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Facial Recognition for People Wearing Masks

The Chinese facial recognition company Hanwang claims it can recognize people wearing masks:

The company now says its masked facial recognition program has reached 95 percent accuracy in lab tests, and even claims that it is more accurate in real life, where its cameras take multiple photos of a person if the first attempt to identify them fails.

[…]

Counter-intuitively, training facial recognition algorithms to recognize masked faces involves throwing data away. A team at the University of Bradford published a study last year showing they could train a facial recognition program to accurately recognize half-faces by deleting parts of the photos they used to train the software.

When a facial recognition program tries to recognize a person, it takes a photo of the person to be identified, and reduces it down to a bundle, or vector, of numbers that describes the relative positions of features on the face.

[…]

Hanwang’s system works for masked faces by trying to guess what all the faces in its existing database of photographs would look like if they were masked.

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Emergency Surveillance During COVID-19 Crisis

Israel is using emergency surveillance powers to track people who may have COVID-19, joining China and Iran in using mass surveillance in this way. I believe pressure will increase to leverage existing corporate surveillance infrastructure for these purposes in the US and other countries. With that in mind, the EFF has some good thinking on how to balance public safety with civil liberties:

Thus, any data collection and digital monitoring of potential carriers of COVID-19 should take into consideration and commit to these principles:

  • Privacy intrusions must be necessary and proportionate. A program that collects, en masse, identifiable information about people must be scientifically justified and deemed necessary by public health experts for the purpose of containment. And that data processing must be proportionate to the need. For example, maintenance of 10 years of travel history of all people would not be proportionate to the need to contain a disease like COVID-19, which has a two-week incubation period.

  • Data collection based on science, not bias. Given the global scope of communicable diseases, there is historical precedent for improper government containment efforts driven by bias based on nationality, ethnicity, religion, and race­ — rather than facts about a particular individual’s actual likelihood of contracting the virus, such as their travel history or contact with potentially infected people. Today, we must ensure that any automated data systems used to contain COVID-19 do not erroneously identify members of specific demographic groups as particularly susceptible to infection.

  • Expiration. As in other major emergencies in the past, there is a hazard that the data surveillance infrastructure we build to contain COVID-19 may long outlive the crisis it was intended to address. The government and its corporate cooperators must roll back any invasive programs created in the name of public health after crisis has been contained.

  • Transparency. Any government use of “big data” to track virus spread must be clearly and quickly explained to the public. This includes publication of detailed information about the information being gathered, the retention period for the information, the tools used to process that information, the ways these tools guide public health decisions, and whether these tools have had any positive or negative outcomes.

  • Due Process. If the government seeks to limit a person’s rights based on this “big data” surveillance (for example, to quarantine them based on the system’s conclusions about their relationships or travel), then the person must have the opportunity to timely and fairly challenge these conclusions and limits.

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More on Crypto AG

One follow-on to the story of Crypto AG being owned by the CIA: this interview with a Washington Post reporter. The whole thing is worth reading or listening to, but I was struck by these two quotes at the end:

…in South America, for instance, many of the governments that were using Crypto machines were engaged in assassination campaigns. Thousands of people were being disappeared, killed. And I mean, they’re using Crypto machines, which suggests that the United States intelligence had a lot of insight into what was happening. And it’s hard to look back at that history now and see a lot of evidence of the United States going to any real effort to stop it or at least or even expose it.

[…]

To me, the history of the Crypto operation helps to explain how U.S. spy agencies became accustomed to, if not addicted to, global surveillance. This program went on for more than 50 years, monitoring the communications of more than 100 countries. I mean, the United States came to expect that kind of penetration, that kind of global surveillance capability. And as Crypto became less able to deliver it, the United States turned to other ways to replace that. And the Snowden documents tell us a lot about how they did that.

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Security of Health Information

The world is racing to contain the new COVID-19 virus that is spreading around the globe with alarming speed. Right now, pandemic disease experts at the World Health Organization (WHO), the US Centers for Disease Control and Prevention (CDC), and other public-health agencies are gathering information to learn how and where the virus is spreading. To do so, they are using a variety of digital communications and surveillance systems. Like much of the medical infrastructure, these systems are highly vulnerable to hacking and interference.

That vulnerability should be deeply concerning. Governments and intelligence agencies have long had an interest in manipulating health information, both in their own countries and abroad. They might do so to prevent mass panic, avert damage to their economies, or avoid public discontent (if officials made grave mistakes in containing an outbreak, for example). Outside their borders, states might use disinformation to undermine their adversaries or disrupt an alliance between other nations. A sudden epidemic­ — when countries struggle to manage not just the outbreak but its social, economic, and political fallout­ — is especially tempting for interference.

In the case of COVID-19, such interference is already well underway. That fact should not come as a surprise. States hostile to the West have a long track record of manipulating information about health issues to sow distrust. In the 1980s, for example, the Soviet Union spread the false story that the US Department of Defense bioengineered HIV in order to kill African Americans. This propaganda was effective: some 20 years after the original Soviet disinformation campaign, a 2005 survey found that 48 percent of African Americans believed HIV was concocted in a laboratory, and 15 percent thought it was a tool of genocide aimed at their communities.

More recently, in 2018, Russia undertook an extensive disinformation campaign to amplify the anti-vaccination movement using social media platforms like Twitter and Facebook. Researchers have confirmed that Russian trolls and bots tweeted anti-vaccination messages at up to 22 times the rate of average users. Exposure to these messages, other researchers found, significantly decreased vaccine uptake, endangering individual lives and public health.

Last week, US officials accused Russia of spreading disinformation about COVID-19 in yet another coordinated campaign. Beginning around the middle of January, thousands of Twitter, Facebook, and Instagram accounts­ — many of which had previously been tied to Russia­ — had been seen posting nearly identical messages in English, German, French, and other languages, blaming the United States for the outbreak. Some of the messages claimed that the virus is part of a US effort to wage economic war on China, others that it is a biological weapon engineered by the CIA.

As much as this disinformation can sow discord and undermine public trust, the far greater vulnerability lies in the United States’ poorly protected emergency-response infrastructure, including the health surveillance systems used to monitor and track the epidemic. By hacking these systems and corrupting medical data, states with formidable cybercapabilities can change and manipulate data right at the source.

Here is how it would work, and why we should be so concerned. Numerous health surveillance systems are monitoring the spread of COVID-19 cases, including the CDC’s influenza surveillance network. Almost all testing is done at a local or regional level, with public-health agencies like the CDC only compiling and analyzing the data. Only rarely is an actual biological sample sent to a high-level government lab. Many of the clinics and labs providing results to the CDC no longer file reports as in the past, but have several layers of software to store and transmit the data.

Potential vulnerabilities in these systems are legion: hackers exploiting bugs in the software, unauthorized access to a lab’s servers by some other route, or interference with the digital communications between the labs and the CDC. That the software involved in disease tracking sometimes has access to electronic medical records is particularly concerning, because those records are often integrated into a clinic or hospital’s network of digital devices. One such device connected to a single hospital’s network could, in theory, be used to hack into the CDC’s entire COVID-19 database.

In practice, hacking deep into a hospital’s systems can be shockingly easy. As part of a cybersecurity study, Israeli researchers at Ben-Gurion University were able to hack into a hospital’s network via the public Wi-Fi system. Once inside, they could move through most of the hospital’s databases and diagnostic systems. Gaining control of the hospital’s unencrypted image database, the researchers inserted malware that altered healthy patients’ CT scans to show nonexistent tumors. Radiologists reading these images could only distinguish real from altered CTs 60 percent of the time­ — and only after being alerted that some of the CTs had been manipulated.

Another study directly relevant to public-health emergencies showed that a critical US biosecurity initiative, the Department of Homeland Security’s BioWatch program, had been left vulnerable to cyberattackers for over a decade. This program monitors more than 30 US jurisdictions and allows health officials to rapidly detect a bioweapons attack. Hacking this program could cover up an attack, or fool authorities into believing one has occurred.

Fortunately, no case of healthcare sabotage by intelligence agencies or hackers has come to light (the closest has been a series of ransomware attacks extorting money from hospitals, causing significant data breaches and interruptions in medical services). But other critical infrastructure has often been a target. The Russians have repeatedly hacked Ukraine’s national power grid, and have been probing US power plants and grid infrastructure as well. The United States and Israel hacked the Iranian nuclear program, while Iran has targeted Saudi Arabia’s oil infrastructure. There is no reason to believe that public-health infrastructure is in any way off limits.

Despite these precedents and proven risks, a detailed assessment of the vulnerability of US health surveillance systems to infiltration and manipulation has yet to be made. With COVID-19 on the verge of becoming a pandemic, the United States is at risk of not having trustworthy data, which in turn could cripple our country’s ability to respond.

Under normal conditions, there is plenty of time for health officials to notice unusual patterns in the data and track down wrong information­ — if necessary, using the old-fashioned method of giving the lab a call. But during an epidemic, when there are tens of thousands of cases to track and analyze, it would be easy for exhausted disease experts and public-health officials to be misled by corrupted data. The resulting confusion could lead to misdirected resources, give false reassurance that case numbers are falling, or waste precious time as decision makers try to validate inconsistent data.

In the face of a possible global pandemic, US and international public-health leaders must lose no time assessing and strengthening the security of the country’s digital health systems. They also have an important role to play in the broader debate over cybersecurity. Making America’s health infrastructure safe requires a fundamental reorientation of cybersecurity away from offense and toward defense. The position of many governments, including the United States’, that Internet infrastructure must be kept vulnerable so they can better spy on others, is no longer tenable. A digital arms race, in which more countries acquire ever more sophisticated cyberattack capabilities, only increases US vulnerability in critical areas such as pandemic control. By highlighting the importance of protecting digital health infrastructure, public-health leaders can and should call for a well-defended and peaceful Internet as a foundation for a healthy and secure world.

This essay was co-authored with Margaret Bourdeaux; a slightly different version appeared in Foreign Policy.

EDITED TO ADD: On last week’s squid post, there was a big conversation regarding the COVID-19. Many of the comments straddled the line between what are and aren’t the the core topics. Yesterday I deleted a bunch for being off-topic. Then I reconsidered and republished some of what I deleted.

Going forward, comments about the COVID-19 will be restricted to the security and risk implications of the virus. This includes cybersecurity, security, risk management, surveillance, and containment measures. Comments that stray off those topics will be removed. By clarifying this, I hope to keep the conversation on-topic while also allowing discussion of the security implications of current events.

Thank you for your patience and forbearance on this.

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Facebook’s Download-Your-Data Tool Is Incomplete

Privacy International has the details:

Key facts:

  • Despite Facebook claim, “Download Your Information” doesn’t provide users with a list of all advertisers who uploaded a list with their personal data.
  • As a user this means you can’t exercise your rights under GDPR because you don’t know which companies have uploaded data to Facebook.
  • Information provided about the advertisers is also very limited (just a name and no contact details), preventing users from effectively exercising their rights.
  • Recently announced Off-Facebook feature comes with similar issues, giving little insight into how advertisers collect your personal data and how to prevent such data collection.

When I teach cybersecurity tech and policy at the Harvard Kennedy School, one of the assignments is to download your Facebook and Google data and look at it. Many are surprised at what the companies know about them.

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Apple’s Tracking-Prevention Feature in Safari has a Privacy Bug

Last month, engineers at Google published a very curious privacy bug in Apple’s Safari web browser. Apple’s Intelligent Tracking Prevention, a feature designed to reduce user tracking, has vulnerabilities that themselves allow user tracking. Some details:

ITP detects and blocks tracking on the web. When you visit a few websites that happen to load the same third-party resource, ITP detects the domain hosting the resource as a potential tracker and from then on sanitizes web requests to that domain to limit tracking. Tracker domains are added to Safari’s internal, on-device ITP list. When future third-party requests are made to a domain on the ITP list, Safari will modify them to remove some information it believes may allow tracking the user (such as cookies).

[…]

The details should come as a surprise to everyone because it turns out that ITP could effectively be used for:

  • information leaks: detecting websites visited by the user (web browsing history hijacking, stealing a list of visited sites)
  • tracking the user with ITP, making the mechanism function like a cookie
  • fingerprinting the user: in ways similar to the HSTS fingerprint, but perhaps a bit better

I am sure we all agree that we would not expect a privacy feature meant to protect from tracking to effectively enable tracking, and also accidentally allowing any website out there to steal its visitors’ web browsing history. But web architecture is complex, and the consequence is that this is exactly the case.

Apple fixed this vulnerability in December, a month before Google published.

If there’s any lesson here, it’s that privacy is hard — and that privacy engineering is even harder. It’s not that we shouldn’t try, but we should recognize that it’s easy to get it wrong.

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New Research on the Adtech Industry

The Norwegian Consumer Council has published an extensive report about how the adtech industry violates consumer privacy. At the same time, it is filing three legal complaints against six companies in this space. From a Twitter summary:

1. [thread] We are filing legal complaints against six companies based on our research, revealing systematic breaches to privacy, by shadowy #OutOfControl #adtech companies gathering & sharing heaps of personal data. https://forbrukerradet.no/out-of-control/#GDPR… #privacy

2. We observed how ten apps transmitted user data to at least 135 different third parties involved in advertising and/or behavioural profiling, exposing (yet again) a vast network of companies monetizing user data and using it for their own purposes.

3. Dating app @Grindr shared detailed user data with a large number of third parties. Data included the fact that you are using the app (clear indication of sexual orientation), IP address (personal data), Advertising ID, GPS location (very revealing), age, and gender.

From a news article:

The researchers also reported that the OkCupid app sent a user’s ethnicity and answers to personal profile questions — like “Have you used psychedelic drugs?” — to a firm that helps companies tailor marketing messages to users. The Times found that the OkCupid site had recently posted a list of more than 300 advertising and analytics “partners” with which it may share users’ information.

This is really good research exposing the inner workings of a very secretive industry.

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Customer Tracking at Ralphs Grocery Store

To comply with California’s new data privacy law, companies that collect information on consumers and users are forced to be more transparent about it. Sometimes the results are creepy. Here’s an article about Ralphs, a California supermarket chain owned by Kroger:

…the form proceeds to state that, as part of signing up for a rewards card, Ralphs “may collect” information such as “your level of education, type of employment, information about your health and information about insurance coverage you might carry.”

It says Ralphs may pry into “financial and payment information like your bank account, credit and debit card numbers, and your credit history.”

Wait, it gets even better.

Ralphs says it’s gathering “behavioral information” such as “your purchase and transaction histories” and “geolocation data,” which could mean the specific Ralphs aisles you browse or could mean the places you go when not shopping for groceries, thanks to the tracking capability of your smartphone.

Ralphs also reserves the right to go after “information about what you do online” and says it will make “inferences” about your interests “based on analysis of other information we have collected.”

Other information? This can include files from “consumer research firms” ­– read: professional data brokers ­– and “public databases,” such as property records and bankruptcy filings.

The reaction from John Votava, a Ralphs spokesman:

“I can understand why it raises eyebrows,” he said. We may need to change the wording on the form.”

That’s the company’s solution. Don’t spy on people less, just change the wording so they don’t realize it.

More consumer protection laws will be required.

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Google Receives Geofence Warrants

Sometimes it’s hard to tell the corporate surveillance operations from the government ones:

Google reportedly has a database called Sensorvault in which it stores location data for millions of devices going back almost a decade.

The article is about geofence warrants, where the police go to companies like Google and ask for information about every device in a particular geographic area at a particular time. In 2013, we learned from Edward Snowden that the NSA does this worldwide. Its program is called CO-TRAVELLER. The NSA claims it stopped doing that in 2014 — probably just stopped doing it in the US — but why should it bother when the government can just get the data from Google.

Both the New York Times and EFF have written about Sensorvault.

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Modern Mass Surveillance: Identify, Correlate, Discriminate

Communities across the United States are starting to ban facial recognition technologies. In May of last year, San Francisco banned facial recognition; the neighboring city of Oakland soon followed, as did Somerville and Brookline in Massachusetts (a statewide ban may follow). In December, San Diego suspended a facial recognition program in advance of a new statewide law, which declared it illegal, coming into effect. Forty major music festivals pledged not to use the technology, and activists are calling for a nationwide ban. Many Democratic presidential candidates support at least a partial ban on the technology.

These efforts are well-intentioned, but facial recognition bans are the wrong way to fight against modern surveillance. Focusing on one particular identification method misconstrues the nature of the surveillance society we’re in the process of building. Ubiquitous mass surveillance is increasingly the norm. In countries like China, a surveillance infrastructure is being built by the government for social control. In countries like the United States, it’s being built by corporations in order to influence our buying behavior, and is incidentally used by the government.

In all cases, modern mass surveillance has three broad components: identification, correlation and discrimination. Let’s take them in turn.

Facial recognition is a technology that can be used to identify people without their knowledge or consent. It relies on the prevalence of cameras, which are becoming both more powerful and smaller, and machine learning technologies that can match the output of these cameras with images from a database of existing photos.

But that’s just one identification technology among many. People can be identified at a distance by their heartbeat or by their gait, using a laser-based system. Cameras are so good that they can read fingerprints and iris patterns from meters away. And even without any of these technologies, we can always be identified because our smartphones broadcast unique numbers called MAC addresses. Other things identify us as well: our phone numbers, our credit card numbers, the license plates on our cars. China, for example, uses multiple identification technologies to support its surveillance state.

Once we are identified, the data about who we are and what we are doing can be correlated with other data collected at other times. This might be movement data, which can be used to “follow” us as we move throughout our day. It can be purchasing data, Internet browsing data, or data about who we talk to via email or text. It might be data about our income, ethnicity, lifestyle, profession and interests. There is an entire industry of data brokers who make a living analyzing and augmenting data about who we are ­– using surveillance data collected by all sorts of companies and then sold without our knowledge or consent.

There is a huge ­– and almost entirely unregulated ­– data broker industry in the United States that trades on our information. This is how large Internet companies like Google and Facebook make their money. It’s not just that they know who we are, it’s that they correlate what they know about us to create profiles about who we are and what our interests are. This is why many companies buy license plate data from states. It’s also why companies like Google are buying health records, and part of the reason Google bought the company Fitbit, along with all of its data.

The whole purpose of this process is for companies –­ and governments ­– to treat individuals differently. We are shown different ads on the Internet and receive different offers for credit cards. Smart billboards display different advertisements based on who we are. In the future, we might be treated differently when we walk into a store, just as we currently are when we visit websites.

The point is that it doesn’t matter which technology is used to identify people. That there currently is no comprehensive database of heartbeats or gaits doesn’t make the technologies that gather them any less effective. And most of the time, it doesn’t matter if identification isn’t tied to a real name. What’s important is that we can be consistently identified over time. We might be completely anonymous in a system that uses unique cookies to track us as we browse the Internet, but the same process of correlation and discrimination still occurs. It’s the same with faces; we can be tracked as we move around a store or shopping mall, even if that tracking isn’t tied to a specific name. And that anonymity is fragile: If we ever order something online with a credit card, or purchase something with a credit card in a store, then suddenly our real names are attached to what was anonymous tracking information.

Regulating this system means addressing all three steps of the process. A ban on facial recognition won’t make any difference if, in response, surveillance systems switch to identifying people by smartphone MAC addresses. The problem is that we are being identified without our knowledge or consent, and society needs rules about when that is permissible.

Similarly, we need rules about how our data can be combined with other data, and then bought and sold without our knowledge or consent. The data broker industry is almost entirely unregulated; there’s only one law ­– passed in Vermont in 2018 ­– that requires data brokers to register and explain in broad terms what kind of data they collect. The large Internet surveillance companies like Facebook and Google collect dossiers on us are more detailed than those of any police state of the previous century. Reasonable laws would prevent the worst of their abuses.

Finally, we need better rules about when and how it is permissible for companies to discriminate. Discrimination based on protected characteristics like race and gender is already illegal, but those rules are ineffectual against the current technologies of surveillance and control. When people can be identified and their data correlated at a speed and scale previously unseen, we need new rules.

Today, facial recognition technologies are receiving the brunt of the tech backlash, but focusing on them misses the point. We need to have a serious conversation about all the technologies of identification, correlation and discrimination, and decide how much we as a society want to be spied on by governments and corporations — and what sorts of influence we want them to have over our lives.

This essay previously appeared in the New York Times.

EDITED TO ADD: Rereading this post-publication, I see that it comes off as overly critical of those who are doing activism in this space. Writing the piece, I wasn’t thinking about political tactics. I was thinking about the technologies that support surveillance capitalism, and law enforcement’s usage of that corporate platform. Of course it makes sense to focus on face recognition in the short term. It’s something that’s easy to explain, viscerally creepy, and obviously actionable. It also makes sense to focus specifically on law enforcement’s use of the technology; there are clear civil and constitutional rights issues. The fact that law enforcement is so deeply involved in the technology’s marketing feels wrong. And the technology is currently being deployed in Hong Kong against political protesters. It’s why the issue has momentum, and why we’ve gotten the small wins we’ve had. (The EU is considering a five-year ban on face recognition technologies.) Those wins build momentum, which lead to more wins. I should have been kinder to those in the trenches.

If you want to help, sign the petition from Public Voice calling on a moratorium on facial recognition technology for mass surveillance. Or write to your US congressperson and demand similar action. There’s more information from EFF and EPIC.

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