Abstract: Cloud photo services are widely used for persistent, convenient, and often free photo storage, which is especially useful for mobile devices. As users store more and more photos in the cloud, significant privacy concerns arise because even a single compromise of a user’s credentials give attackers unfettered access to all of the user’s photos. We have created Easy Secure Photos (ESP) to enable users to protect their photos on cloud photo services such as Google Photos. ESP introduces a new client-side encryption architecture that includes a novel format-preserving image encryption algorithm, an encrypted thumbnail display mechanism, and a usable key management system. ESP encrypts image data such that the result is still a standard format image like JPEG that is compatible with cloud photo services. ESP efficiently generates and displays encrypted thumbnails for fast and easy browsing of photo galleries from trusted user devices. ESP’s key management makes it simple to authorize multiple user devices to view encrypted image content via a process similar to device pairing, but using the cloud photo service as a QR code communication channel. We have implemented ESP in a popular Android photos app for use with Google Photos and demonstrate that it is easy to use and provides encryption functionality transparently to users, maintains good interactive performance and image quality while providing strong privacy guarantees, and retains the sharing and storage benefits of Google Photos without any changes to the cloud service
In order to develop a practical quantum computer, scientists will have to design ways to deal with any errors that will inevitably pop up in its performance. Now Google has demonstrated that exponential suppression of such errors is possible, experiments that may help pave the way for scalable, fault-tolerant quantum computers.
A quantum computer with enough components known as quantum bits or “qubits” could in theory achieve a “quantum advantage” allowing it to find the answers to problems no classical computer could ever solve.
However, a critical drawback of current quantum computers is the way in which their inner workings are prone to errors. Current state-of-the-art quantum platforms typically have error rates near 10^-3 (or one in a thousand), but many practical applications call for error rates as low as 10^-15.
This blog was co-authored by Caitlin Condon, VRM Security Research Manager, and Bob Rudis, Senior Director and Chief Security Data Scientist.
On Monday, Jan. 25, 2021, Google’s Threat Analysis Group (TAG) published a blog on a widespread social engineering campaign that targeted security researchers working on vulnerability research and development. The campaign, which Google attributed to North Korean (DPRK) state-sponsored actors, has been active for several months and sought to compromise researchers using several methods.
Rapid7 is aware that many security researchers were targeted in this campaign, and information is still developing. While we currently have no evidence that we were compromised, we are continuing to investigate logs and examine our systems for any of the IOCs listed in Google’s analysis. We will update this post with further information as it becomes available.
Organizations should take note that this was a highly sophisticated attack that was important enough to those who orchestrated it for them to burn an as-yet unknown exploit path on. This event is the latest in a chain of attacks—e.g., those targeting SonicWall, VMware, Mimecast, Malwarebytes, Microsoft, Crowdstrike, and SolarWinds—that demonstrates a significant increase in threat activity targeting cybersecurity firms with legitimately sophisticated campaigns. Scenarios like these should become standard components of tabletop exercises and active defense plans.
North Korean-attributed social engineering campaign
Google discovered that the DPRK threat actors had built credibility by establishing a vulnerability research blog and several Twitter profiles to interact with potential targets. They published videos of their alleged exploits, including a YouTube video of a fake proof-of-concept (PoC) exploit for CVE-2021-1647—a high-profile Windows Defender zero-day vulnerability that garnered attention from both security researchers and the media. The DPRK actors also published “guest” research (likely plagiarized from other researchers) on their blog to further build their reputation.
The malicious actors then used two methods to social engineer targets into accepting malware or visiting a malicious website. According to Google:
After establishing initial communications, the actors would ask the targeted researcher if they wanted to collaborate on vulnerability research together, and then provide the researcher with a Visual Studio Project. Within the Visual Studio Project would be source code for exploiting the vulnerability, as well as an additional pre-compiled library (DLL) that would be executed through Visual Studio Build Events. The DLL is custom malware that would immediately begin communicating with actor-controlled command and control (C2) domains.
In addition to targeting users via social engineering, Google also observed several cases where researchers have been compromised after visiting the actors’ blog. In each of these cases, the researchers followed a link on Twitter to a write-up hosted on blog[.]br0vvnn[.]io, and shortly thereafter, a malicious service was installed on the researcher’s system and an in-memory backdoor would begin beaconing to an actor-owned command and control server. At the time of these visits, the victim systems were running fully patched and up-to-date Windows 10 and Chrome browser versions. As of Jan. 26, 2021, Google was unable to confirm the mechanism of compromise.
The blog the DPRK threat actors used to execute this zero-day drive-by attack was posted on Reddit as long as three months ago. The actors also used a range of social media and communications platforms to interact with targets—including Telegram, Keybase, Twitter, LinkedIn, and Discord. As of Jan. 26, 2021, many of these profiles have been suspended or deactivated.
Google’s threat intelligence includes information on IOCs, command-and-control domains, actor-controlled social media accounts, and compromised domains used as part of the campaign. Rapid7’s MDR team is deploying IOCs and behavior-based detections. These detections will also be available to InsightIDR customers later today. We will update this blog post with further information as it becomes available.
TAG noted in their blog post that they have so far only seen actors targeting Windows systems. As of the evening of Jan. 25, 2021, researchers across many companies confirmed on Twitter that they had interacted with the DPRK actors and/or visited the malicious blog. Organizations that believe their researchers or other employees may have been targeted should conduct internal investigations to determine whether indicators of compromise are present on their networks.
At a minimum, responders should:
Ensure members of all security teams are aware of this campaign and encourage individuals to report if they believe they were targeted by these actors.
Search web traffic, firewall, and DNS logs for evidence of contacts to the domains and URLs provided by Google in their post.
According to Rapid7 Labs’ forward DNS archive, the br0vvnn[.]io apex domain has had two discovered fully qualified domain names (FQDNs)—api[.]br0vvnn[.]io and blog[.]br0vvnn[.]io—over the past four months with IP addresses 192[.]169[.]6[.]31 and 192[.]52[.]167[.]169, respectively. Contacts to those IPs should also be investigated in historical access records.
Check for evidence of the provided hashes on all systems, starting with those operated and accessed by members of security teams.
Moving forward, organizations and individuals should heed Google’s advice that “if you are concerned that you are being targeted, we recommend that you compartmentalize your research activities using separate physical or virtual machines for general web browsing, interacting with others in the research community, accepting files from third parties and your own security research.”
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Google’s Project Zero has exposed a sophisticated watering-hole attack targeting both Windows and Android:
Some of the exploits were zero-days, meaning they targeted vulnerabilities that at the time were unknown to Google, Microsoft, and most outside researchers (both companies have since patched the security flaws). The hackers delivered the exploits through watering-hole attacks, which compromise sites frequented by the targets of interest and lace the sites with code that installs malware on visitors’ devices. The boobytrapped sites made use of two exploit servers, one for Windows users and the other for users of Android
The use of zero-days and complex infrastructure isn’t in itself a sign of sophistication, but it does show above-average skill by a professional team of hackers. Combined with the robustness of the attack code — which chained together multiple exploits in an efficient manner — the campaign demonstrates it was carried out by a “highly sophisticated actor.”
The modularity of the payloads, the interchangeable exploit chains, and the logging, targeting, and maturity of the operation also set the campaign apart, the researcher said.
No attribution was made, but the list of countries likely to be behind this isn’t very large. If you were to ask me to guess based on available information, I would guess it was the US — specifically, the NSA. It shows a care and precision that it’s known for. But I have no actual evidence for that guess.
The cloning works by using a hot air gun and a scalpel to remove the plastic key casing and expose the NXP A700X chip, which acts as a secure element that stores the cryptographic secrets. Next, an attacker connects the chip to hardware and software that take measurements as the key is being used to authenticate on an existing account. Once the measurement-taking is finished, the attacker seals the chip in a new casing and returns it to the victim.
Extracting and later resealing the chip takes about four hours. It takes another six hours to take measurements for each account the attacker wants to hack. In other words, the process would take 10 hours to clone the key for a single account, 16 hours to clone a key for two accounts, and 22 hours for three accounts.
By observing the local electromagnetic radiations as the chip generates the digital signatures, the researchers exploit a side channel vulnerability in the NXP chip. The exploit allows an attacker to obtain the long-term elliptic curve digital signal algorithm private key designated for a given account. With the crypto key in hand, the attacker can then create her own key, which will work for each account she targeted.
The attack isn’t free, but it’s not expensive either:
A hacker would first have to steal a target’s account password and also gain covert possession of the physical key for as many as 10 hours. The cloning also requires up to $12,000 worth of equipment and custom software, plus an advanced background in electrical engineering and cryptography. That means the key cloning — were it ever to happen in the wild — would likely be done only by a nation-state pursuing its highest-value targets.
That last line about “nation-state pursuing its highest-value targets” is just not true. There are many other situations where this attack is feasible.
Note that the attack isn’t against the Google system specifically. It exploits a side-channel attack in the NXP chip. Which means that other systems are probably vulnerable:
While the researchers performed their attack on the Google Titan, they believe that other hardware that uses the A700X, or chips based on the A700X, may also be vulnerable. If true, that would include Yubico’s YubiKey NEO and several 2FA keys made by Feitian.
Researchers at the time said that they were able to launch inaudible commands by shining lasers — from as far as 360 feet — at the microphones on various popular voice assistants, including Amazon Alexa, Apple Siri, Facebook Portal, and Google Assistant.
They broadened their research to show how light can be used to manipulate a wider range of digital assistants — including Amazon Echo 3 — but also sensing systems found in medical devices, autonomous vehicles, industrial systems and even space systems.
The researchers also delved into how the ecosystem of devices connected to voice-activated assistants — such as smart-locks, home switches and even cars — also fail under common security vulnerabilities that can make these attacks even more dangerous. The paper shows how using a digital assistant as the gateway can allow attackers to take control of other devices in the home: Once an attacker takes control of a digital assistant, he or she can have the run of any device connected to it that also responds to voice commands. Indeed, these attacks can get even more interesting if these devices are connected to other aspects of the smart home, such as smart door locks, garage doors, computers and even people’s cars, they said.
Another article. The researchers will present their findings at Black Hat Europe — which, of course, will be happening virtually — on December 10.
One of the things we learned from the Snowden documents is that the NSA conducts “about” searches. That is, searches based on activities and not identifiers. A normal search would be on a name, or IP address, or phone number. An about search would something like “show me anyone that has used this particular name in a communications,” or “show me anyone who was at this particular location within this time frame.” These searches are legal when conducted for the purpose of foreign surveillance, but the worry about using them domestically is that they are unconstitutionally broad. After all, the only way to know who said a particular name is to know what everyone said, and the only way to know who was at a particular location is to know where everyone was. The very nature of these searches requires mass surveillance.
The FBI does not conduct mass surveillance. But many US corporations do, as a normal part of their business model. And the FBI uses that surveillance infrastructure to conduct its own about searches. Here’s an arson case where the FBI asked Google who searched for a particular street address:
Homeland Security special agent Sylvette Reynoso testified that her team began by asking Google to produce a list of public IP addresses used to google the home of the victim in the run-up to the arson. The Chocolate Factory [Google] complied with the warrant, and gave the investigators the list. As Reynoso put it:
On June 15, 2020, the Honorable Ramon E. Reyes, Jr., United States Magistrate Judge for the Eastern District of New York, authorized a search warrant to Google for users who had searched the address of the Residence close in time to the arson.
The records indicated two IPv6 addresses had been used to search for the address three times: one the day before the SUV was set on fire, and the other two about an hour before the attack. The IPv6 addresses were traced to Verizon Wireless, which told the investigators that the addresses were in use by an account belonging to Williams.
Google’s response is that this is rare:
While word of these sort of requests for the identities of people making specific searches will raise the eyebrows of privacy-conscious users, Google told The Register the warrants are a very rare occurrence, and its team fights overly broad or vague requests.
“We vigorously protect the privacy of our users while supporting the important work of law enforcement,” Google’s director of law enforcement and information security Richard Salgado told us. “We require a warrant and push to narrow the scope of these particular demands when overly broad, including by objecting in court when appropriate.
“These data demands represent less than one per cent of total warrants and a small fraction of the overall legal demands for user data that we currently receive.”
Here’s another example of what seems to be about data leading to a false arrest.
According to the lawsuit, police investigating the murder knew months before they arrested Molina that the location data obtained from Google often showed him in two places at once, and that he was not the only person who drove the Honda registered under his name.
Avondale police knew almost two months before they arrested Molina that another man his stepfather sometimes drove Molina’s white Honda. On October 25, 2018, police obtained records showing that Molina’s Honda had been impounded earlier that year after Molina’s stepfather was caught driving the car without a license.
Data obtained by Avondale police from Google did show that a device logged into Molina’s Google account was in the area at the time of Knight’s murder. Yet on a different date, the location data from Google also showed that Molina was at a retirement community in Scottsdale (where his mother worked) while debit card records showed that Molina had made a purchase at a Walmart across town at the exact same time.
Molina’s attorneys argue that this and other instances like it should have made it clear to Avondale police that Google’s account-location data is not always reliable in determining the actual location of a person.
“About” searches might be rare, but that doesn’t make them a good idea. We have knowingly and willingly built the architecture of a police state, just so companies can show us ads. (And it is increasingly apparent that the advertising-supported Internet is heading for a crash.)
Before being taken down, the 25 apps were collectively downloaded more than 2.34 million times.
The malicious apps were developed by the same threat group and despite offering different features, under the hood, all the apps worked the same.
According to a report from French cyber-security firm Evina shared with ZDNet today, the apps posed as step counters, image editors, video editors, wallpaper apps, flashlight applications, file managers, and mobile games.
The apps offered a legitimate functionality, but they also contained malicious code. Evina researchers say the apps contained code that detected what app a user recently opened and had in the phone’s foreground.
Interesting story of malware hidden in Google Apps. This particular campaign is tied to the government of Vietnam.
At a remote virtual version of its annual Security Analyst Summit, researchers from the Russian security firm Kaspersky today plan to present research about a hacking campaign they call PhantomLance, in which spies hid malware in the Play Store to target users in Vietnam, Bangladesh, Indonesia, and India. Unlike most of the shady apps found in Play Store malware, Kaspersky’s researchers say, PhantomLance’s hackers apparently smuggled in data-stealing apps with the aim of infecting only some hundreds of users; the spy campaign likely sent links to the malicious apps to those targets via phishing emails. “In this case, the attackers used Google Play as a trusted source,” says Kaspersky researcher Alexey Firsh. “You can deliver a link to this app, and the victim will trust it because it’s Google Play.”
The first hints of PhantomLance’s campaign focusing on Google Play came to light in July of last year. That’s when Russian security firm Dr. Web found a sample of spyware in Google’s app store that impersonated a downloader of graphic design software but in fact had the capability to steal contacts, call logs, and text messages from Android phones. Kaspersky’s researchers found a similar spyware app, impersonating a browser cache-cleaning tool called Browser Turbo, still active in Google Play in November of that year. (Google removed both malicious apps from Google Play after they were reported.) While the espionage capabilities of those apps was fairly basic, Firsh says that they both could have expanded. “What’s important is the ability to download new malicious payloads,” he says. “It could extend its features significantly.”
Kaspersky went on to find tens of other, similar spyware apps dating back to 2015 that Google had already removed from its Play Store, but which were still visible in archived mirrors of the app repository. Those apps appeared to have a Vietnamese focus, offering tools for finding nearby churches in Vietnam and Vietnamese-language news. In every case, Firsh says, the hackers had created a new account and even Github repositories for spoofed developers to make the apps appear legitimate and hide their tracks.
Google and Apple have announced a joint project to create a privacy-preserving COVID-19 contact tracing app. (Details, such as we have them, are here.) It’s similar to the app being developed at MIT, and similar to others being described and developed elsewhere. It’s nice seeing the privacy protections; they’re well thought out.
I was going to write a long essay about the security and privacy concerns, but Ross Anderson beat me to it. (Note that some of his comments are UK-specific.)
First, it isn’t anonymous. Covid-19 is a notifiable disease so a doctor who diagnoses you must inform the public health authorities, and if they have the bandwidth they call you and ask who you’ve been in contact with. They then call your contacts in turn. It’s not about consent or anonymity, so much as being persuasive and having a good bedside manner.
I’m relaxed about doing all this under emergency public-health powers, since this will make it harder for intrusive systems to persist after the pandemic than if they have some privacy theater that can be used to argue that the whizzy new medi-panopticon is legal enough to be kept running.
Second, contact tracers have access to all sorts of other data such as public transport ticketing and credit-card records. This is how a contact tracer in Singapore is able to phone you and tell you that the taxi driver who took you yesterday from Orchard Road to Raffles has reported sick, so please put on a mask right now and go straight home. This must be controlled; Taiwan lets public-health staff access such material in emergencies only.
Third, you can’t wait for diagnoses. In the UK, you only get a test if you’re a VIP or if you get admitted to hospital. Even so the results take 1-3 days to come back. While the VIPs share their status on twitter or facebook, the other diagnosed patients are often too sick to operate their phones.
Fourth, the public health authorities need geographical data for purposes other than contact tracing – such as to tell the army where to build more field hospitals, and to plan shipments of scarce personal protective equipment. There are already apps that do symptom tracking but more would be better. So the UK app will ask for the first three characters of your postcode, which is about enough to locate which hospital you’d end up in.
Fifth, although the cryptographers – and now Google and Apple – are discussing more anonymous variants of the Singapore app, that’s not the problem. Anyone who’s worked on abuse will instantly realise that a voluntary app operated by anonymous actors is wide open to trolling. The performance art people will tie a phone to a dog and let it run around the park; the Russians will use the app to run service-denial attacks and spread panic; and little Johnny will self-report symptoms to get the whole school sent home.
To me, the real problems aren’t around privacy and security. The efficacy of any app-based contact tracing is still unproven. A “contact” from the point of view of an app isn’t the same as an epidemiological contact. And the ratio of infections to contacts is high. We would have to deal with the false positives (being close to someone else, but separated by a partition or other barrier) and the false negatives (not being close to someone else, but contracting the disease through a mutually touched object). And without cheap, fast, and accurate testing, the information from any of these apps isn’t very useful. So I agree with Ross that this is primarily an exercise in that false syllogism: Something must be done. This is something. Therefore, we must do it. It’s techies proposing tech solutions to what is primarily a social problem.
EDITED TO ADD: Susan Landau on contact tracing apps and how they’re being oversold. And Farzad Mostashari, former coordinator for health IT at the Department of Health and Human Services, on contact tracing apps.
As long as 1) every contact does not result in an infection, and 2) a large percentage of people with the disease are asymptomatic and don’t realize they have it, I can’t see how this sort of app is valuable. If we had cheap, fast, and accurate testing for everyone on demand…maybe. But I still don’t think so.
EDITED TO ADD (4/15): More details from Apple and Google.
Насред тежките ограничения заради пандемията от COVID-19, мобилността на българските граждани е намаляла най-малко в сравнение със съседните страни, показват данни разпространени от Google.
Данните са от геолокализацията на мобилни устройства и са анонимизирани. Те обхващат периода от 16 февруари до 29 март и са предоставени публично, за да могат правителствата да се информират за реалното положение със спазването на карантинните мерки – твърдят от световния интернет гигант.
Мобилността в България според данните на Google към 29 март.
Мобилността е разделена на три категории – Шопинг и развлечения (Retail & recreation) или посещения в търговски центрове, кафенета, ресторанти, музеи, кина и атракциони; Хранителни стоки и аптеки (Grocery & pharmacy) или посещения в магазини за хранителни стоки, пазари и аптеки; Паркове (Parks) или посещения на паркове, градини и плажове. Данните са обобщени като разлика в проценти на посещаемост спрямо периода преди ограничителните мерки.
Дисциплината на българите в категориите “Развлечения” и “Пазаруване” е най-зле на Балканите, а в категорията “Паркове” е по-добре единствено от Босна и Херцеговина, показва сравнението на данните за различни страни, направено от Биволъ. Това заключение е условно, тъй като за Албания и Сърбия не са налични данни към този момент.
Шопинг и развлечения
Пазаруване и аптеки
Всъщност България стои много по-близо до Нидерландия, където режимът на ограниченията е по-либерален. На Балканите шампион и в трите категории е Румъния. Без изненади, в Европа класацията по намалена мобилност се оглавява от най-засегнатите Италия и Испания.
Една от интерпретациите на тези данни е, че строгите мерки за ограничаване на социалната и физичска отдалеченост в България не се спазват. Ниска дисциплина в това отношение демонстрираха и българските народни представители, които преди два дни се наредиха на опашка за тестване от COVID-19 в две столични болници. На снимките, разпространени в медиите се вижда, че те не съблюдават регламентираната дистанция от метър и половина.
Voice assistants — the demo targeted Siri, Google Assistant, and Bixby — are designed to respond when they detect the owner’s voice after noticing a trigger phrase such as ‘Ok, Google’.
Ultimately, commands are just sound waves, which other researchers have already shown can be emulated using ultrasonic waves which humans can’t hear, providing an attacker has a line of sight on the device and the distance is short.
What SurfingAttack adds to this is the ability to send the ultrasonic commands through a solid glass or wood table on which the smartphone was sitting using a circular piezoelectric disc connected to its underside.
Although the distance was only 43cm (17 inches), hiding the disc under a surface represents a more plausible, easier-to-conceal attack method than previous techniques.
Google presented its system of using deep-learning techniques to identify malicious email attachments:
At the RSA security conference in San Francisco on Tuesday, Google’s security and anti-abuse research lead Elie Bursztein will present findings on how the new deep-learning scanner for documents is faring against the 300 billion attachments it has to process each week. It’s challenging to tell the difference between legitimate documents in all their infinite variations and those that have specifically been manipulated to conceal something dangerous. Google says that 63 percent of the malicious documents it blocks each day are different than the ones its systems flagged the day before. But this is exactly the type of pattern-recognition problem where deep learning can be helpful.
The document analyzer looks for common red flags, probes files if they have components that may have been purposefully obfuscated, and does other checks like examining macros — the tool in Microsoft Word documents that chains commands together in a series and is often used in attacks. The volume of malicious documents that attackers send out varies widely day to day. Bursztein says that since its deployment, the document scanner has been particularly good at flagging suspicious documents sent in bursts by malicious botnets or through other mass distribution methods. He was also surprised to discover how effective the scanner is at analyzing Microsoft Excel documents, a complicated file format that can be difficult to assess.
This is the sort of thing that’s pretty well optimized for machine-learning techniques.
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.
The smartphone messaging app ToTok is actually an Emirati spying tool:
But the service, ToTok, is actually a spying tool, according to American officials familiar with a classified intelligence assessment and a New York Times investigation into the app and its developers. It is used by the government of the United Arab Emirates to try to track every conversation, movement, relationship, appointment, sound and image of those who install it on their phones.
ToTok, introduced only months ago, was downloaded millions of times from the Apple and Google app stores by users throughout the Middle East, Europe, Asia, Africa and North America. While the majority of its users are in the Emirates, ToTok surged to become one of the most downloaded social apps in the United States last week, according to app rankings and App Annie, a research firm.
Apple and Google have removed it from their app stores. If you have it on your phone, delete it now.
Siri, Alexa, and Google Assistant are vulnerable to attacks that use lasers to inject inaudible — and sometimes invisible — commands into the devices and surreptitiously cause them to unlock doors, visit websites, and locate, unlock, and start vehicles, researchers report in a research paper published on Monday. Dubbed Light Commands, the attack works against Facebook Portal and a variety of phones.
Shining a low-powered laser into these voice-activated systems allows attackers to inject commands of their choice from as far away as 360 feet (110m). Because voice-controlled systems often don’t require users to authenticate themselves, the attack can frequently be carried out without the need of a password or PIN. Even when the systems require authentication for certain actions, it may be feasible to brute force the PIN, since many devices don’t limit the number of guesses a user can make. Among other things, light-based commands can be sent from one building to another and penetrate glass when a vulnerable device is kept near a closed window.
Interesting article on people using banks of smartphones to commit ad fraud for profit.
No one knows how prevalent ad fraud is on the Internet. I believe it is surprisingly high — here’s an article that places losses between $6.5 and $19 billion annually — and something companies like Google and Facebook would prefer remain unresearched.
Private Join and Compute uses a 1970s methodology known as “commutative encryption” to allow data in the data sets to be encrypted with multiple keys, without it mattering which order the keys are used in. This is helpful for multiparty computation, where you need to apply and later peel away multiple layers of encryption without affecting the computations performed on the encrypted data. Crucially, Private Join and Compute also uses methods first developed in the ’90s that enable a system to combine two encrypted data sets, determine what they have in common, and then perform mathematical computations directly on this encrypted, unreadable data through a technique called homomorphic encryption.
True homomorphic encryption isn’t possible, and my guess is that it will never be feasible for most applications. But limited application tricks like this have been around for decades, and sometimes they’re useful.
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