Gaming’s Shift from Web 2.0 to Web 3.0 G-Link Mobile Blockchain

Traditional gaming is a large but plateauing industry, plagued by legacy problems — in contrast, blockchain gaming is a sunrise industry with exponential growth potential. The number of daily Unique Active Wallets (UAW) interacting with game-related smart contracts shot to 1.3 million as of the end of 2021, up from 28,000 as of end 2020, representing a 4642% year-on-year rapid increase in adoption. The traditional gaming industry is estimated to have around 3.2 billion gamers globally. Still, blockchain gaming has only captured approximately 0.04% of the available players who generated US$178.37 billion in traditional gaming revenue in 2021.

Web 3.0 gaming

G-Link is designed to be the Web 3.0 games ‘app store’, ideally positioned to give the global 2.7 billion traditional mobile gamers a smooth and enjoyable experience in blockchain gaming. G-Link makes it hassle-free to begin playing games on the blockchain, by offering a familiar and simple Web 2.0 account registration to get started. Connecting gamers, game developers, and investors, G-Link will be the go-to platform for Web 2.0 users who want the best of both webs — earning while playing fun casual to mid-core games.

To start it off, G-Link will be publishing 4 P2E mobile games in 2022: Racetrack game Kartopia; strategy-based collectible card game Card Master; simulation kingdom-building game SPE Colony; arcade game Coin Fishing Frenzy. On top of that, G-Link is in talks with over 10 studios to bring a diverse range of games to the platform. With an ever-expanding gameverse where mobile gamers will be spoilt for choice, the G-Link platform is built for flexibly exploring new games. The comprehensive platform includes features designed to address Web 3.0 gaming’s most prevalent and fundamental problems. Specifically, the GLINK platform token enables higher throughput and lower gas fees, which are critical infrastructures for improving the element of interactivity in gameplay mechanics. GLINK also provides cross-chain and cross-game liquidity, such that gamers can easily switch between games and securely exchange assets. Meanwhile, the GameFi incubator and NFT marketplace support smaller game developers with funding and resources, thereby encouraging open innovation.

Investors can reap passive returns from the sunrise blockchain gaming industry without being a gamer themselves, through several avenues on G-Link’s platform. This includes holding G-Link’s Chief Toad NFTs, GLINK tokens, staking, becoming a virtual landlord, and backing projects via the incubator. GLINK holders can earn up to a higher APR of 1.8-200% with locked staking of 3 different durations, or retain liquidity with the flexible staking option to earn up to 1-2.8% APR.

G-Link’s platform

Being the genesis collection, Chief Toad NFT holders are given VIP membership access into G-Link’s gameverse platform. The utilities of Chief Toad include the privilege to create guilds in the gameverse, gain early access to games in beta and sales of virtual land, higher in-game earnings, and priority access to the GLINK token IDO whitelist. Those who want to get in early to the G-Link platform should mint their own Chief Toad. The Chief Toad NFT collection’s mint date falls from 5-7 July 2022. A total supply of 10,000 is available, at 0.08-0.1ETH.

G-Link’s IDO

G-Link’s Initial DEX Offering (IDO) for its platform GLINK token will be happening in August 2022. The GLINK token has a total supply of 1 billion tokens and uses the ERC-20 standard.

All transactions on G-Link’s platform will be facilitated by the GLINK token:

* GSwap – Seamlessly trade between in-game currencies

* Provide seed investment to back your dream game

* DAO voting rights

* Staking in the liquidity pool

* Purchase of in-game assets, NFTs, and virtual lands

Chief Toad NFT owners will have advantages in the form of a higher percentage of airdrops and guaranteed whitelists for the GLINK token pre-sale.

G-Link is building the ecosystem that links the gaming community of gamers, game developers, and investors. With the GLINK token enabling a gameverse of fun blockchain games, games incubator, NFT marketplace, and the GSwap trading network, G-Link aims to bring Web 2.0 users to Web 3.0, through mobile gaming.

SE Ranking

What is SE Ranking?

SE Ranking is a single, tool-packed platform that enables you to perform all of the integral SEO tasks like keyword research, competitive analysis, rank tracking, website audit, backlink check, and much more. SE Ranking offers solutions for entrepreneurs, SMBs, and digital agencies, so no matter how many projects you have, the platform is always fast and comfortable to work with.

SE Ranking tools and features

1) Keyword Rank Tracker keeps track of your keyword search ranking in Google, Bing, and Yahoo for any location, language, and device. Plus, you can track Google rankings on mobile and desktop devices, as well as check which SERP features are present for the keywords you’re tracking.

2) Competitor Research tool for SEO and PPC helps you analyze competitor keyword strategies for both paid and organic search, and their Google Ads history.

3) Website Audit checks all your pages and subdomains against tech parameters that are crucial for SEO. For every found error, the tool suggests its level of urgency and how it can be fixed.

4) Backlink Checker helps you sort out your link-building priorities and examine the backlink strategies of your competitors.

About SE Ranking.

The main goal of our company is to make SEO accessible to everyone, regardless of their level of expertise. For example, if you are new to search optimization, SE Ranking will help you get started off on the right foot and with ease. And if you are a seasoned expert, you won’t have to go through that annoying process of getting used to the new interface and going through a learning curve – our tools are ridiculously simple and intuitive. If you’re serious about making your business visible online and are ready to give it your all to bring more organic traffic to your site – SE Ranking is ready to become your faithful helper. Our support team is already eager to walk you through the onboarding process, and support you every step of your journey. But if you want to take things at your own pace, we have plenty of help videos and articles that will help you figure out all the nooks and crannies of SE Ranking.

Microsite

What is a microsite?

A microsite is a small-scale website that businesses can use to promote an individual product, sub-brand, campaign, event, or competition. They can be made up of a single web page or a small cluster of pages.Microsites are hosted separately from a brand’s main website. They usually have their own unique domain names, but they can be hosted on a subdomain too. These simple sites don’t include ‘About us’ pages or information about brand values. They don’t usually have eCommerce functionality either. Instead, they feature informative, fun, or interactive content that aims to engage visitors.

Benefits

Microsites can help brands achieve a multitude of marketing goals. Whether they want to supercharge a product launch, generate leads, or target audience segments with specific content, microsites can help. Whether you want to build top-of-mind awareness for a new product or highlight a brand partnership, microsites can keep visitors focused on the information you want them to see. They won’t get distracted by an unrelated page or click on the wrong button. Instead, microsites allow brands to manage and monitor the consumer journey.

Because microsites concentrate on one particular product, brand, target market or promotional campaign, the analytics gathered are highly accurate and informative. Analyzing data from your main brand website will generally provide less conclusive results. This means microsites can be optimized for maximum impact. But a microsite is also the perfect medium for testing out new content. Brands can then use this data to make informed business decisions.

Disadvantages of a microsite

When implemented for the right reasons, a microsite benefits your brand in countless ways. But there are some downsides too.

It requires a lot of investment

Building a website from scratch requires significant time and money. You’ll need the help of designers, developers, and copywriters. Then there are ongoing costs like domain registration and site maintenance. While a microsite won’t require complex coding, it will cost more than adding pages to an existing brand website.

They’re only temporary

Once your event, campaign, or competition ends, the microsite you created is no longer useful. So you need to consider if it’s worth the investment.

Efforts

In the past, many microsites enjoyed SEO success. Brands dominated search results with multiple domains and used backlinks to boost their main site. But Google has adopted it. Today, microsites don’t often generate huge amounts of organic traffic. They may even compete with your main website for keywords and backlinks – especially if you duplicate content. That’s why modern microsite campaigns are often launched alongside paid advertising campaigns.

Use a microsite

We’ve already touched on lots of situations where microsites can prove useful. But here is an overview of what to consider before deciding to create one.

Is your content long-term or temporary

Microsites are ideal for one-off events, temporary advertising campaigns, and seasonal product promotions. Any content that doesn’t need to be on your brand’s main website year-round could be a contender.

Running an ad campaign alongside 

Microsites work particularly well as landing pages for PPC ads. That’s because brands can send prospects to a microsite related to the ad viewed. By providing relevant content and clear navigation, brands can keep visitors’ attention and nudge them to take action.

 Building awareness for a specific initiative

If you want to direct attention to a specific product, sub-brand, influencer collaboration, brand partnership, event, or any other company initiative, building a microsite might be the right choice.

Targeting a specific audience segment

If you’re creating content for a subset of your target audience, hosting this content on its own website is advisable. This will give your brand the freedom to create distinctive content that will appeal to this audience segment – without alienating other key demographics.

Is your content experimental

If you’re trying out something new, creating a microsite will allow you to accurately track the results without running the risk of ruining your main website’s user experience.

Create a microsite

The process of creating a microsite will vary depending on your brand’s goals and needs. But here are some general steps to follow.

Set out your objectives

Be clear about why you’re building a microsite and who it’s for. What do you want to achieve? Is a microsite the right solution? Have you created a buyer persona yet?

Choose a domain name

Be sure to buy a domain name that will appeal to your target audience. Will it stand out and be memorable enough for visitors to find again? Is it short enough to use offline?

Craft the content

Content is key when it comes to building a successful microsite. You need to connect with your target persona, while also considering how the keywords used could impact your brand’s main website. It may make sense to prioritize a niche keyword that won’t compete with your parent website.

Design your microsite

Your microsite should have a simple design that directs users toward a single CTA. But you can also get creative with color and visuals because you aren’t restricted by the branding of your parent brand’s website.

Connect your analytics and marketing tools

Because microsites provide in-depth insights into content performance and visitor behavior, hooking up your analytics tools of choice is essential. Integrating an A/B testing solution is a good idea too.

Peer-to-peer network

In the simplest terms, a peer-to-peer network is a network created whenever two or more devices (usually a computer) are connected and share the resources. But what creates the main difference here is that a peer-to-peer network, unlike the conventional network systems, forms an ecosystem where the computers are connected through a single server computer. It can also be seen as a network where multiple computer systems are connected through a single server that enables the transfer of files from one end to the other.  Moreover, a peer-to-peer network also serves the role of a permanent infrastructure that can connect more than a dozen computers in a small region amidst the conventional offline environment. In addition to this, if you want to learn more about peer-to-peer networks and how they can be beneficial in the field of blockchain, you can go for a blockchain certification course from any certified platform. 

While these networks have now become a very common thing, there are many other benefits to using a peer-to-peer network that gives it an edge over the others. Here are a few reasons why –

1) It is extremely tough to bring them down. Even if one of the sections is about to shut down, other pairs continue to operate and communicate, which ensures that the network does not stop working even if a single unit is not able to perform its functions. 

2) These networks are highly scalable because adding new peers is an extremely easy and quick process as you don’t have to perform any central configuration on the server.

3) P2P networks are best when it comes to filing sharing. Due to the fact that it is so quick in its processing, it becomes extremely easy to have the same file stored on multiple peers. It ensures that every time someone needs to download a particular file, the downloading process from multiple locations can take place simultaneously without any hassle. 

Peer-to-peer network

 Architecture is a kind of network where there is absolutely no division of activities among various other sections. Every node performs the same task and set of actions where each device serves the purpose of both the server and the client. Response of network architecture established over the computer networking ecosystem under this model is such that each and every workstation is responsible for equal tasks but fewer devices are connected to the main server. The peer-to-peer network architecture is most suitable for residential areas and small-scale businesses in smaller regions. This is because in such networks every device plays an independent role as a workstation as it has the access to save the entire set of data in its own database

To state in layman’s language, the general peer-to-peer architecture is designed keeping in mind the functionalities of a single software program. In this way, every program is responsible to perform its task while fulfilling the role of both client and server carrying similar responsibilities and abilities. Moreover, if you wonder about basics, you can also get multiple content pieces to help you throughout the process.

 

Further, peer-to-peer networks can be classified into two major categories based on how the sections in the network are linked to each other. Here are the two major types –

Unstructured networks: An unstructured peer-to-peer network is one where the links in the network are established randomly. Such networks are easy to construct as any new peer that would like to join and contribute to the network can do so by copying the existing links of another section and then forming and spreading its own links. 

However, it is equally important to know that the queries may not always get a resolution in unstructured networks so there can be hassles. For instance, a popular piece of content may be available to certain peers but if any other is looking for content that is rarely available, then the user may not be able to search for it.

Structured networks: Unlike unstructured networks, the structured ones allow each peer to look after a specific section of the content over the network. These networks assign a specific value to each content and peer in the network which is then followed by a common protocol that determines which section is responsible for which part of the content. In this way, whenever someone reaches out to a peer to search for content, the network uses the common protocol to determine the section responsible for data transfer and direct the search query towards the peer responsible for it.

Uses of P2P network 

Peer-to-peer technology has undeniably paved the way for several other technologies that integrate with its architecture to provide greater and better services to the users. Apart from blockchain, which you can learn in any top-rated blockchain classes, there are various other applications of peer-to-peer networks.

However, there are few areas where P2P networks find quite different applications. Let us take you through some of the most common applications where peer-to-peer networks are predominantly used. 

Peer-to-peer and copyright infringement

The first and most obvious application of a P2P network is associated with copyright infringement. As these file-sharing networks use the devices from both the end of the client and the server, it becomes one of the most commonly used platforms for sharing electronic media, mostly for pirated content. In addition to this, these networks also find their application in distributing malicious software such as spyware and viruses. It means that by installing any peer-to-peer file-sharing software on a device, anyone can access the files among millions of other users, irrespective of whether the person is doing it intentionally or not. However, with such networks, people who lawfully buy the content online may also get in trouble. So, it is always advisable to take the necessary precautions.

 File Sharing

File sharing is another significant application of peer-to-peer networking that takes place through file-sharing technology. As the name itself implies, it allows the users to access and transfer various kinds of multimedia files such as videos, images, music, etc. So, basically, you can use a file-sharing network across various devices to transfer any kind of file you want. 

Blockchain 

As a technology, a P2P network is based on the concept of decentralization. The foundational architecture of blockchain technology similarly enables a user to transfer cryptocurrency across the globe without needing any middleman or intermediary. With such a decentralized distribution, it becomes easier for any individual to become a part of this process of verification.

When a peer-to-peer network is enabled on a blockchain, the network helps in the maintenance of a complete replica of the records ensuring the accuracy of data. On the other hand, it also offers greater security as compared to conventional client-server systems. Therefore, a peer-to-peer network works phenomenally when used with blockchain technology. If you wish to learn more about the foundational concepts of blockchain, make sure to pick up the best blockchain training platform for it. 

Content Delivery Acceleration 

If there is one network service that can significantly help in reducing delivery costs, it has to be a P2P content delivery network. The technical functionalities of a peer-to-peer network can potentially integrate with any content delivery system and offer a wide range of service capabilities. One of the most famous examples of such a content delivery network is Alibaba Cloud’s peer-to-peer content delivery network that is based on the same technology where these two worked as components that can effectively manage content delivery even during significantly high traffic. 

Robotic Process Automation

What Is Robotic Process Automation (RPA)?

Robotic process automation (RPA) occurs when basic tasks are automated through software or hardware systems that function across a variety of applications, just as human workers do. This can greatly reduce labor costs and increase efficiency by speeding things up and greatly minimizing human error. The software or robot can be taught a workflow with multiple steps and applications, such as taking received forms, sending a receipt message, checking the form for completeness, filing the form in a folder, and updating a spreadsheet with the name of the form, the date filed, and so on. RPA software is designed to reduce the burden for employees of completing repetitive, simple tasks.

1) Robotic process automation (RPA) refers to software that can be easily programmed to do basic, repetitive tasks across applications.

2) RPA creates and deploys a software robot with the ability to launch and operate other software.

3) Designed primarily for office-type functions, RPA works like a digital assistant, doing routine onerous tasks that would otherwise eat up employees' time.

4) RPA today is found across a range of industries and applications.

5) RPA without human oversight, however, can lead to problems, as was the case with mortgage "robot-signers."

Robotic process automation (RPA) is designed to help primarily with office-type functions that often require the ability to do several types of tasks in a specific order. It creates and deploys a software robot with the ability to launch and operate other software. In a sense, the basic concept is similar to traditional manufacturing automation, which focuses on taking one portion of a workflow—or even just one task—and creating a robot to specialize in doing it.

Benefits of Robotic Process Automation (RBA)

The software used in process automation is programmed to do the tasks in a particular workflow by the employees with minimal assistance from human workers. The software doesn’t learn on its own or seek to tweak out new efficiencies or new insights like big data analysis or enterprise resource management (ERM) software. Instead, RPA works like a digital assistant for employees by clearing the onerous, simple tasks that eat up part of every office worker’s day.

As such, RPA is a simpler product than an artificial intelligence-driven system or enterprise software that seeks to bring all data inside the platform. This also makes it a relatively cheaper product than AI or ERM software. This simplicity and relative cheapness can make RPA a more attractive solution for many companies, particularly if the company has legacy systems. Robotic process automation is designed to be compatible with most legacy applications, making it easier to implement compared to other enterprise automation solutions.

RBA Be Applied

RBA is quite common in the financial services industry. With increasing compliance and regulatory filing requirements, the finance industry—banks, insurers, and investment management companies—has been an early adopter of RPA. Many onerous back-office functions, such as ensuring an up-to-date know your client (KYC) form is filed or a recent credit check is included on a loan application, are ideal for RPA. Removing this burden from employees allows them to focus on high-return tasks. More importantly, the software can clear these basic filing and data manipulation functions faster than humans, reducing the overall processing time.Of course, RPA is not just limited to finance. Any industry that deals in data and filing can benefit from robotic process automation. When software can reduce costs and increase efficiency without requiring an onerous and complex implementation, it will find eager users and useful applications in almost any sector. Indeed, RPA has also been found useful in the following fields:

• Customer service and CRM
• Accounting
• Healthcare
• Human resources
• Supply chain management

RPA does, however, have its drawbacks. These systems can be expensive to customize and deploy, and may not be suitable for more complex tasks that require some degree of human judgment or creativity.RPA systems, when unchecked, can also go awry. One example is the case of so-called "robo-signers" used in the mortgage industry. These systems rubber-stamped foreclosure documents on homeowners automatically, even when the foreclosure was questionable or avoidable. Moreover, this practice failed to meet government regulations for oversight of the foreclosure process in the mid-2010s, leading to a scandal following the housing market bubble of the 2008-09 financial crisis. Following the public exposure of Robo-signers, foreclosure documents had to be manually reexamined, and the companies involved faced disciplinary action.

Machine Learning

What Is Machine Learning

The robot-depicted world of our not-so-distant future relies heavily on our ability to deploy artificial intelligence (AI) successfully. However, transforming machines into thinking devices is not as easy as it may seem. Strong AI can only be achieved with machine learning (ML) to help machines understand as humans do.

Machine Learning Work

Similar to how the human brain gains knowledge and understanding, machine learning relies on input, such as training data or knowledge graphs, to understand entities, domains, and the connections between them. With entities defined, deep learning can begin. Machine learning begins with observations or data, such as examples, direct experience, or instruction. It looks for patterns in data so it can later make inferences based on the examples provided. The primary aim of ML is to allow computers to learn autonomously without human intervention or assistance and adjust actions accordingly.

Machine Learning Important

Machine learning as a concept has been around for quite some time. The term “machine learning” was coined by Arthur Samuel, a computer scientist at IBM and a pioneer in AI and computer gaming. Samuel designed a computer program for playing checkers. The more the program played, the more it learned from experience, using algorithms to make predictions. As a discipline, machine learning explores the analysis and construction of algorithms that can learn from and make predictions on data.ML has proven valuable because it can solve problems at a speed and scale that cannot be duplicated by the human mind alone. With massive amounts of computational ability behind a single task or multiple specific tasks, machines can be trained to identify patterns in and relationships between input data and automate routine processes.

Data Is Key:

The algorithms that drive machine learning are critical to success. ML algorithms build a mathematical model based on sample data, known as “training data,” to make predictions or decisions without being explicitly programmed to do so. This can reveal trends within data that information businesses can use to improve decision-making, optimize efficiency and capture actionable data at scale.

AI Is the Goal: 

ML provides the foundation for AI systems that automate processes and solve data-based business problems autonomously. It enables companies to replace or augment certain human capabilities. Common machine learning applications you may find in the real world include chatbots, self-driving cars, and speech recognition.

• Data security: 
• Machine learning models can identify data security vulnerabilities before they can turn into breaches. By looking at past experiences, machine learning models can predict future high-risk activities so the risk can be proactively mitigated.
• Finance: 
• Banks, trading brokerages, and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America is using a chatbot, Erica, to automate customer support.
• Healthcare: 
• ML is used to analyze massive healthcare data sets to accelerate the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human error
• Fraud detection: 
• AI is being used in the financial and banking sector to autonomously analyze large numbers of transactions to uncover fraudulent activity in real-time. Technology services firm Capgemini claims that fraud detection systems using machine learning and analytics
• Retail: 
• AI researchers and developers are using ML algorithms to develop AI recommendation engines that offer relevant product suggestions based on buyers’ past choices, as well as historical, geographic, and demographic data.

Machine learning offers clear benefits for AI technologies. But which machine learning approach is right for your organization? There are many ML training methods to choose from including:

• supervised learning
• unsupervised learning
• semi-supervised learning

Supervised Learning: 

Supervised machine learning algorithms apply what has been learned in the past to new data using labeled examples to predict future events. By analyzing a known training dataset, the learning algorithm produces an inferred function to predict output values. The system can provide targets for any new input after sufficient training. It can also compare its output with the correct, intended output to find errors and modify the model accordingly.

Unsupervised Learning: 

Unsupervised machine learning algorithms are used when the information used to train is neither classified nor labeled. Unsupervised learning studies how systems can infer a function to describe a hidden structure from unlabeled data. At no point does the system know the correct output with certainty. Instead, it draws inferences from datasets as to what the output should be

Reinforcement Learning: 

Reinforcement machine learning algorithms are a learning method that interacts with its environment by producing actions and discovering errors or rewards. The most relevant characteristics of reinforcement learning are trial and error search and delayed reward. This method allows machines and software agents to automatically determine the ideal behavior within a specific context to maximize its performance. Simple reward feedback — known as the reinforcement signal — is required for the agent to learn which action is best.

Biometrics Technologies

Biometrics is the measurement and statistical analysis of people's unique physical and behavioral characteristics. The technology is mainly used for identification and access control or for identifying individuals who are under surveillance.

How do biometrics work?

Authentication by biometric verification is becoming increasingly common in corporate and public security systems, consumer electronics and point-of-sale applications. In addition to security, the driving force behind biometric verification has been convenience, as there are no passwords to remember or security tokens to carry. Some biometric methods, such as measuring a person's gait, can operate with no direct contact with the person being authenticated.

Components of biometric devices include the following:

1) a reader or scanning device to record the biometric factor being authenticated

2) software to convert the scanned biometric data into a standardized digital format and to compare match points of the observed data with stored data; and

3) a database to securely store biometric data for comparison.

Biometric data may be held in a centralized database, although modern biometric implementations often depend instead on gathering biometric data locally and then cryptographically hashing  it so that authentication or identification can be accomplished without direct access to the biometric data itself.

Types of biometrics

The two main types of biometric identifiers are either physiological characteristics or behavioral characteristics.Physiological identifiers relate to the composition of the user being authenticated and include the following:

1) facial recognition

2) fingerprints

3) finger geometry

4) iris recognition

5) vein recognition

6) retina scanning

7) voice recognition

8) DNA (deoxyribonucleic acid) matching

9) digital signatures

Behavioral identifiers include the unique ways in which individuals act, including recognition of typing patterns, mouse and finger movements, website and social media engagement patterns, walking gait and other gestures. Some of these behavioral identifiers can be used to provide continuous authentication instead of a single one-off authentication check. While it remains a newer method with lower reliability ratings, it has the potential to grow alongside other improvements in biometric technology.

Biometric data can be used to access information on a device like a smartphone, but there are also other ways biometrics can be used. For example, biometric information can be held on a smart card, where a recognition system will read an individual's biometric information, while comparing that against the biometric information on the smart card.

Advantages and disadvantages of biometrics

The use of biometrics has plenty of advantages and disadvantages regarding its use, security and other related functions. Biometrics are beneficial for the following reasons:

• hard to fake or steal, unlike passwords;
• easy and convenient to use;
• generally, the same over the course of a user's life;
• nontransferable; and
• efficient because templates take up less storage.

      Disadvantages, however, include the following:

• It is costly to get a biometric system up and running.
• If the system fails to capture all of the biometric data, it can lead to failure in identifying a user.
• Databases holding biometric data can still be hacked.
• Errors such as false rejects and false accepts can still happen.
• If a user gets injured, then a biometric authentication system may not work -- for example, if a user burns their hand, then a fingerprint scanner may not be able to identify them.
• Law enforcement.It is used in systems for criminal IDs, such as fingerprint or palm print authentication systems.
• United States Department of Homeland Security. It is used in Border Patrol branches for numerous detection, vetting and credentialing processes -- for example, with systems for electronic passports, which store fingerprint data, or in facial recognition systems.
• Healthcare. It is used in systems such as national identity cards for ID and health insurance programs, which may use fingerprints for identification.
• Airport security. This field sometimes uses biometrics such as iris recognition.

Security and privacy issues of biometrics

Biometric identifiers depend on the uniqueness of the factor being considered. For example, fingerprints are generally considered to be highly unique to each person. Fingerprint recognition, especially as implemented in Apple's Touch ID for previous iPhones, was the first widely used mass-market application of a biometric authentication factor.Other biometric factors include retina, iris recognition, vein and voice scans. However, they have not been adopted widely so far, in some part, because there is less confidence in the uniqueness of the identifiers or because the factors are easier to spoof and use for malicious reasons, like identity theft.

Stability of the biometric factor can also be important to acceptance of the factor. Fingerprints do not change over a lifetime, while facial appearance can change drastically with age, illness or other factors.The most significant privacy issue of using biometrics is that physical attributes, like fingerprints and retinal blood vessel patterns, are generally static and cannot be modified. This is distinct from nonbiometric factors, like passwords (something one knows) and tokens (something one has), which can be replaced if they are breached or otherwise compromised. A demonstration of this difficulty was the over 20 million individuals whose fingerprints were compromised in the 2014 U.S.office of personnel mangagement data breach.

The increasing ubiquity of high-quality cameras, microphones and fingerprint readers in many of today's mobile devices means biometrics will continue to become a more common method for authenticating users, particularly as Fast ID Online has specified new standards for authentication with biometrics that support two-factor authentication with biometric factors.While the quality of biometric readers continues to improve, they can still produce false negatives, when an authorized user is not recognized or authenticated, and false positives, when an unauthorized user is recognized and authenticated.

Biometrics secure

While high-quality cameras and other sensors help enable the use of biometrics, they can also enable attackers. Because people do not shield their faces, ears, hands, voice or gait, attacks are possible simply by capturing biometric data from people without their consent or knowledge.An early attack on fingerprint biometric authentication was called the gummy bear hack, and it dates back to 2002 when Japanese researchers, using a gelatin-based confection, showed that an attacker could lift a latent fingerprint from a glossy surface. The capacitance of gelatin is similar to that of a human finger, so fingerprint scanners designed to detect capacitance would be fooled by the gelatin transfer.Determined attackers can also defeat other biometric factors. In 2015, Jan Krissler, also known as Starbug, a Chaos Computer Club biometric researcher, demonstrated a method for extracting enough data from a high-resolution photograph to defeat iris scanning authentication. In 2017, Krissler reported defeating the iris scanner authentication scheme used by the Samsung Galaxy S8 smartphone. Krissler had previously recreated a user's thumbprint from a high-resolution image to demonstrate that Apple's Touch ID fingerprinting authentication scheme was also vulnerable.