Check how we use some skin properties combined with cutting-edge technologies to enhance the way Svort recognizes users.

While attackers invent new ways to trick defense systems, on the other side we roll with their punches. There are many kinds of spoofing attacks but have you ever heard that your skin can reduce the probability of a successful attack to zero? This article explains how and why the skin can act as the liveness marker.

What is pulsation in terms of biometrics?

First of all, let’s define the term “pulsation”. By using this word we do not refer to heart rate and ways to track it. This authentication method would not withstand the slightest criticism.

The term “pulsation” designates the human skin’s ability to reflect light. When there is a constant source of light, the skin reflects it evenly. But if the light flashes and goes out then, this spark is reflected by the skin also as a flash.

Repulses obtained differ depending on the skin's individual features and the flash color. This is because the skin is penetrated by the thinnest vessels filled with blood. The blood of a living person pulsates due to a heartbeat. It is this pulsation of blood that allows the reflection of even slightest changes in skin color highlighted by a flash. Humans can’t see these changes, but a camera will pick it up.

Here is how it works:

• Svort analyzes some face parameters and then highlights an object on a user’s face. Any part of the face (the nose, eyebrows, eye, cheeks, etc.) can act as an object.
• The parameters obtained during the flash outbreak are compared with the initial parameters obtained before the flash.
• At the same time camera detects whether the image is three-dimensional.

Three-dimensional volume and relevant pulsation parameters indicate that the person in front of the camera is alive. That is how Svort performs liveness detection through pulsation.

Why is it safe?

The method is combined and consists of 2 parts: obtaining and comparing parameters before and during a flash and detection of three-dimensional volume. But there are also trained neural networks that enhance security.

For granting access, it is not enough just to obtain and compare face parameters. It is also important to reflect the individual characteristics of every user’s skin, its texture, and reactions to flashing light. This is possible due to neural networks trained to catch patterns of how users’ skin reacts on pulsation.

Altogether these components allow Svort to accurately detect liveliness. It sounds simple but actually we’ve done a tremendous amount of work to make the process of liveness detection through pulsation precise and smooth. The matter at hand is the synthesizing and collecting the huge dataset needed for neural networks deep learning. But for enthusiasts like us, nothing is impossible so we coped, and now everything works as it was expected to work.

If it looks like what you’ve been looking for, drop us a line on founders@svort.io, and let’s stay in touch: LinkedIn, Facebook, Twitter, Website. We are ready to discuss the technology and answer the questions.

Pulsation for liveness detection was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Before the pandemic destroyed our way of life, global passenger traffic used to rise and force air transport hubs to invent new methods aimed to increase airport capacity. One of such methods is to replace passport and boarding pass by biometrics at all the journey stages from check-in to boarding. This article covers using biometrics for passenger verification & identification within transport hubs and explains its benefits.

How do biometrics identification & verification work?

Biometrics identification is the process of recognizing a person through the facial image. It is advantageous to both users and businesses as using biometrics cuts hardware expenses, reduces the time of customer service, prevents fraud, automates business processes and increases profit.

The main purpose of biometrics verification is to make sure that the human in front of a camera is the very that person he pretends to be. So the first step of this process is to compare a passengers’ passport with his image which can be done at the reception during self-check-in. Meanwhile, Svort neural network learns to recognize this particular passenger and transfers his biometrics data to all other touchpoints. Since this moment all the passenger needs for passing the journey steps is his face.

It is possible due to a particular neural network algorithm combined with infallible liveness detection that determines whether it interacts with a human being and prevents spoofing attacks employing photo, video, or mask. Although our liveness detection tests excellent we reiterate that its efficiency also depends on hardware characteristics like computer or webcam specifics, depth sensors in the camera, etc.

What are the benefits of Svort biometrics and what tasks does it resolve?

Unlike existing systems with one or several standards, Svort basically has no standards/references (photos or other human-interpretable data on face parameters). Svort is the 3D reconstruction of the user’s face, which is irreversible, non-human interpretable, and anonymous. It also recognizes passengers in the most precise manner even from those angles where current systems are experiencing difficulties.

No sensitive data like facial images are stored or transferred. Svort stores and transfers only neural networks that are trained to recognize passengers. These networks are depersonalized and anonymous as they do not contain any data on passengers and it is impossible to clarify some person’s face features (like eyes color, face geometry, etc.) using it. Such data can be transferred to any transport hub as it does not contradict GDPR.

Svort is not just a biometric identification system, but also the liveness detection that mitigates face-spoofing and is able to take advantage of cameras capable of constructing depth maps. Yet, Svort can with the same effect perform all its functions using GB/smartphone/notebook/etc. cameras. Svort does not have strong requirements for hardware and can be scaled horizontally if necessary to increase productivity. It is backward compatible with installed systems of both video surveillance and access control.

Svort is faster, more reliable, and safer than other biometrics solutions with facial recognition. Neither sunglasses, beards, and makeup nor face masks would not significantly impede its functions.

How Svort neural-biometric verification and identification work

Biometrics verification can be integrated at all steps where using a passport or boarding pass is supposed: check-in desks, bag drop units, gates, boarding, etc. The main idea is to replace documents with passenger’s face once his identity was verified. Facial biometrics can also enable airports to create lists of suspicious people or criminals and swap these lists to all transport hubs. Let’s clarify in detail how exactly neural-biometrics identification occurs.

Online neural-biometric registration for a flight

Actually, such registration can be used for everything that implies buying and checking tickets. After completing registration (on the website or in the application) a client is offered to pass neural-biometrics registration.

• A user needs to provide his ID and complete the registration process on his smartphone. For this purpose, he will be offered to pass a rotational challenge. He will also have to escape a virtual maze to confirm liveness.
• During the rotational challenge, the camera scans the passenger’s face comparing the image with the photo in ID, building its 3D face model, and training neural networks to recognize this passenger.

This action can be performed as a one-time registration or issuing a kind of biometrics ID. During these processes, Svort extracts some non-human interpretable vectors. Using a neural network, Svort converts these vectors into a biometric key realizing the concept “You Are The Key”.

Actually the key is a neural network that is trained to recognize a particular user. It is irreversible that makes it similar to password hashes. This allows to store and transfer it according to the same requirements as exist for hashes. Note that the neural network is neither a reference image nor other data that would provide specific characteristics of a registered user’s face.

After the neural network is saved in storage, it can be used for subsequent identification, authentication, and verification of a previously registered user.

Offline neural-biometric registration for a flight

For offline registration, a passenger uses a terminal or camera at registration desks in the airport instead of their own device. There are two ways of biometrics registration at the airport.

1. The video stream is continuously transmitted to a data center where it is processed. It creates a significant load on the network.
2. In the case of local processing, already trained neural networks or biometric vectors are transferred from the terminal or the camera at the registration desk to the data center. It significantly (up to 99%) reduces traffic and load on the network.

One more peculiarity of offline registration is that using public terminals instead of personal devices leads to either queues or low quality of biometrics registration. The way out is the dynamic registration, that completes neural network training. Dynamic registration collects missed biometrics data while a passenger moves through the airport until the neural network won’t be trained to recognize this passenger (or until another trigger emerges).

In summary, Svort biometric solution can:

• improve analytics of passenger traffic and customer service;
• help monitor overburdened areas within transport hub and reorganize its work;
• enable airports to make personalized offers to passengers in duty-free stores and service desks;
• increase the safety of air travel with the support of international crime control organizations (like INTERPOL, Europol, etc.) by comparing passengers with the databases of these organizations, identifying unwanted persons, and sending notifications to the staff.

Although air carriers are currently experiencing challenging times due to the pandemic, after everything is over and the borders open, airports will experience even greater load. That is, they will have to adapt, but increasing bandwidth will not be enough. The touch-free trend is gaining momentum and public places are already starting to implement the technology to protect people from diseases spreading through human-to-surface contacts. Here you can learn more about how Svort implements touch-free technology.

Svort is faster, more reliable, and safer than other biometrics solutions. We are open to discussion, collaboration, and new opportunities.

Let’s stay in touch: LinkedIn, Facebook, Twitter, Website.

Smart and secure travel: how and why apply facial biometrics in airports was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Epidemics trigger the world’s response no less than wars impacting and changing people’s ways of life. It was outbreaks of different diseases that taught humanity to wash hands, clean foods thoroughly, and deal with pests in the yards. Now it is time to get used to cover our mouths when sneezing or coughing, stop touching faces and implement touch-free technologies wherever it is possible to protect people from touching dirty surfaces.

CDC recommends us to stay at home, wash our hands, and disinfect surfaces thoroughly. Pandemic will stop sooner or later but humanity will never be the same again. The new habits like sanitizing hands and avoiding touching surfaces in public places will remain with us for the rest of our lives. That is why those who are able to provide their customers with touch-free experience will succeed. Implementation of contactless interactions and interfaces is a trend that gaining momentum right now, so enterprises will have to adapt or lose customers and reputation.

Where touch-free technology can be implemented?

It can be used literally in any process that implies the user’s authentication or identification. The idea is to replace traditional meanings of performing some actions to touch-free technology without touching surfaces. For example, open doors, check out at the counter, confirm the identity, etc.

Why humanity will apply touch-free technologies widely? Actually, there are just 2 reasons: it is convenient and it is safe. Pandemic has exposed deficiencies of the existing tools. Imagine how many people have already touched a fingerprint scanner by the moment you need to place your thumb on it? It has never been safe but in the circumstances of the global pandemic, it is even less safe than ever. Replacing outdated methods of getting access like traditional keys, cards, documents, and passes with users’ faces opens new vistas in terms of usability and user-friendliness.

How does Svort perform touch-free within access management?

Svort combines biometrics, neural network, and liveness detection to provide users with touch-free access to their offices, homes, premises, buildings, and workstations. It can be used for payment, identity confirmation, getting access, verification, registration, and whatever else. All necessary hardware is a system of video surveillance or even a single camera. Svort scans the user’s face then recognizes its biometric features and therefore performs the action needed.

Note that there are no special requirements for cameras so Svort can be integrated into any existing video security system. It is possible due to its flexibility and the certain algorithms of users’ recognition that identify people by some biometrics features of their faces and grants users access in less than a second.

• Imagine that you do not need to bring with you documents as your face is the only ID card you need.
• You also will not have to use card keys to get access to office as Svort integrated into the existing security system will recognize and grant you access even before you get your card key out of the bag.
• And you won’t even have to use Apple Pay or Samsung Pay to check out at the counter as your face can serve as a credit card.

There are many ways to implement Svort to provide your clients and employees with passwordless and touch-free access to whatever. If you want to know more check this article, it covers in detail how exactly Svort performs users’ recognition and why it is safe and fast. And this one demonstrates that Svort successfully recognizes even half-covered faces what is especially important now when we all have to protect ourselves with masks.

Now it is pretty clear that we’d better avoid touching surfaces in public places to prevent disease spreading through human-to-surface contacts. Facial recognition technology makes it possible, but how to implement it in places like airports that need to perform huge bandwidth? The trick is that a correctly selected tool will not only not slow down the established processes, but also accelerate them along with improving people’s safety. Stay in touch, we will soon tell you how to use Svort to identify and verify passengers at airports to improve services, optimize processes and increase aviation safety.

If you want to know more on how Svort can perform the touch-free trend within authentication and identification solutions, please drop us a line on founders@svort.io. Take care now and let’s stay in touch: LinkedIn, Facebook, Twitter, Website.

Touch-free: not a trend but market disruptor was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Learn how Svort Liveness Detection prevents identity farming

The environment is rapidly changing, and here at Svort, we’re making progress too. We continuously improve our technologies to meet the security requirements and offer our customers the most advanced solutions.

Infallible liveness detection is one of our core features that was created to provide users with the full anonymity, and user-friendly interface is our priority along with unprecedented safety. That is why we use virtual maze for liveness detection. This article explains how we perform this process and what makes it anonymous and accurate.

What is a virtual maze?

It is a kind of rotational challenge that allows Svort to recognize whether is it a live person in front of a camera. A user is supposed to turn his head in certain directions escaping the virtual maze. At the same time, Svort scans the user’s face and then grants or prohibits access according to the results. I.e. virtual maze is used to both authenticate the user and detect his liveness. It is convenient due to using a single action instead of separate steps for authentication and liveness detection.

How does it work?

During registration, a user has to turn his head in different directions. At this moment certain parameters of his face are scanned at different angles. Then our networks recreate a three-dimensional model of the face and learn to authenticate the user. And when the training is completed, the neural network is able to recognize whether it is a live person in front of the camera. I.e. after the registration and training the neural network detects liveness without the necessity to store sensitive users’ data.

Why is it secure?

We needed to make our liveness detection system secure and resistant to spoofing attacks. But we also did not want to overload it with some time-consuming details as passing the system was supposed to be simple or even enjoyable. That is how we decided to implement it in the form of a virtual maze. It is easy to use and hard to be evaded.

To complicate spoofing attacks, we make our maze unpredictable. I.e. a user never knows what action he is supposed to perform next time to escape it as the number of maze escape options reaches 127 132 672 867 200. Using face-tracking systems reduces the probability of successful photo or video spoofing attack almost to nothing as for hacking such a system in its most simple kind intruders have to possess billions of photos and videos of the user’s face taken in different conditions.

All of the above resulted in the convenient, precise and user-friendly liveness detection method. Yet we know that there are things to be improved so we are working hard to make the technology impeccable. If you want to know more about Svort Liveness Detection, please drop us a line on founders@svort.io. And let’s stay in touch: LinkedIn, Facebook, Twitter, Website.

Virtual maze for liveness detection was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Password replaced with face and using banking services without visiting the bank: how Svort takes our interactions with financial institutions to a new level.

Biometrics continues conquering the world helping businesses improve their services along with saving money. So it’s reasonable that financial institutions become to integrate the technology into their services. Read on to learn how users’ faces replace passwords and IDs, why it is good and how exactly biometrics will hold money in our accounts.

4 key benefits of using neural-biometrics

When it comes to using technology in the banking sector, it’s all about striking a balance between convenience and security. Facial biometrics is the precisely right solution to meet both requirements. It is convenient for banks and their customers for the following reasons:

• It is generally dependent on a single action of biometric scanning, rather than having to input a long and complex password (it really has to be long and complex to be safe).
• Forging biometric features is much harder and expensive than other fraud methods. By the way, forging someone’s face is not enough as hackers also have to override anti-spoofing systems that reduce the likelihood of success.
• Facial biometrics improves service and reduces the time spent on it. It also increases the accessibility of banking services by making all interactions remote.
• Integration facial biometrics does not imply extra spendings on hardware because usual cameras in branches can be used as well as clients’ smartphones.

Using facial biometrics in financial institutions is not only convenient but safe as well. Read on to learn, why the client’s face protects bank account better than the most complex password.

How facial biometrics combats fraud

The most important feature of using facial biometrics is increasing the security level. People lose billions of dollars because of stolen passwords and identity frauds. And here is when facial biometrics comes in.

• It replaces passwords with the user’s face making the loss impossible.
• It prevents identity fraud due to liveness detection.
• It also impedes the creation of fake accounts and drawing credit using someone else’s document.
• It protects banks from insider fraud by establishing secure employee authentication.

If you’d like to know more on neural-biometrics reliability check this article to clarify the core features of Svort and its principal advantages in comparison with other solutions.

4 ways to employ facial biometrics in the banking sector

There are many ways neural-biometrics can be used in banking opening new vistas for the industry, let’s address the principal ones.

Remote verification

Verification is the process of recognizing whether a person is really that one he/she pretends to be. It is essential for the banking sector due to being included in many processes:

• opening an account in a bank;
• drawing a credit;
• withdrawals;
• other financial activities; etc.

Until recently people have to be physically present in a bank branch and bring their passports or other documents to be verified. With the advent of facial biometrics, verification became more convenient and simple. Now to be verified a user just has to possess a smartphone with a camera. Here you can know more on how Svort remote verification works.

Employing remote verification comes in handy not only for routine operations but also reduces frauds of the bank’s manager and client collusion to draw credit using someone else’s document. The document’s owner is protected reliably as he is the only person who is able to pass verification to perform some action that implies confirming identity. It is possible due to the liveness detection system that prevents spoofing attacks employing photos, videos, and masks. Here you can learn in detail how liveness detection performs.

Passwordless access

Svort neural-biometrics provides both customers and employees with passwordless access to the bank’s application and internal services. Using a password is not secure enough as billions of them are already exposed online and leaks won’t stop. Replacing traditional authentication methods with passwordless access through biometrics significantly increases data security as forging an identity for passing Svort is highly unlikely. No stranger would get access to private data even if he possesses the password as he is also required to pass the liveness detection challenge along with using biometrics. Here it is a detailed explanation on how passwordless access within authentication works.

Multi-factor authentication

MFA has become routine in enterprises since the importance of cybersecurity architecture had been recognized. Now there are 2 ways to employ MFA: to use U2F tokens or one-time codes (OTPs). The first is inconvenient and the second is insecure, so there is the raising need in a multi-factor authentication method that is both convenient and reliable.

Using biometric authentication as the additional security factor essentially reduces the probability of successful hacking accounts due to the multi-layered protection. Firstly hackers have to compromise the password, then to obtain biometric data, and finally to pass authentication with this biometric data that is impossible due to the liveness detection system. This multi-layered structure is impenetrable and impassable for perpetrators.

Another feature of biometrics within MFA is the absence of a database that can be useful for hackers. No sensitive data like facial images are stored or transferred. Only neural networks trained to recognize users are stored and processed on the customer’s servers. These networks are depersonalized and anonymous as they do not contain any data on users. So even if a bank’s cybersecurity architecture is hacked such networks won’t come in handy for hackers as it is impossible to clarify some person’s face features (like eyes color, face geometry, etc.) using it.

You Are The Key, of a face instead of all other means of access

The integration of Svort neural-biometrics into existing security infrastructure means replacing keys, cards, and all other means of access by face. Employees can get safe access to their workspaces and internal services, and customers can be authenticated in the bank’s application, request for a loan and perform all types of operations remotely.

Even bankcards can be removed since the face is the only needed tool to get withdrawal in ATM or pay at counters. Another exciting thing on employing biometrics is that it does not require special hardware. Regular video surveillance systems can be used along with webcams on desktops or smartphones equipped with a camera.

Biometrics relieves the burden on bank branches, speeds up the time of customer service along with increasing their loyalty and cut expenses through optimization of internal business processes, let alone significantly increasing the security. Drop us a line to clarify what value Svort can place to your business.

Stay in touch with us: LinkedIn, Facebook, Twitter, Website

Facial Biometrics In The Banking Industry was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

There are currently 129,589 confirmed cases of the coronavirus as of March 12, 2020. For thousands of people, the epidemic means altering their behavior by wearing masks to protect themselves. Some of them complain, that their devices’ facial recognition doesn’t work properly because of the half-covered face. Others are dissatisfied with facial recognition software that is used at some train stations, airports, retail stores, and hotels that become annoying and inconvenient because of face-mask wearing.

Does it mean the universality of biometrics is in doubt? Actually, it just brings to light imperfections of the existing solutions. While other providers of biometric identification attempt to fix their software and increase its accuracy, SVORT is not much concerned as it recognizes users in masks exactly in the same way as without them. The details are covered below, but first, take a look at these pictures. Spoiler: neither hat nor mask impedes the accuracy of SVORT as it still recognizes the user.

To conduct neural-biometric matching we take two images. The first is a standard that is available from previous registration, ID, internal database, etc. The second image is taken in real-time when a user performs biometric identification and deleted immediately after extracting biometric vectors. SVORT compares biometric vectors from both images and indicates (the number in the middle) how similar are people on the left and right.

What makes SVORT non-sensitive to wearing face masks?

The core lies in the approach to recognition. SVORT does not rely on facial images but builds a 3D model and extracts biometric vectors that are responsible for recognition. That is how it goes:

• During the user’s registration, SVORT takes 40+ photos at certain angles.
• Biometrics vectors are extracted.
• Neural networks are trained to recognize the user.

By ‘biometrics vectors’ we mean a non-human interpretable identifier that has the biggest possible cosine similarity* for one person and the biggest inequality for different persons. And this poses SVORT’s unique ability to identify people wearing face masks.

*Cosine similarity is a measure of similarity between two non-zero vectors of an inner product space that measures the cosine of the angle between them (source: Wikipedia).

Do not be defensive about the pictures above, they were taken to demonstrate SVORT’s accuracy when user’s face is half-covered. Note that we do not take photos and there is no sensitive data like facial images stored or transferred. SVORT enables clients to store and transfer only neural networks that are trained to recognize users. These networks are depersonalized and anonymous as they do not contain any data on users and it is impossible to clarify some person’s face features (like eyes color, face geometry, etc.) using it.

Conclusion

Some argue that the coronavirus epidemic will lead to a massive technology rollback and will return humanity if not to the Stone Age then at least to the use of a fingerprint. Here in SVORT, we think that COVID-19 will open up new opportunities for truly working solutions and give a boost to new players in the biometrics market if old ones are failing. If you are interested in testing our neural-biometrics, leave your request here.

Stay in touch with us: LinkedIn, Facebook, Twitter, Website

SVORT vs. Coronavirus: can protection from COVID-19 impede neural-biometrics? was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

The power of data in the retail context cannot be overemphasized. Such information on customers like purchase history, behavioral patterns in stores, their preferences, and the ways they move through stores enables retailers to adopt balanced decisions that improve customer loyalty and increase revenue.

The use of biometrics is gaining popularity in retail. Businesses implement the technology to identify customers providing them with personal communication during shopping. There are plenty of ways to employ the technology of customer identification in the retail industry, but this text is dedicated to facial biometrics as it becomes the most demanded among retailers and convenient for consumers. Read on to learn why to employ biometrics in retail, how does it impact customer service, and what are its benefits for businesses.

How does facial biometrics recognition work and what benefits are there for retailers & consumers?

It is the method of identification of people through some special features of their faces features like textures and shapes. That is possible due to artificial intelligence and special neural network algorithms. The camera captures a customer’s image, compares it with the database, and then identifies him. All you need is cameras and integrated software solution yet there are some requirements on hardware features that depends on every particular case.

Biometrics in retail tackles the following challenges:

• customer identification;
• counting visitors traffic;
• tracking consumers’ behavior and the ways they move through stores;
• the shopping histories;
• loyalty cards replacement;
• improving customer service and increasing engagement by providing them with personalized offers and discounts based on their preferences;
• cutting costs and automation;
• data collection and analysis.

All the aforementioned solutions can be successfully resolved with a scope of separate tools. But the competition between retailers has reached an impressive scale so to win it they have to invent new approaches and modernize & automatize current business solutions. Biometrics has become a safe and proven tool providing retailers with an easy win across improving customer services. It enables business to:

• cut expenses on the scope of marketing tools by replacing them;
• increase consumers’ engagement making them return so it increases revenue;
• make ads targeting more precise and effective that also leads to cutting expenses and increasing revenue;
• improve shelf spaces and plan procurement thoroughly on the basis of consumers behavior and preferences;
• reduce losses caused by shoplifters and prevent employees theft;
• enable business owners to control employees eliminating time and attendance fraud and making workforce management processes transparent at all stages;
• access the quality of service provided by employees;
• protect storage facilities and staff entrances from outsiders;
• reduce operational cost as it replaces all kinds of traditional keys, loyalty cards and passwords.

Notable cases of biometric facial recognition

It is always hard and risky to be a pioneer in implementing new technology. Fortunately, we do not have to learn on our own mistakes as gigantic players have already tried the technology for us and demonstrated its efficiency clearly. Here is a list of the companies that had already implied biometrics and not going to stop:

• A chain of luxury department stores Saks Fifth Avenue has been using facial recognition since 2016 to identify VIPs and capture shoplifters.
• Mastercard introduced selfie pay that enables customers to verify online payments by looking at their smartphone cameras.
• KFC China uses biometrics facial recognition to identify customers and predict their orders. The predictions are based on a customer’s gender, age, and mood.

• South Korea uses AI and facial recognition to help enterprises interview and hire people.
• South Korea also identifies people in front of kiosks to provide them with personalized, interactive advertisements for restaurants and stores.
• American airports use biometrics to screen passengers on international flights.
• The US government is using facial recognition technology to surveil Americans (here is an interesting article that covers how widespread the use of facial recognition technology has become in the US).

Using biometrics in retail is gaining momentum and going to replace the whole pool of marketing and security tools. Though some consumers concern about digital privacy and security. They fear that facial recognition will undermine privacy so preference will be given to the solutions like SVORT that do not store any sensitive data. Meantime both businesses and customers are getting ready for the technological renaissance in retail as shopping services and experience need constant improvement to remain competitive.

How biometrics modifies retail and impacts customer service was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

The cybersecurity market will soar along with developing new data protection tools. We’ve conducted a kind of research and chosen 4 cybersecurity trends as we regard the most interesting to watch in 2020.

Mobile devices will become the principal target for phishing attacks

Desktop Internet use is declining steadily along with increasing usage of mobile devices. That is the reason fraudsters’ focus shifts to attacks on mobile.

But smartphone manufacturers improve protection constantly, making it difficult to hack a modern device. The weakest link is smartphone owners, and this fact has been used successfully for attacks, the number of which will only increase. Phishing attacks aimed at smartphones owners can lead to the following:

• employees identities theft, getting access to corporate resources, compromising the corporate network and sensitive (commercial/confidential) data theft;
• forcing to install a program for remote control, stealing money from a bank account;
• compromising user credentials for a bank mobile app and stealing money by OTP interception; etc.

This topic deserves separate research, but users must remember that their safety is up to them. Do not click links from strangers, protect your device by PIN code, do not open suspicious e-mails, and be attentive when downloading an application.

2FA becomes a thing of the past being replaces by MFA

2FA is not that safe as it is expected to be. It can be bypassed by phishing, third-party login, or a simple token theft. The new trend is multi-factor authentication (MFA), including biometrics. To prevent data breaches, enterprises increasingly take biometric authentication that improves security architecture.

It also positively affects the users’ experience. Here is an article on how biometrics will accustom people to use multi-factor authentication. In 2020, MFA is expected to become widely disseminated and implemented to protect both corporate and personal data.

Adoption of 5G and IoT devices will make us more vulnerable

With the 5G network implementation and development, the amount of attacked connected IoT devices will increase substantially. Some experts estimate 5G and IoT devices to be hackers’ paradise.

IoT devices and their connections are still a weak link in cybersecurity architecture. The volume of personal data is growing increasingly, along with the need for defending against breaches and theft.

But 5G networks are complicated and require a tremendous level of security that still can not be provided by the majority of cloud vendors. New vulnerabilities are yet to discover and protect, so blind spots will be used by hackers for attacks and data theft causing irreparable damage to enterprises.

So 2020 is going to become a year of rethinking approaches to IoT security and new tools to protect these growing networks across all industries.

Artificial intelligence (AI) will play a crucial role in both attack and defense

The number of cyberattacks is growing steadily, which means that the industry experts work harder but yet don’t cope with an increasing number of threats. But there is the artificial intelligence that reacts to a threat faster than the most experienced and skilled experts. AI is constantly being improved and trained. Using machine and deep learning AI can improve its algorithms to better recognize and prevent threats for cybersecurity.

But this process works both ways. Cybersecurity experts train AI to recognize and prevent threats while hackers train AI to bypass defense. Some industry experts compare this competition with arms race so perhaps in 2020 AI will play a crucial role in cybersecurity architectures.

4 cybersec trends to watch in 2020 was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Reading this article implies having Internet access that means your data is at risk if not protected properly.

We have developed a neural-biometrics access management system called SVORT and want to explain how it can protect your money and identity in digital space.

Those who take their digital security seriously can scroll down to “How does SVORT raise my security to another level?” section of the article.

All the others are welcomed to acquaint themselves with a bit of stats we’ve collected. We did not aim to cause you to panic. Our purpose is to enable users to assess the risks properly when they ignore data protection or treat it too carelessly.

A cyberattack occurs every 39 seconds on average as a Clark School study at the University of Maryland claimed. Cyber threats apply to anyone who somehow acts on the Internet. It is especially the cause of concern for those who keep and manage their money online.

• In 2018, frauds cost $1.7 billion to its victims.
• In May 2019, hackers withdrew $41 million from Binance that is one of the largest cryptocurrency exchanges in the world.

Whatever you are a bank’s customer, crypto or exchange trader, freelancer, poker player, remote worker or use online payments services or crypto wallet your digital money is at risk.

Read on to learn what steps you should take to strengthen your protection against fraudsters.

The main threats to online transactions are money and identity theft. Being stolen, your passwords, emails, and other data provide fraudsters with access to bank accounts, digital wallets, etc.

Money loss is not the only attack consequence that each of us can face as fraudsters can use our name and personal data for their malicious purposes damaging people close to us. Therefore protecting our digital environment can be considered not only as defending our interests but also as taking care of people we associate with.

Protective measures and its imperfections

Depending on the kind of activity you maintain on the Internet you might have been recommended for different data protective measures.

Using password managers, cryptographic keys, additional security factors as OTP and U2F, etc. people often get an illusion that their data is securely protected. Yet statistics indicates this illusion is not borne out by reality as frauds is increasing every year:

• In 2019, a collection of 2.7 billion identity records, consisting of 774 million unique email addresses and 21 million unique passwords, was exposed online (Wikipedia).
• Using OTPs as 2nd security factors in industries relating to blockchain or others can not stop cyber-thieves as it did not stop hackers from stealing $41 million from Binance wallets (Binance blog).
• OTP is an outdated method since perpetrators armed with special equipment intercepts OTPs and transfer money from the victims’ accounts to their own (The Economic Times).
• U2F implies users’ data safety depends on devices. Once it is stolen or lost, their data is threatened. U2F is also vulnerable to phishing (PYMNTS.com).

Whatever protective measure you use with high probability it can be bypassed. The only question is how difficult it is to override this or that security system. We have created a software solution called SVORT that is really hard to bypass. It can be used as an additional security factor within MFA and implies using something that can be neither stolen nor forged instead of using a password, token or device. By something we mean your face or more specifically its biometric data.

How does SVORT raise my security to another level?

SVORT is a neural-biometrics access management system based on liveness detection.

The great combo of a particular neural network algorithm, biometrics, and infallible liveness detection enabled a perfect authenticator that is entirely invulnerable to spoofing attacks. SVORT operates as follows:

• The particular neural network algorithm learns to detect the user by his face.
• A camera scan the user’s appearance at different angles.
• Then the system transforms the user’s face into code which itself is the private and depersonalized key.

Such a key is depersonalized because it does not contain any sensitive data i.e. fraudsters are unable to find out the key owner. That is, even it is stolen it won’t enable attackers to get access to your data because the transformation of biometrics data into code is irreversible.

Liveness detection is another element of SVORT’s system that determines whether SVORT interacts with a human being. Face liveness detection is based on computer vision technologies and deep learning algorithms with face detection and tracking at their core therefore photo/video/mask spoofing or side-channel attacks can not override the system.

Liveness detection’s security is provided by the system of rotational challenges. A user can be asked to smile, blink, turn his head, raise eyebrows, etc. Therefore fraudsters won’t be able to intercept into authentication process as it is impossible to get prepared for such a challenge as tasks vary every time.

Leveraging neural networks, face liveness detection, and biometrics, we get troublefree authenticator that prevents all kinds of spoofing and protects data reliably.

Here you can read more on what is neural-biometrics and how liveness detection in SVORT works. This article covers in detail how to use SVORT for authentication. If you are interested in SVORT, please leave a request on our website and we will send you our demo. It is free and will remain free for individual users.

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Your digital accounts are at fraud risk was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.

Biometrics identification recognizes a person through the facial image. It enables users to open a bank account or sign up in a sharing service or perform any other action that requires identification without leaving home.

It is advantageous to both users and businesses as biometrics identification cuts expenses, reduces the time of customer service, prevents fraud, automates business processes and increases profit.
We have described 3 unobvious ways to extract use from the technology. Read on to learn how it can boost your business and save resources.

How does SVORT perform identification?

The neural network learns to identify people and performs the action needed like opening a door or providing access or confirming identity, etc. SVORT operates not on a person’s image but on his biometrics data that actually is a depersonalized anonymous biometrics key.

The infallible liveness detection saves users from being counterfeited. In terms of biometrics, liveness detection is the computer’s ability to determine whether it interacts with a human being. Although our liveness detection tests excellent we reiterate that its efficiency also depends on hardware characteristics like computer or webcam specifics, depth sensors in the camera, etc.

United with a special neural network algorithm and biometrics liveness detection prevents spoofing and makes SVORT invulnerable for forgery of identity. Click here for more details on how SVORT provides its users with security.

The most efficient ways of identification implementations

Here at SVORT, we can perform any case using identification. Actually, SVORT is software development kit (SDK). It is the set of tools that enables us to build a custom solution that can be successfully adapted for any existing software and requirements. The most demanded cases are the following.

Physical access by face

This option is available for both customers and employees. Use physical access by face for the following purposes:

• to replace traditional keys, passes, and magnetic card keys;
• to control the time of arrival and leave of employees;
• to limit access to certain premises;
• to prevent strangers’ from entering the building.

Replacing traditional keys and passes with identification system increases turnstiles capacity and prevents troubles for forgotten, lost or stolen keys. This is how the identification of employees works:

• SVORT is integrated into the current system of video surveillance and turnstiles;
• employees continue to use the adopted methods of gaining access to the office;
• meanwhile the neural network remembers employees and learns to recognize them;
• in a couple of days, the SVORT will open the turnstile or door in front of the identified employee even before he can even pull out the key from his pocket, which he actually no longer needs.

Here it is explained in detail why your business needs the IAM system. By the way, SVORT can be used not only for controlling physical access to buildings/premises but also for access to workstations or certain programs/services/etc.

Such measures taken would prevent data breaches and protect sensitive business data. Details on the use of SVORT as an additional security factor within MFA are written here.

Customers recognition

Identification can bring your business the following benefits:

• to identify VIPs and other customers;
• to notify receptionists when VIPs or other identified customers enter the building/office/shop/etc.;
• to replace loyalty cards;
• to collect and analyze data.

Improving customer service with identification SVORT also improves internal business processes providing due to data analytics. The last point implies a wide range of functions so it is worthy to discuss it separately.

Identification for analytics

A business must know its customers to develop and apply a development strategy successfully. SVORT provides you with the following information:

• Who are your customers?
• How often do they need your services?
• What time and what days of the week do they usually come to you?
• How much time do they spend in your place?
• Do they leave satisfied or disappointed (possible if the emotion recognition system is integrated)?

For these purposes SVORT performs the following actions:

• learn to identify your customers;
• control the time they come and leave;
• count how many time do they spend in your place;
• collect and analyze this data providing you with access to analytics.

The emotion recognition system can be integrated into SVORT to improve the quality of service. It will also help the business owner analyze what exactly affects the level of customer satisfaction.

Once the data is collected, your task is only to interpret it correctly and make a decision that will benefit your customers while improving the business.

Our neural-biometrics access management system can be applied not only for identification but in a variety of other ways. Tell us about your business, and we will tell you how SVORT can automate processes, enhance services, save resources, and boost your enterprise.

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Using SVORT for identification was originally published in SVORT on Medium, where people are continuing the conversation by highlighting and responding to this story.