MediaTech Law

By M STREET LEGAL

Apple Touts Differential Privacy, Privacy Wonks Remain Skeptic, Google Joins In

(Originally published January 19, 2017, updated July 24, 2017)

Apple has traditionally distinguished itself from its rivals, like Google and Facebook, by emphasizing its respect of user privacy. It has taken deliberate steps to avoid vacuuming up all of its users’ data, providing encryption at the device level as well as during data transmission. It has done so, however, at the cost of foregoing the benefits that pervasive data collection and analysis have to offer. Such benefits include improving on the growing and popular on-demand search and recommendation services, like Google Now and Microsoft’s Cortana and Amazon’s Echo. Like Apple’s Siri technology, these services act as a digital assistant, providing responses to search requests and making recommendations. Now Apple, pushing to remain competitive in this line of its business, is taking a new approach to privacy, in the form of differential privacy (DP).

Announced in June 2016 during Apple’s Worldwide Developers’ Conference in San Francisco, DP is, as Craig Federighi, senior vice president of software engineering, stated “a research topic in the area of statistics and data analytics that uses hashing, subsampling and noise injection to enable … crowdsourced learning while keeping the data of individual users completely private.” More simply put, DP is the statistical science of attempting to learn as much as possible about a group while learning as little as possible about any individual in it.

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Legal Issues in Ad Tech: De-Identified vs. Anonymized in a World of Big Data

In the booming world of Big Data, consumers, governments, and even companies are rightfully concerned about the protection and security of their data and how to keep one’s personal and potentially embarrassing details of life from falling into nefarious hands.   At the same time, most would recognize that Big Data can serve a valuable purpose, such as being used for lifesaving medical research and to improve commercial products. A question therefore at the center of this discussion is how, and if, data can be effectively “de-identified” or even “anonymized” to limit privacy concerns – and if the distinction between the two terms is more theoretical than practical. (As I mentioned in a prior post, “de-identified” data is data that has the possibility to be re-identified; while, at least in theory, anonymized data cannot be re-identified.)

Privacy of health data is particularly important and so the U.S. Health Insurance Portability and Accountability Act (HIPPA) includes strict rules on the use and disclosure of protected health information. These privacy constraints do not apply if the health data has been de-identified – either through a safe harbor-blessed process that removes 18 key identifiers or through a formal determination by a qualified expert, in either case presumably because these mechanisms are seen as a reasonable way to make it difficult to re-identify the data.

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“Do Not Track” and Cookies – European Commission Proposes New ePrivacy Regulations

The European Commission recently proposed new regulations that will align privacy rules for electronic communications with the much-anticipated General Data Protection Regulation (GDPR) (the GDPR was fully adopted in May 2016 and goes into effect in May 2018). Referred to as the Regulation on Privacy and Electronic Communications or “ePrivacy” regulation, these final additions to the EU’s new data protection framework make a number of important changes, including expanding privacy protections to over-the-top applications (like WhatsApp and Skype), requiring consent before metadata can be processed, and providing additional restrictions on SPAM. But the provisions relating to “cookies” and tracking of consumers online activity are particularly interesting and applicable to a wide-range of companies.

Cookies are small data files stored on a user’s computer or mobile device by a web browser. The files help websites remember information about the user and track a user’s online activity. Under the EU’s current ePrivacy Directive, a company must get a user’s specific consent before a cookie can be stored and accessed. While well-intentioned, this provision has caused frustration and resulted in consumers facing frequent pop-up windows (requesting consent) as they surf the Internet.

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Blogs and Writings We Like

This week we highlight 3 fine writers discussing timely subjects in media tech law: Beverly Berman writing about website terms of service and fair use, Leonard Gordon writing about “astroturfing” in advertising law, and John Buchanan and Dustin Cho writing about a gaping coverage gap with cybersecurity insurance.

Hot Topic: Fake News

Beverly Berneman’s timely post, “Hot Topic: Fake News” blog post (on the “IP News For Business” blog of Chicago firm Golan Christie Taglia), offers a simple cautionary tale about publishing your copyrighted artwork on the internet, or in this case publishing on a website (DeviantArt) promoting the works of visual artists. One such artist’s posting subsequently appeared for sale, unauthorized, on t-shirts promoted on the website of another company (Hot Topic). The aggrieved artist then sought recourse from DeviantArt. Berneman (like DeviantArt) pointed to DeviantArt’s terms of use, which prohibited downloading or using artwork for commercial purposes without permission from the copyright owner – leaving the artist with no claim against DeviantArt.

Berneman correctly highlights the need to read website terms of use before publishing your artwork on third party sites, especially if you expect that website to enforce piracy by other parties. Berneman also dismisses arguments about fair use made by some commentators about this case, adding “If Hot Topic used the fan art without the artist’s permission and for commercial purposes, it was not fair use.”

What we like: We like Berneman’s concise and spot-on guidance about the need to read website terms of use and, of course, when fair use is not “fair”. Plus her witty tie-in to “fake news”.

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NY AG Keeps up the Pressure on Astroturfing

Leonard Gordon, writing in Venable’s “All About Advertising Law” blog, offered a nice write-up of several recent settlements of “Astroturfing” enforcement actions by New York State’s Attorney General. First, what is Astroturfing? Gordon defines it as “the posting of fake reviews”, although blogger Sharyl Attkisson put it more vividly: “What’s most successful when it appears to be something it’s not? Astroturf. As in fake grassroots.” (And for the partisan spin on this, Attkisson follows that up with her personal conclusions as to who makes up the “Top 10 Astroturfers”, including “Moms Demand Action for Gun Sense in America and Everytown” and The Huffington Post. Ok now. But we digress ….)

The first case involved an urgent care provider (Medrite), which evidently contracted with freelancers and firms to write favorable reviews on sites like Yelp and Google Plus. Reviewers were not required to have been actual urgent care patients, nor were they required to disclose that they were compensated for their reviews.

The second case involved a car service (Carmel). The AG claimed that Carmel solicited favorable Yelp reviews from customers in exchange for discount cards on future use of the service. As with Medrite, reviewers were not required to disclose compensation for favorable reviews, and customers posting negative reviews were not given discount cards.

The settlements both involved monetary penalties and commitments against compensating reviewers without requiring the reviewers to disclose compensation. And in the Carmel settlement, Carmel took on affirmative obligations to educate its industry against conducting these practices.

What we like: We like Gordon’s commentary about this case, particularly its advisory conclusion: “Failure to do that could cause you to end up with a nasty case of “turf toe” from the FTC or an AG.” Very nice.

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Insurance Coverage Issues for Cyber-Physical Risks

John Buchanan and Dustin Cho write in Covington’s Inside Privacy blog about a gaping insurance coverage gap from risks to physical property from cybersecurity attacks, as opposed to the more familiar privacy breaches. Buchanan and Cho report on a recently published report from the U.S. Government’s National Institute of Standards and Technology (NIST), helpfully titled “Systems Security Engineering Considerations for a Multidisciplinary Approach in the Engineering of Trustworthy Secure Systems”. Rolls off the tongue.

The NIST report is a dense read (257 pages), and covers much more than insurance issues, in particular recommendations for improvements to system security engineering for (among other things) critical infrastructure, medical devices and hospital equipment and networked home devices (IoT or the Internet of Things).

Buchanan and Cho’s post addresses insurance issues, noting that “purchasers of cyber insurance are finding that nearly all of the available cyber insurance products expressly exclude coverage for physical bodily injury and property damage”.

What we like: Insurance is always an important and underappreciated business issue, with even less public understanding of the property and injury risks to (and coverage from) cyber damage. We like how Buchanan and Cho took the time to plow through an opaque government report to tell a simple and important story.

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Dataveillance Protection: The E.U.-U.S. Privacy Shield

For many years, technology outpaced policy when it came to standards and protections around ownership of and access to personal data. Privacy policies are not set by governments but rather by technology companies that created the digital world as it is experienced today. Many if not all of the dominant players in this space are American technology companies that include Alphabet (i.e. Google), Apple, Amazon, Facebook and Microsoft. These companies have more say about a user’s online life than any individual local, state or national government.

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Legal Issues in Ad Tech: IP Addresses Are Personal Data, Says the EU (well … sort of)

Much has been written in the past 2 weeks about the U.S. Presidential election. Time now for a diversion into the exciting world of data privacy and “personal data”. Because in the highly refined world of privacy and data security law, important news actually happened in the past few weeks. Yes, I speak breathlessly of the European Court of Justice (ECJ) decision on October 19th that IP (internet protocol) addresses are “Personal Data” for purposes of the EU Data Directive. This is bigly news (in the data privacy world, at least).

First, what the decision actually said, which leads immediately into a riveting discussion of the distinction between static and dynamic IP addresses.

The decision ruled on a case brought by a German politician named Patrick Breyer, who sought an injunction preventing a website and its owner – here, publicly available websites operated by the German government – from collecting and storing his IP address when he lawfully accessed the sites. Breyer claimed that the government’s actions were in violation of his privacy rights under the EU Directive 95/46/EC – The Data Protection Directive (Data Protection Directive). As the ECJ reported in its opinion, the government websites “register and store the IP addresses of visitors to those sites, together with the date and time when a site was accessed, with the aim of preventing cybernetic attacks and to make it possible to bring criminal proceedings.”

The case is Patrick Breyer v Bundesrepublik Deutschland, Case C-582/14, and the ECJ’s opinion was published on October 19th.

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Legal Issues in Ad Tech: Who Owns Marketing Performance Data?

Does a marketer own data related to performance of its own marketing campaigns? It might surprise marketers to know that data ownership isn’t automatically so. Or more broadly, who does own that data? A data rights clause in contracts with DSPs or agencies might state something like this:

“Client owns and retains all right, title and interest (including without limitation all intellectual property rights) in and to Client Data”,

… where “Client Data” is defined as “Client’s data files”. Or this:

“As between the Parties, Advertiser retains and shall have sole and exclusive ownership and Intellectual Property Rights in the … Performance Data”,

… where “Performance Data” means “campaign data related to the delivery and tracking of Advertiser’s digital advertising”.

Both clauses are vague, although the second is broader and more favorable to the marketer. In neither case are “data files” or “campaign data” defined with any particularity, and neither case includes any delivery obligation much less specifications for formatting, reporting or performance analytics. And even if data were provided by a vendor or agency, these other questions remain: What kind of data would be provided, how would it be provided, and how useful would the data be if it were provided?

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Legal Issues in Ad Tech: Anonymized and De-Identified Data

Recently, in reviewing a contract with a demand-side platform (DSP), this week, I came across this typical language in a “Data Ownership” section:

“All Performance Data shall be considered Confidential Information of Advertiser, provided that [VENDOR] may use such Performance Data … to create anonymized aggregated data, industry reports, and/or statistics (“Aggregated Data”) for its own commercial purposes, provided that Aggregated Data will not contain any information that identifies the Advertiser or any of its customers and does not contain the Confidential Information of the Advertiser or any intellectual property of the Advertiser or its customers.” (emphasis added).

I was curious what makes data “anonymized”, and I was even more curious whether the term was casually and improperly used. I’ve seen the same language alternately used substituting “de-identified” for “anonymized”. Looking into this opened a can of worms ….

What are Anonymized and De-Identified Data – and Are They the Same?

Here’s how Gregory Nelson described it in his casually titled “Practical Implications of Sharing Data: A Primer on Data Privacy, Anonymization, and De-Identification”:

“De-identification of data refers to the process of removing or obscuring any personally identifiable information from individual records in a way that minimizes the risk of unintended disclosure of the identity of individuals and information about them. Anonymization of data refers to the process of data de-identification that produces data where individual records cannot be linked back to an original as they do not include the required translation variables to do so.” (emphasis added)

Or in other words, both methods have the same purpose and both methods technically remove personally identifiable information (PII) from the data set. But while de-identified data can be re-identified, anonymized data cannot be re-identified. To use a simple example, if a column from an Excel spreadsheet containing Social Security numbers is removed from a dataset and discarded, the data would be “anonymized”.

But first … what aspects or portions of data must be removed in order to either de-identify or anonymize a set?

But What Makes Data “De-Identified” or “Anonymous” in the First Place?

Daniel Solove has written that, under the European Union’s Data Directive 95/46/EC, “Even if the data alone cannot be linked to a specific individual, if it is reasonably possible to use the data in combination with other information to identify a person, then the data is PII.” This makes things complicated in a hurry. After all, in the above example where Social Security numbers are removed, remaining columns might include normally non-PII information such as zip codes or gender (male or female). But the Harvard researchers Olivia Angiuli, Joe Blitzstein, and Jim Waldo show how even these 3 data points in an otherwise “de-identified” data set (i.e. “medical data” in the image below) can be used to re-identify individuals when combined with an outside data source that shares these same points (i.e. “voter list” in the image below):

Data Sets Overlap Chart

(Source: How to De-Identify Your Data, by Olivia Angiuli, Joe Blitzstein, and Jim Waldo, http://queue.acm.org/detail.cfm?id=2838930)

That helps explain the Advocate General opinion recently issued in the European Union Court of Justice (ECJ), finding that dynamic IP addresses can, under certain circumstances, be “personal data” under the European Union’s Data Directive 95/46/EC. Specifically, those circumstances. The case involves interpretation of the same point made by Daniel Solove cited above, namely discerning the “personal data” definition, including this formulation in Recital 26 of the Directive:

“(26) … whereas, to determine whether a person is identifiable, account should be taken of all the means likely reasonably to be used either by the controller or by any other person to identify the said person …”

There was inconsistency among the EU countries on the level of pro-activity required by a data controller in order to render an IP address “personal data”.   So, for example, the United Kingdom’s definition of “personal data” “data which relate to a living individual who can be identified – (a) from those data, or (b) from those data and other information which is in the possession of, or is likely to come into the possession of, the data controller” (emphasis added). Not so in Germany and, according to a White & Case report on the ECJ case, not so according to the Advocate General, whose position was that “the mere possibility that such a request [for further identifying information] could be made is sufficient.”

Which then circles things back to the question at the top, namely: Are Anonymized and De-Identified Data the Same? They are not the same. That part is easy to say. The harder part is determining which is which, especially with the ease of re-identifying presumably scrubbed data sets. More on this topic shortly.

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Appellate Court Upholds FTC’s Authority to Fine and Regulate Companies Shirking Cybersecurity

In a case determining the scope of the Federal Trade Commission’s (FTC) ability to govern data security, the 3rd U.S. Circuit Court of Appeals in Philadelphia upheld a 2014 ruling allowing the FTC to pursue a lawsuit against Wyndham Worldwide Corp. for failing to protect customer information after three data breaches that occurred in 2008 and 2009. The theft of credit card and personal details from over 600,000 consumers resulted in $10.6 million in fraudulent charges and the transfer of consumer account information to a website registered in Russia.

In 2012, the FTC sued Wyndham, which brands include Days Inn, Howard Johnson, Ramada, Super 8 and Travelodge. The basis of the claim stated that Wyndham’s conduct was an unfair practice and its privacy policy deceptive. The suit further alleged the company “engaged in unfair cybersecurity practices that unreasonably and unnecessarily exposed consumers’ personal data to unauthorized access and theft.”

The appellate court’s decision is of importance because it declares the FTC has the authority to regulate cybersecurity under the unfairness doctrine within §45 of the FTC Act. This doctrine allows the FTC to declare a business practice unfair if it is oppressive or harmful to consumers even though the practice is not an antitrust violation. Under this decision, the FTC has the authority to level civil penalties against companies convicted of engaging in unfair practices.

What exactly did Wyndham do to possibly merit the claim of unfair practices?

According to the FTC’s original complaint, the company:

  • allowed for the storing of payment card information in clear readable text;
  • allowed for the use of easily guessed password to access property management systems;
  • failed to use commonly available security measures, like firewalls, to limit access between hotel property management systems, corporate networks and the internet; and
  • failed to adequately restrict and measure unauthorized access to its network.

Furthermore, the FTC alleged the company’s privacy policy was deceptive, stating:

“a company does not act equitably when it publishes a privacy policy to attract customers who are concerned about data privacy, fails to make good on that promise by investing inadequate resources in cybersecurity, exposes its unsuspecting customers to substantial financial injury, and retains the profits of the business.”

Wyndham requested the suit be dismissed arguing the FTC did not have the authority to regulate cybersecurity. The appellate court found otherwise, however, stating that Wyndham failed to show that its alleged conduct fell outside the plain meaning of unfair.

The appellate court’s ruling highlights the need for companies to take special care in crafting a privacy policy to ensure it reflects the company’s cybersecurity standards and practices. This includes staying up-to-date on the latest best practices, and being familiar with the ever-changing industry standard security practices, including encryption and firewalls.

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What’s Behind the Decline in Internet Privacy Litigation?

The number of privacy lawsuits filed against big tech companies has significantly dropped in recent years, according to a review of court filings conducted by The Recorder, a California business journal.

According to The Recorder, the period 2010-2012 saw a dramatic spike in cases filed against Google, Apple, or Facebook (as measured by filings in the Northern District of California naming one of the three as defendants). The peak year was 2012, with 30 cases filed against the three tech giants, followed by a dramatic drop-off in 2014 and 2015, with only five privacy cases filed between the two years naming one of the three as defendants. So what explains the sudden drop off in privacy lawsuits?

One theory, according to privacy litigators interviewed for The Recorder article, is that the decline reflects the difficulty in applying federal privacy statutes to prosecute modern methods of monetizing, collecting, or disclosing online data. Many privacy class action claims are based on statutes passed in the 1980s like the Electronic Communications Privacy Act (ECPA), the Stored Communications Act (SCA), both passed in 1986, and the Video Privacy Protection Act (VPPA), passed in 1988. These statutes were originally written to address specific privacy intrusions like government wire taps or disclosures of video rental history.

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License Plate Numbers: a valuable data-point in big-data retention

What can you get from a license plate number?

At first glance, a person’s license plate number may not be considered that valuable a piece of information. When tied to a formal Motor Vehicle Administration (MVA) request it can yield the owner’s name, address, type of vehicle, vehicle identification number, and any lienholders associated with the vehicle. While this does reveal some sensitive information, such as a likely home address, there are generally easier ways to go about gathering that information. Furthermore, states have made efforts to protect such data, revealing owner information only to law enforcement officials or certified private investigators. The increasing use of Automated License Plate Readers (ALPRs), however, is proving to reveal a treasure trove of historical location information that is being used by law enforcement and private companies alike. Also, unlike historical MVA data, policies and regulations surrounding ALPRs are in their infancy and provide much lesser safeguards for protecting personal information.

ALPR – what is it?

Consisting of either a stationary or mobile-mounted camera, ALPRs use pattern recognition software to scan up to 1,800 license plates per minute, recording the time, date and location a particular car was encountered.

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