliant device, when activated by its user, can send verified details about the device and the user to service providers, via standardized protocols. FIDO leverages the ubiquity of sophisticated handsets and the tidal wave of smart things. The Alliance focuses on device level protocols without venturing to change the way user accounts are managed or shared.
The centerpieces of FIDO’s technical work are two protocols, called UAF and U2F, for exchanging verified authentication signals between devices and services. Several commercial applications have already been released under the UAF and U2F specifications, including fingerprint-based payments apps from Alibaba and PayPal, and Google’s Security Key from Yubico. After a rigorous review process, both protocols are published now at version 1.0, and the FIDO Certified Testing program was launched in April 2015. And Microsoft announced that FIDO support would be built into Windows 10.
With its focus, pragmatism and membership breadth, FIDO is today’s go-to authentication standards effort. In this report, I look at what the FIDO Alliance has to offer vendors and end user communities, and its critical success factors.
I'm going to assume readers know what's meant by the "Creepy Test" in privacy. Here's a short appeal to use the Creepy Test sparingly and carefully.
The most obvious problem with the Creepy Test is its subjectivity. One person's "creepy" can be another person's "COOL!!". For example, a friend of mine thought it was cool when he used Google Maps to check out a hotel he was going to, and the software usefully reminded him of his check-in time (evidently, Google had scanned his gmail and mashed up the registration details next time he searched for the property). I actually thought this was way beyond creepy; imagine if it wasn't a hotel but a mental health facility, and Google was watching your psychiatric appointments.
In fact, for some people, creepy might actually be cool, in the same way as horror movies or chilli peppers are cool. There's already an implicit dare in the "Nothing To Hide" argument. Some brave souls seem to brag that they haven't done anything they don't mind being made public.
Our sense of what's creepy changes over time. We can get used to intrusive technologies, and that suits the agendas of infomoplists who make fortunes from personal data, hoping that we won't notice. On the other hand, objective and technology-neutral data privacy principles have been with us for over thirty years, and by and large, they work well to address contemporary problems like facial recognition, the cloud, and augmented reality glasses.
Using folksy terms in privacy might make the topic more accessible to laypeople, but it tends to distract from the technicalities of data privacy regulations. These are not difficult matters in the scheme of things; data privacy is technically about objective and reasonable controls on the collection, use and disclosure of personally identifiable information. I encourage anyone with an interest in privacy to spend time familiarising themselves with common Privacy Principles and the definition of Personal Information. And then it's easy to see that activities like Facebook's automated face recognition and Tag Suggestions aren't merely creepy; they are objectively unlawful!
Finally and most insideously, when emotive terms like creepy are used in debating public policy, it actually disempowers the critical voices. If "creepy" is the worst thing you can say about a given privacy concern, then you're marginalised.
We should avoid being subjective about privacy. By all means, let's use the Creepy Test to help spot potential privacy problems, and kick off a conversation. But as quickly as possible, we need to reduce privacy problems to objective criteria and, with cool heads, debate the appropriate responses.
See also A Theory of Creepy: Technology, Privacy and Shifting Social Norms by Omer Tene and Jules Polonetsky.
- "Alas, intuitions and perceptions of 'creepiness' are highly subjective and difficult to generalize as social norms are being strained by new technologies and capabilities". Tene & Polonetsky.
Facial recognition is digital alchemy. It's the prince of data mining.
Facial recognition takes previously anonymous images and conjures peoples' identities. It's an invaluable capability. Once they can pick out faces in crowds, trawling surreptitiously through anyone and everyone's photos, the social network businesses can work out what we're doing, when and where we're doing it, and who we're doing it with. The companies figure out what we like to do without us having to 'like' or favorite anything.
So Google, Facebook, Apple at al have invested hundreds of megabucks in face recognition R&D and buying technology start-ups. And they spend billions of dollars buying images and especially faces, going back to Google's acquisition of Picasa in 2004, and most recently, Facebook's ill-fated $3 billion offer for Snapchat.
But if most people find face recognition rather too creepy, then there is cause for optimism. The technocrats have gone too far. What many of them still don't get is this: If you take anonymous data (in the form of photos) and attach names to that data (which is what Facebook photo tagging does - it guesses who people are in photos are, attaches putative names to records, and invites users to confirm them) then you Collect Personal Information. Around the world, existing pre-biometrics era black letter Privacy Law says you can't Collect PII even indirectly like that without am express reason and without consent.
When automatic facial recognition converts anonymous data into PII, it crosses a bright line in the law.
A repeated refrain of cynics and “infomopolists” alike is that privacy is dead. People are supposed to know that anything on the Internet is up for grabs. In some circles this thinking turns into digital apartheid; some say if you’re so precious about your privacy, just stay offline.
But socialising and privacy are hardly mutually exclusive; we don’t walk around in public with our names tattooed on our foreheads. Why can’t we participate in online social networks in a measured, controlled way without submitting to the operators’ rampant X-ray vision? There is nothing inevitable about trading off privacy for conviviality.
The privacy dangers in Facebook and the like run much deeper than the self-harm done by some peoples’ overly enthusiastic sharing. Promiscuity is actually not the worst problem, neither is the notorious difficulty of navigating complex and ever changing privacy settings.
The advent of facial recognition presents far more serious and subtle privacy challenges.
Facebook has invested heavily in face recognition technology, and not just for fun. Facebook uses it in effect to crowd-source the identification and surveillance of its members. With facial recognition, Facebook is building up detailed pictures of what people do, when, where and with whom.
You can be tagged without consent in a photo taken and uploaded by a total stranger.
The majority of photos uploaded to personal albums over the years were not intended for anything other than private viewing.
Under the privacy law of Australia and data protection regulations in dozens of other jurisdictions, what matters is whether data is personally identifiable. The Commonwealth Privacy Act 1988 (as amended in 2014) defines “Personal Information” as: “information or an opinion about an identified individual, or an individual who is reasonably identifiable”.
Whenever Facebook attaches a member’s name to a photo, they are converting hitherto anonymous data into Personal Information, and in so doing, they become subject to privacy law. Automated facial recognition represents an indirect collection of Personal Information. However too many people still underestimate the privacy implications; some technologists naively claim that faces are “public” and that people can have no expectation of privacy in their facial images, ignoring that information privacy as explained is about the identifiability and identification of data; the words “public” and “private” don’t even figure in the Privacy Act!
If a government was stealing into our photo albums, labeling people and profiling them, there would be riots. It's high time that private sector surveillance - for profit - is seen for what it is, and stopped.
A Social Media Week Sydney event #SMWSydney
Law Lounge, Sydney University Law School
New Law School Building
Eastern Ave, Camperdown
Fri, Sep 26 - 10:00 AM - 11:30 AM
How can you navigate privacy fact and fiction, without the geeks and lawyers boring each other to death?
It's often said that technology has outpaced privacy law. Many digital businesses seem empowered by this brash belief. And so they proceed with apparent impunity to collect and monetise as much Personal Information as they can get their hands on.
But it's a myth!
Some of the biggest corporations in the world, including Google and Facebook, have been forcefully brought to book by privacy regulations. So, we have to ask ourselves:
- what does privacy law really mean for social media in Australia?
- is privacy "good for business"?
- is privacy "not a technology issue"?
- how can digital businesses navigate fact & fiction, without their geeks and lawyers boring each other to death?
In this Social Media Week Master Class I will:
- unpack what's "creepy" about certain online practices
- show how to rate data privacy issues objectively
- analyse classic misadventures with geolocation, facial recognition, and predicting when shoppers are pregnant
- critique photo tagging and crowd-sourced surveillance
- explain why Snapchat is worth more than three billion dollars
- analyse the regulatory implications of Big Data, Biometrics, Wearables and The Internet of Things.
We couldn't have timed this Master Class better, coming two weeks after the announcement of the Apple Watch, which will figure prominently in the class!
So please come along, for a fun and in-depth a look at social media, digital technology, the law, and decency.
About the presenter
Steve Wilson is a technologist, who stumbled into privacy 12 years ago. He rejected those well meaning slogans (like "Privacy Is Good For Business!") and instead dug into the relationships between information technology and information privacy. Now he researches and develops design patterns to help sort out privacy, alongside all the other competing requirements of security, cost, usability and revenue. His latest publications include:
- "Big Privacy: The new standard for Big Data Privacy" from Constellation Research, and
- "The collision between Big Data and privacy law" due out in October in the Australian Journal of Telecommunications and the Digital Economy.
The problem of identity takeover
The root cause of much identity theft and fraud today is the sad fact that customer reference numbers, personal identifiers and attributes generally are so easy to copy and replay without permission and without detection. Simple numerical attributes like bank account numbers and health IDs can be stolen from many different sources, and replayed with impunity in bogus transactions.
Our personal data nowadays is leaking more or less constantly, through breached databases, websites, online forms, call centres and so on, to such an extent that customer reference numbers on their own are no longer reliable. Privacy consequentially suffers because customers are required to assert their identity through circumstantial evidence, like name and address, birth date, mother’s maiden name and other pseudo secrets. All this data in turn is liable to be stolen and used against us, leading to spiraling identity fraud.
To restore the reliability of personal attribute data, we need to know their pedigree. We need to know that a presented data item is genuine, that it originated from a trusted authority, it’s been stored safely by its owner, and it’s been presented with the owner’s consent. If confidence in single attributes can be restored then we can step back from all the auxiliary proof-of-identity needed for routine transactions, and thus curb identity theft.
A practical response to ID theft
Several recent breaches of government registers leave citizens vulnerable to ID theft. In Korea, the national identity card system was attacked and it seems that all Korean's citizen IDs will have to be re-issued. In the US, Social Security Numbers are often stolen and used tin fraudulent identifications; recently, SSNs of 800,000 Post Office employees appear to have been stolen along with other personal records.
Update 14 June 2015: Now last week we got news of a hugely worse breach of US SSNs (not to mention deep personal records) of four million federal US government employees, when the Office of Personnel Management was hacked.
We could protect people against having their stolen identifiers used behind their backs. It shouldn't actually be necessary to re-issue every Korean's ID. Nor should it matter that US SSNs aren't usually replaceable. And great improvements may be made to the reliability of identification data presented online without dramatically changing Relying Parties' back-end processes. If for instance a service provider has always used SSN as part of its identification regime, they could continue to do so, if only the actual Social Security Numbers being received were known to be reliable.
The trick is to be able to tell "original" ID numbers from "copies". But what does "original" mean in the digital world? A more precise term for what we really want is pedigree. What we need is to be able to present attribute data in such a way that the receiver may be sure of their pedigree; that is, know that the attributes were originally issued by an authoritative body to the person presenting or claiming them, and that each presentation of an attribute has occurred under the owner's control.
These objectives can be met with the help of smart cryptographic technologies which today are built into most smart phones and smartcards, and which are finally being properly exploited by initiatives like the FIDO Alliance.
There are ways of issuing attributes to a smart chip device that prevent them from being stolen, copied and claimed by anyone else. One way to do so is to encapsulate and notarise attributes in a unique digital certificate issued to a chip. Today, a great many personal devices routinely embody cryptographically suitable chips for this purpose, including smart phones, SIM cards, "Secure Elements", smartcards and many wearable computers.
Consider an individual named Smith to whom Organisation A has issued a unique attribute N (which could be as simple as a customer reference number). If N is saved in ordinary computer memory or something like a magnetic stripe card, then it has no pedigree. Once the number N is presented by the cardholder in a transaction, it has the same properties as any other number. To better safeguard N in a chip device, it can be sealed into a digital certificate, as follows:
1. generate a fresh private-public key pair inside Smith’s chip
2. export the public key
3. create a digital certificate around the public key, with an attribute corresponding to N
4. have the certificate signed by (or on behalf of) organisation A.
The result of coordinating these processes and technologies is a logical triangle that inextricably binds cardholder Smith to her attribute N and to a specific personally controlled device. The certificate signed by organisation A attests to both Smith’s attribute value N and Smith's control of a particular device. Keys generated inside the chip are retained internally, never divulged to outsiders. It is not possible to copy the private key to another device, so the logical triangle cannot be reproduced or counterfeited.
Note that this technique is at the heart of the EMV "Chip-and-PIN" system where the smart payment card digitally signs cardholder and transaction data, rendering it immune to replay, before sending it to the merchant terminal. See also my 2012 paper Calling for a uniform approach to card fraud, offline and on. Now we should generalise notarised personal data and digitally signed transactions beyond Card-Present payments into as much online business as possible.
Restoring privacy and consumer control
When Smith wants to present her attribute N in an electronic transaction, instead of simply copying N out of memory (at which point it would lose its pedigree), Smith’s app digitally signs the transaction using the certificate containing N. With standard security software, anyone else can then verify that the transaction originated from a genuine device under Smith's control, with an attribute certified by A. And above all, this assurance is reliably made without needing to name Smith or reveal anything about her other than the attribute of interest.
Note that N doesn't have to be a customer number or numeric identifier; it could be any personal data, such as a biometric template, or a package of medical information like an allergy alert, or an isolated (and anonymous) property of the user, such as her age.
The capability to manage multiple key pairs and certificates, and to sign transactions with a nominated private key, is increasingly built into smart devices today. By narrowing down what you need to know about someone to a precise attribute or personal data item, we will reduce identity theft and fraud while radically improving privacy. This sort of privacy enhancing technology is the key to a safe Internet of Things, and it is now widely available.
Addressing ID theft
Perhaps the best thing governments could do immediately is to adopt smartcards and equivalent smart phone apps for holding and presenting such attributes as official ID numbers. The US government has actually come close to such a plan many times; Chip-based Social Security Cards and Medicare Cards have been proposed before, without realising their full potential. These devices would best be used as above to hold a citizen's identifiers and present them cryptographically, without vulnerability to ID theft and takeover. We wouldn't have to re-issue compromised SSNs; we would instead switch from manual presentation of these numbers to automatic online presentation, with a chip card or smart phone app conveying the data through digitally signatures.