And of course I referenced VeriDas in my February 7 post when it defined the difference between presentation attack detection and injection attack detection.
Biometric Update played up this difference:
To stay ahead of the curve, Spanish biometrics company Veridas has introduced an advanced injection attack detection capability into its system, to combat the growing threat of synthetic identities and deepfakes….
Veridas says that standard fraud detection only focuses on what it sees or hears – for example, face or voice biometrics. So-called Presentation Attack Detection (PAD) looks for fake images, videos and voices. Deepfake detection searches for the telltale artifacts that give away the work of generative AI.
Neither are monitoring where the feed comes from or whether the device is compromised.
I can revisit the arguments about whether you should get PAD and…IAD?…from the same vendor, or whether you should get best in-class solutions to address each issue separately.
Checking the purported identity against private databases, such as credit records.
Checking the person’s driver’s license or other government document to ensure it’s real and not a fake.
Checking the purported identity against government databases, such as driver’s license databases. (What if the person presents a real driver’s license, but that license was subsequently revoked?)
Perform a “who you are” biometric test against the purported identity.
If you conduct all four tests, then you have used multiple factors of authentication to confirm that the person is who they say they are. If the identity is synthetic, chances are the purported person will fail at least one of these tests.
Do you fight synthetic identity fraud?
If you fight synthetic identity fraud, you should let people know about your solution.
Let’s say that your identity/biometric firm has decided that silence ISN’T golden, and that perhaps your firm needs to talk about its products and services.
So you turn to your favorite generative AI tool to write something that will represent your company in front of everyone. What could go wrong?
Battling synthetic identities requires a multi-pronged approach. Layering advanced technology is key: robust identity verification using government-issued IDs and biometrics to confirm a person’s existence, data enrichment and validation from diverse sources to check for inconsistencies, and machine learning algorithms to identify suspicious patterns and red flags. Collaboration is crucial too, from financial institutions sharing watchlists to governments strengthening regulations and consumers practicing good cyber hygiene. Ultimately, vigilance and a layered defense are the best weapons against these ever-evolving digital phantoms.
From Google Bard.
Great. You’re done, and you saved a lot of money by NOT hiring an identity blog writing expert. The text makes a lot of important points, so I’m sure that your prospects will be inspired by it.
Bot-speak is not an optimal communication strategy either. Generated at craiyon.com.
Well…
…until your prospects ask what YOU do and how you are better than every other identity firm out there. If you’re the same as all the other “me too” solutions, then your prospects will just go with the lowest price provider.
So how do you go about intelligently writing about biometrics?
Intelligently writing about biometrics doesn’t only require some critical words such as “validation.”
Intelligently writing about biometrics doesn’t only require that you KNOW what those words mean, and that you’re conversant in basic biometric topics. (If you want to know five topics a biometric content marketing expert needs to understand, read my post on that subject.)
Intelligently writing about biometrics requires that you put all of this information together AND effectively communicate your message…
…including why your identity/biometrics firm is great and why all the other identity/biometric firms are NOT great.
If you’re doing this on your own, be sure to ask yourself a lot of questions so that you get started on the right track.
If you’re asking Bredemarket to help you create your identity/biometric content by intelligently writing about biometrics, I’ll take care of the questions.
Oh, and one more thing: if you noted my use of the word “no siree” earlier in this post, it was taken from the Talking Heads song “The Big Country.” Here’s an independent video of that song, especially recommended for people outside of North America who may not realize that the United States and Canada are…well, big countries.
My belief that everything on the Internet is true has been irrevocably shattered, all because of what an entertainment executive ordered in his spare time. But the Casey Bloys / “Kelly Shepherd” story is just a tiny bit of what is going on with synthetic identities. And X isn’t the only platform plagued by them, as my LinkedIn experience attests.
By the way, this blog post contains pictures of a lot of people. Casey Bloys is real. Some of the others, not so much.
Casey Bloys is the Chairman and CEO of HBO and Max Content. Bloys had to start a recent 2024 schedule presentation with an apology, according to Variety. After explaining how passionate he is about his programming, he went back in time a couple of years to a period that we all remember.
So when you think of that mindset, and then think of 2020 and 2021, I’m home, working from home and spending an unhealthy amount of scrolling through Twitter. And I come up with a very, very dumb idea to vent my frustration.
So why did Bloys have to apologize on Thursday? Because of an article that Rolling Stone published on Wednesday. The article led off with this juicy showbiz tidbit about Bloys’ idea for responding to a critic.
“Maybe a Twitter user should tweet that that’s a pretty blithe response to what soldiers legitimately go through on [the] battlefield,” he texted. “Do you have a secret handle? Couldn’t we say especially given that it’s D-Day to dismiss a soldier’s experience like that seems pretty disrespectful … this must be answered!”
(A note to my younger readers: Twitter used to be a popular social media service that no longer exists. It was replaced by X.)
Eventually Bloys found someone to create the “secret handle.” Sully Temori is now alleging wrongful termination by HBO (which is why we’re learning about these juicy tidbits, via court filings). But in 2021 he was an executive assistant who wanted to get ahead by pleasing his bosses.
Ms. Shepherd seems like a nice woman. A mom, a Texan, a herbalist and aromatherapist, and a vegan. (The cows love that last part.)
Most critically, Shepherd is a normal person, not one of those Hollywood showbiz folks. Although Shepherd, who never posted anything on her own, seems to have a distinct motivation to respond to critics of HBO shows. Take her first reply to a critic from (checks notes) Rolling Stone. (Two years later, Rolling Stone would gleefully report on this story. Watch out who you anger.)
Kelly’s other three replies were along the same lines.
All were short one-sentence blurbs.
Most were completely in lower case, because that’s how regular non-Hollywood folk tweet.
All were critical of those who were critical of HBO, accusing them of “shitting on a show about women,” getting their “panties in a bunch,” and being “busy virtue signaling.”
Hey, if I couldn’t eat hamburgers and my home was filled with weird herbs and aromas, I’d be a little mad too.
And then, a little over a week later, it was over, and Kelly Shepherd never tweeted again. Although Temori apparently performed other activities against HBO critics via other methods. Well, until he was terminated.
Did Kelly Shepherd open a LinkedIn account?
But as part of the plan to satisfy Casey Bloys’ angry whims, Kelly Shepherd acquired a social media account, which she could use as a possible proof of identity.
Even though we now know she doesn’t exist.
But X isn’t the only platform plagued with synthetic identities, and some synthetic identities can do much more than anger an entertainment reviewer.
Many of us on LinkedIn are regularly receiving InMails and connection requests (in my case, from profiles with pictures of beautiful women) who say that we are constantly recommended by LinkedIn, who tell us how impressive our profiles are, and who want to contact us outside of the LinkedIn platform via text message or WhatsApp.
Now perhaps some of these messages are from real people, but I seriously doubt that so many of the employees at John Q Wine & Liquor Winery in New York happen to have the last name “Walter.” And the exact same job title.
Ms. Walter is a pretty busy freelance general manager / director / content partnerships manager.
As for her colleague Ms. Alice Walter, she has more experience (having started in 2018) but also has an extensive biography that begins:
The United States is a country with innovative challenges, and there is more room for development in the wine industry at John Q Wine & Liquor Winery. I am motivated and love to learn, and like to be exposed to more different cultures, and hope to develop more careers in my future life.
And you can check out Maria Walter’s profile if you’re so inclined. Or at least check out “her” picture.
Now none of the Walters women tried to contact me, but another “employee” (or maybe it was a “freelancer,” I forget) of this company tried to do so, which led my curious nature to discover yet another hive of fake LinkedIn profiles.
Sadly, one person from this company is a second-degree connection, which means that one of my connections accepted “her” connection request.
Synthetic identities are harmless…right?
Who knows what Karina, Alice, and Maria will do with their LinkedIn profiles?
Will they connect with other professionals?
Will they ask said professionals to move the conversation to SMS or WhatsApp, for whatever reason?
Will they apply for new jobs, using their impressive work history? A 98.8% customer satisfaction rate while managing 1,800 sub-partnerships is remarkable.
Will they apply for bank accounts…or loans?
The fraud possibilities from fake LinkedIn accounts are endless, and could be very costly for any company who falls for a fake synthetic identity. In fact, FiVerity reports that “in 2020, an estimated $20 billion was lost to SIF” (synthetic identity fraud). Which means that LinkedIn account holders and Partnerships Managers Karina, Alice, and Maria Walter could make a LOT of money.
Now banks and other financial institutions have safeguards to verify financial identities of people who open accounts and apply for loans, because fraud reduction is critically important to financial institutions.
Social media companies? Identity is only “important” to them.
They don’t even care about uniqueness (as Worldcoin does), evidenced by the fact that I have more than two X accounts (but none in which I portray a female Texas mom and vegan).
So if someone comes up to you on X or LinkedIn, remember that all may not be as it seems.
But are computerized systems any better, and can they detect spoofed voices?
Well, in the same way that fingerprint readers worked to overcome gummy bears, voice readers are working to overcome deepfake voices.
This is only the beginning of the war against voice spoofing. Other companies will pioneer new advances that will tell the real voices from the fake ones.
As for independent testing:
ID R&D has participated in multiple ASVspoof tests, and performed well in them.
Ignoring your prospects is NOT a winning business strategy. But a lot of companies do it anyway by not communicating regularly with their prospects.
If you ignore your prospects, your prospects will ignore you.
Meetings and money, via a third party
Of my three Bredemarket meetings (so far) today, the second was the most promising.
A person at a large company needs consulting services from me. All we need to do is work out the mechanics. The large company relies on a third party to manage its indpendent contractor relationships, including onboarding, time cards, and payments for hourly work. I wanted to learn about the third party, but I ran into walls when seeking current information about the firm.
The third party’s website is static
The third party’s website talks about its services, some unique aspects about the business, the story of its founder (a fascinating story), its technology partners, and its call to action. It provides ALMOST everything…with the exception of CURRENT information.
Luckily for me, I knew where to find current information on the company. Since the company is a B2B provider, I assumed that the company has a LinkedIn page. And I was right. But…
The third party’s LinkedIn page is also static
As you probably know, company LinkedIn pages have several subpages. The “About” supage talks about the third party company’s services, and the “People” subpage links to the profiles of the company’s employees, including the founder. So I went to the “Posts” subpage for the third party…
Use other social media outlets: TikTok, X, YouTube, whatever.
Pay attention to your prospects by providing current content.
If you ignore your prospects, your prospects will ignore you.
Are you ready to stop ignoring your prospects?
If you need help creating content for your blog, your social media platforms, or your website, Bredemarket can help you regain credibility with your prospects and customers.
Authorize Bredemarket, Ontario California’s content marketing expert, to help your firm produce words that return results.
Does your firm fight crooks who try to fraudulently use synthetic identities? If so, how do you communicate your solution?
This post explains what synthetic identities are (with examples), tells four ways to detect synthetic identities, and closes by providing an answer to the communication question.
While this post is primarily intended for identity firms who can use Bredemarket’s marketing and writing services, anyone else who is interested in synthetic identities can read along.
What are synthetic identities?
To explain what synthetic identities are, let me start by telling you about Jason Brown.
Jason Brown wasn’t Jason Brown
You may not have heard of him unless you lived in Atlanta, Georgia in 2019 and lived near the apartment he rented.
Jason Brown’s renting of an apartment isn’t all that unusual.
If you were to visit Brown’s apartment in February 2019, you would find credit cards and financial information for Adam M. Lopez and Carlos Rivera.
Now that’s a little unusual, especially since Lopez and Rivera never existed.
For that matter, Jason Brown never existed either.
A Georgia man was sentenced Sept. 1 (2022) to more than seven years in federal prison for participating in a nationwide fraud ring that used stolen social security numbers, including those belonging to children, to create synthetic identities used to open lines of credit, create shell companies, and steal nearly $2 million from financial institutions….
Cato joined conspiracies to defraud banks and illegally possess credit cards. Cato and his co-conspirators created “synthetic identities” by combining false personal information such as fake names and dates of birth with the information of real people, such as their social security numbers. Cato and others then used the synthetic identities and fake ID documents to open bank and credit card accounts at financial institutions. Cato and his co-conspirators used the unlawfully obtained credit cards to fund their lifestyles.
Talking about synthetic identity at Victoria Gardens
Here’s a video that I created on Saturday that describes, at a very high level, how synthetic identities can be used fraudulently. People who live near Rancho Cucamonga, California will recognize the Victoria Gardens shopping center, proof that synthetic identity theft can occur far away from Georgia.
Note that synthetic identity theft different from stealing someone else’s existing identity. In this case, a new identity is created.
So how do you catch these fraudsters?
Catching the identity synthesizers
If you’re renting out an apartment, and Jason Brown shows you his driver’s license and provides his Social Security Number, how can you detect if Brown is a crook? There are four methods to verify that Jason Brown exists, and that he’s the person renting your apartment.
Method One: Private Databases
One way to check Jason Brown’s story is to perform credit checks and other data investigations using financial databases.
Did Jason Brown just spring into existence within the past year, with no earlier credit record? That seems suspicious.
Does Jason Brown’s credit record appear TOO clean? That seems suspicious.
Does Jason Brown share information such as a common social security number with other people? Are any of those other identities also fraudulent? That is DEFINITELY suspicious.
This is one way that many firms detect synthetic identities, and for some firms it is the ONLY way they detect synthetic identities. And these firms have to tell their story to their prospects.
If your firm offers a tool to verify identities via private databases, how do you let your prospects know the benefits of your tool, and why your solution is better than all other solutions?
Method Two: Check That Driver’s License (or other government document)
What about that driver’s license that Brown presented? There are a wide variety of software tools that can check the authenticity of driver’s licenses, passports, and other government-issued documents. Some of these tools existed back in 2019 when “Brown” was renting his apartment, and a number of them exist today.
Maybe your firm has created such a tool, or uses a tool from a third party.
If your firm offers this capability, how can your prospects learn about its benefits, and why your solution excels?
Method Three: Check Government Databases
Checking the authenticity of a government-issued document may not be enough, since the document itself may be legitimate, but the implied credentials may no longer be legitimate. For example, if my California driver’s license expires in 2025, but I move to Minnesota in 2023 and get a new license, my California driver’s license is no longer valid, even though I have it in my possession.
Why not check the database of the Department of Motor Vehicles (or the equivalent in your state) to see if there is still an active driver’s license for that person?
The American Association of Motor Vehicle Administrators (AAMVA) maintains a Driver’s License Data Verification (DLDV) Service in which participating jurisdictions allow other entities to verify the license data for individuals. Your firm may be able to access the DLDV data for selected jurisdictions, providing an extra identity verification tool.
If your firm offers this capability, how can your prospects learn where it is available, what its benefits are, and why it is an important part of your solution?
Method Four: Conduct the “Who You Are” Test
There is one more way to confirm that a person is real, and that is to check the person. Literally.
If someone on a smartphone or videoconference says that they are Jason Brown, how do you know that it’s the real Jason Brown and not Jim Smith, or a previous recording or simulation of Jason Brown?
This is where tools such as facial recognition and liveness detection come to play.
You can ensure that the live face matches any face on record.
You can also confirm that the face is truly a live face.
In addition to these two tests, you can compare the face against the face on the presented driver’s license or passport to offer additional confirmation of true identity.
Now some companies offer facial recognition, others offer liveness detection, others match the live face to a face on a government ID, and many companies offer two or three of these capabilities.
One more time: if your firm offers these capabilities—either your own or someone else’s—what are the benefits of your algorithms? (For example, are they more accurate than competing algorithms? And under what conditions?) And why is your solution better than the others?
This is for the firms who fight synthetic identities
While most of this post is of general interest to anyone dealing with synthetic identities, this part of this post is specifically addressed to identity and biometric firms who provide synthetic identity-fighting solutions.
When you communicate about your solutions, your communicator needs to have certain types of experience.
Industry experience. Perhaps you sell your identity solution to financial institutions, or educational institutions , or a host of other industries (gambling/gaming, healthcare, hospitality, retailers, or sport/concert venues, or others). You need someone with this industry experience.
Solution experience. Perhaps your communications require someone with 29 years of experience in identity, biometrics, and technology marketing, including experience with all five factors of authentication (and verification).
Communication experience. Perhaps you need to effectively communicate with your prospects in a customer focused, benefits-oriented way. (Content that is all about you and your features won’t win business.)
If you haven’t read a Bredemarket blog post before, or even if you have, you may not realize that this post is jam-packed with additional information well beyond the post itself. This post alone links to the following Bredemarket posts and other content. You may want to follow one or more of the 13 links below if you need additional information on a particular topic:
Here’s my latest brochure for the Bredemarket 400 Short Writing Service, my standard package to create your 400 to 600 word blog posts and LinkedIn articles. Be sure to check the Bredemarket 400 Short Writing Service page for updates.
When you have tens of thousands of people dying, then the only conscionable response is to ban automobiles altogether. Any other action or inaction is completely irresponsible.
After all, you can ask the experts who want us to ban biometrics because it can be spoofed and is racist, so therefore we shouldn’t use biometrics at all.
I disagree with the calls to ban biometrics, and I’ll go through three “biometrics are bad” examples and say why banning biometrics is NOT justified.
Even some identity professionals may not know about the old “gummy fingers” story from 20+ years ago.
And yes, I know that I’ve talked about Gender Shades ad nauseum, but it bears repeating again.
And voice deepfakes are always a good topic to discuss in our AI-obsessed world.
But the iris security was breached by a “dummy eye” just a month later, in the same way that gummy fingers and face masks have defeated other biometric technologies.
Back in 2002, this news WAS really “scary,” since it suggested that you could access a fingerprint reader-protected site with something that wasn’t a finger. Gelatin. A piece of metal. A photograph.
TECH5 participated in the 2023 LivDet Non-contact Fingerprint competition to evaluate its latest NN-based fingerprint liveness detection algorithm and has achieved first and second ranks in the “Systems” category for both single- and four-fingerprint liveness detection algorithms respectively. Both submissions achieved the lowest error rates on bonafide (live) fingerprints. TECH5 achieved 100% accuracy in detecting complex spoof types such as Ecoflex, Playdoh, wood glue, and latex with its groundbreaking Neural Network model that is only 1.5MB in size, setting a new industry benchmark for both accuracy and efficiency.
TECH5 excelled in detecting fake fingers for “non-contact” reading where the fingers don’t even touch a surface such as an optical surface. That’s appreciably harder than detecting fake fingers that touch contact devices.
I should note that LivDet is an independent assessment. As I’ve said before, independent technology assessments provide some guidance on the accuracy and performance of technologies.
So gummy fingers and future threats can be addressed as they arrive.
Let’s stop right there for a moment and address two items before we continue. Trust me; it’s important.
This study evaluated only three algorithms: one from IBM, one from Microsoft, and one from Face++. It did not evaluate the hundreds of other facial recognition algorithms that existed in 2018 when the study was released.
The study focused on gender classification and race classification. Back in those primitive innocent days of 2018, the world assumed that you could look at a person and tell whether the person was male or female, or tell the race of a person. (The phrase “self-identity” had not yet become popular, despite the Rachel Dolezal episode which happened before the Gender Shades study). Most importantly, the study did not address identification of individuals at all.
However, the findings did find something:
While the companies appear to have relatively high accuracy overall, there are notable differences in the error rates between different groups. Let’s explore.
All companies perform better on males than females with an 8.1% – 20.6% difference in error rates.
All companies perform better on lighter subjects as a whole than on darker subjects as a whole with an 11.8% – 19.2% difference in error rates.
When we analyze the results by intersectional subgroups – darker males, darker females, lighter males, lighter females – we see that all companies perform worst on darker females.
What does this mean? It means that if you are using one of these three algorithms solely for the purpose of determining a person’s gender and race, some results are more accurate than others.
And all the stories about people such as Robert Williams being wrongfully arrested based upon faulty facial recognition results have nothing to do with Gender Shades. I’ll address this briefly (for once):
In the United States, facial recognition identification results should only be used by the police as an investigative lead, and no one should be arrested solely on the basis of facial recognition. (The city of Detroit stated that Williams’ arrest resulted from “sloppy” detective work.)
If you are using facial recognition for criminal investigations, your people had better have forensic face training. (Then they would know, as Detroit investigators apparently didn’t know, that the quality of surveillance footage is important.)
If you’re going to ban computerized facial recognition (even when only used as an investigative lead, and even when only used by properly trained individuals), consider the alternative of human witness identification. Or witness misidentification. Roeling Adams, Reggie Cole, Jason Kindle, Adam Riojas, Timothy Atkins, Uriah Courtney, Jason Rivera, Vondell Lewis, Guy Miles, Luis Vargas, and Rafael Madrigal can tell you how inaccurate (and racist) human facial recognition can be. See my LinkedIn article “Don’t ban facial recognition.”
Obviously, facial recognition has been the subject of independent assessments, including continuous bias testing by the National Institute of Standards and Technology as part of its Face Recognition Vendor Test (FRVT), specifically within the 1:1 verification testing. And NIST has measured the identification bias of hundreds of algorithms, not just three.
Richard Nixon never spoke those words in public, although it’s possible that he may have rehearsed William Safire’s speech, composed in case Apollo 11 had not resulted in one giant leap for mankind. As noted in the video, Nixon’s voice and appearance were spoofed using artificial intelligence to create a “deepfake.”
In early 2020, a branch manager of a Japanese company in Hong Kong received a call from a man whose voice he recognized—the director of his parent business. The director had good news: the company was about to make an acquisition, so he needed to authorize some transfers to the tune of $35 million. A lawyer named Martin Zelner had been hired to coordinate the procedures and the branch manager could see in his inbox emails from the director and Zelner, confirming what money needed to move where. The manager, believing everything appeared legitimate, began making the transfers.
What he didn’t know was that he’d been duped as part of an elaborate swindle, one in which fraudsters had used “deep voice” technology to clone the director’s speech…
Now I’ll grant that this is an example of human voice verification, which can be as inaccurate as the previously referenced human witness misidentification. But are computerized systems any better, and can they detect spoofed voices?
IDVoice Verified combines ID R&D’s core voice verification biometric engine, IDVoice, with our passive voice liveness detection, IDLive Voice, to create a high-performance solution for strong authentication, fraud prevention, and anti-spoofing verification.
Anti-spoofing verification technology is a critical component in voice biometric authentication for fraud prevention services. Before determining a match, IDVoice Verified ensures that the voice presented is not a recording.
This is only the beginning of the war against voice spoofing. Other companies will pioneer new advances that will tell the real voices from the fake ones.
As for independent testing:
ID R&D has participated in multiple ASVspoof tests, and performed well in them.
I’ve previously contacted a journalist via Help a Reporter Out (HARO), and I occasionally pitch to journalists on the service. In fact, I submitted a new pitch earlier this month.
So I noted with interest this story of how fraudsters fool Help a Reporter Out pitch recipients with synthetic or otherwise fraudulent identities.
When a reporter is writing a story that requires a source that he or she does not have, that reporter will likely turn to HARO, a service that “connects journalists seeking expertise to include in their content with sources who have that expertise.”…
Now, shady SEOs hide behind fake photos and personalities. The latest black hat search-engine optimization trend is to respond to Help-a-Reporter-Out (HARO) inquiries pretending to be a person of whichever gender/ethnicity the journalist is seeking comment from.
As it turns out, I have never responded to a pitch that specifically requested comments from white males. (Probably because if a pitch DOESN’T request gender/ethnicity information, chances are that the respondent will be a white male.) But it’s clear how a HARO pitch scammer could create a synthesized identity of a biometric proposal writing expert.
So if you’re asking your source for a picture, John W. Defeo suggests that you ask for TWO pictures. I think that the technical term for this is MPA, or Multi Photo Authentication.
There’s one other suggestion.
Take those photographs and plug them into a reverse image lookup service like Tineye (or even Google Images). Have they appeared on the web before? Does the context make sense?
I often use the picture that is found on my jebredcal Twitter profile.
So I plugged that in to a Google reverse image search. As expected, it hit on Twitter, but also hit on some other social media platforms such as LinkedIn.
I hadn’t heard of TinEye before, so I figured I’d give it a shot. Here’s what TinEye found:
Very odd, since as I previously mentioned this particular image is available on Twitter, LinkedIn, and other sources. But it turns out that TinEye honors requests from social media services NOT to crawl their sites. (No comment.) And TinEye apparently hasn’t crawled the relevant page on bredemarket.com yet.
Which leads to the scary thought – what if someone searched TinEye for me, and didn’t bother to search anywhere else after getting 0 results? Would the searcher conclude that I was a synthetically-generated biobot?
Bredemarket 