What Is Facial Scanning? What Are the Threats Involved in It?

Facial scanning seemed like a fantasy a few years ago, but today we can open our mobile phones by scanning our faces. Millions of people are happy to access their smartphones with facial scanning worldwide. Facial scanning technology has a rapid increase in corporate organizations, airports, mobile phones, and shopping malls. Although facial recognition has advantages to companies, biometric technology also poses threats that both companies and users are concerned about in recent years. Although many automobile companies still introduce facial scanning technology.

More Info: 312-50: Certified Ethical Hacker (CEH)

Technological developments continue to open new ways in which organizations can use face template data to improve their efficiency and reliability. It is common to unlock a smartphone with facial scanning or check-in at the airport with your face today. Although the technology for facial scanning has brought countless advantages, its use also carries substantial privacy risks. This article talks about facial scanning technology, threats that evolved in it, and how to mitigate them.

What Is Facial Scanning Technology?

Facial scanning is a new age technology computerized to match a human face among a huge record of images or videos of faces in a database called a facial recognition database. The primary purpose of facial scanning is to authorize users against identity verification services by mapping out the features of a facial structure and distinctive details such as distance between eyes, the shape of the nose, etc., from an array of provided images or videos.

The technology of facial scanning attracts a lot of attention. Many companies and organizations use online recognition and verification to achieve their desired objectives, whether for fun, security, or user experience. Facial scanning is a biometric check that can identify or verify an individual to compare and analyze patterns based on the person’s facial contours.

Facial recognition uses deep learning algorithms to make it more likely to have fewer errors compared. Deep learning is a form of machine learning that provides data to learn from artificial neural webs, human-inspired algorithms. A deep learning algorithm would repeat a task, modifying it each time to improve the outcome. It identifies and captures the human face and then becomes an object of verification based on the essential characteristics of the face. These characteristics are generally the position of the eyes, the nose, and the corners of the mouth.

◉ For instance, facial scanning firstly scans the distance between your eyes, nose, and mouth, the shape of your nose and mouth, and a variety of all other minor details on the face.

◉ Once all features on your face are identified, a face signature will be created. Finally, once the face is scanned, a database with known faces is compared for a match again.

How does Facial Scanning Technology Work?

Humans can identify faces quickly. You will likely find the facet of an individual, a friend, or an acquaintance in your family. Your face features — the distance between the arch of your eyebrows and eyes, the tilt of your lips, position of your nose, etc. comprise your unique facial structure; this is how it works but on a large, algorithmic scale. Recognition technology sees data where you see a face. This information can be saved and accessed.

Face detection

Firstly, facial scanning begins with a face and identifies the appropriate face characteristics of the person. We think the human face is a basic set of eyes, nose, and mouth characteristics. Like that, the facial scanning technology recognizes the face; this is done through an extensive database of images with human sides looking at different points of view with deeper neural network & machine learning algorithms.

It starts with eyes, then eyebrows followed by nose and mouth begins to calculate the nose width, distance from forehead to mouth, and sizes. Once all the features are identified on the face region, the algorithm’s numerous algorithm training is performed on databases to detect faces.

· Face recognition

After the face is identified, a program is designed to detect the facial landmarks with an image processing algorithm. Each landmark on the face is referred to as nodal points about 80 on every human face. These landmarks are very crucial in identifying the face in the database. Now the face registered in the database is repositioned and appropriately scaled to match the original face as it is beneficial to recognize when the facial expressions change.

· Face representation

After the face is registered, the face’s nodal points, position, and sizes are sent into the software. Later, the software assigns a new face vector for every individual face in numerical codes called faceprints. Now, each faceprint distinguishes from person to person in the database.

Face matching

Lastly, after the face is recognized with the new vector code, it is compared to the faces available in the database, consisting of all registered faces. If the software detects the exact match in the database, it will give the person’s information, or else the interface classifier returns the vector code to the database.

Applications of Facial Scanning Technology

· Attendance in school

most schools have begun to implement facial scanning technology to automate students’ attendance; this helps the teachers spend less time taking the student’s attendance of larger strength and focus on teaching more. The advantage of the automated facial scanning attendance system is that no proxies can be given. It is also good to keep track of the whole campus to avoid threats.

· At airports

Airports must have facial scanning to track the passengers or people entering and going out of the airport. The security department uses this technology to identify the criminals, terrorists, and the people who exceeded the visas by comparing their photos in their existing database, which contains pictures of criminals and people who have exceeded their visas.

· Organizations’ access control

Facial scanning technology is now used in many corporate companies and other government offices for fast and effective access. As it helps in tracking everyone’s activities in the organization, identify the visitors. It also functions in enhancing security by immediately reporting any potential violations.

· Mobile apps

Many mobile apps, including Facebook Snapchat, also use facial scanning features. For instance, if a user clicks his/he selfie and can look how young or old or as the opposite gender or any other comic characters look just for entertainment. luxand is also a popular app specially designed for security purposes as it can identify faces in real-time.

· Banking

The banking sector uses facial scanning technology for making transactions more secure. Some businesses even started using pay-by-face counters as safe and fastest payment methods, unlike credit card payments and other forms, as it’s difficult to spoof the face.

Security Threats and Privacy Risks of Face Recognition

Like all other technologies, facial scanning also has significant downsides, such as cost, privacy threats, data hacking, and other crimes. There is also the risk of errors due to technological flaws.

· High costs required

Facial scanning requires high-quality, obviously costly cameras and advanced software. It is expected that technological advancements will lower the cost of facial recognition systems in the future.

Due to poor camera quality, facial scanning has a problem in identifying people with darker skin tones, so it is significantly less accurate to identify these people. So, it is challenging to determine the actual person. It can be a severe problem in law enforcement where misidentification can lead to an arrest of an innocent person instead of a criminal. It is expected that technological advancements will lower the cost of facial recognition systems soon.

· Data storage and theft

Facial scanning generally requires video and high-quality images, which need a significant amount of storage. It forces businesses to process everything on several machines at the same time, which is inconvenient.

Facial scanning generally requires video and high-quality images, which need a significant amount of storage which is an important issue. Few companies and law enforcement departments store their face recognition data on local servers, due to which data breaches occur. If data from facial recognition technologies are stored in the cloud, the data is most secure. It forces businesses to process everything on several machines at the same time, which is inconvenient.

· Loss of individual privacy

Individual privacy is adversely affected because of facial scanning technology. None of us like to have our faces stored in an unknown database. Confidentiality is a significant problem for everyone, especially in California that has prohibited facial scanning in real-time. In that case, police can use video recordings of video security devices owned by persons but cannot use software for live facial scanning

· Identification errors

Facial scanning may not always be completely accurate with the database on the faceprints. Errors usually happen because the images are insufficient or the database lacks information. Poor illumination or image quality can make it challenging to analyze the nodal points properly. When the face angles are blurred, the data are affected and cause errors in the faceprint and incorrect matches in the databases.

· Provide fraud opportunities

Cybercriminals also use facial scanning technology for criminal activities. They gather personal data, images, videos of an unknown person collected from facial scans and stored in databases. A hacker uses this information to obtain the credit card, debit card credentials of the victim.

How to Mitigate Facial Scanning Threats

Facial scanning technology has a wide range of applications in every industry, making it an easy target for cybercriminals to exploit and steal data from facial recognition databases. It is very crucial to take necessary precautions and mitigate cyber threats caused due to facial scanning technology.

◉ For excellent and proper data storage, the organization’s IT security team should maintain network security 24/7.

◉ Cybersecurity should be part of the organization’s security plan to ensure proper data storage to manage facial scanning technology

◉ Examine the company’s privacy and data security practices to learn who it shares data with.

◉ The organization must implement external audits for security measures and protocols, such as t SOC 2 certifications.

◉ External white hat security testing, such as penetration testing, is performed by the organization.

◉ An ethical hacker would help in securing the system from violations and vulnerabilities that attackers exploit. By using ethical hacking tools, the hacker would protect and prevent the attacks from occurring.

Facial scanning technology is effective but should be used effectively. It is advantageous for government offices, law enforcement, organizations, and end-users to increase their safety and track crimes. Besides, facial scanning also may be exploited and have severe consequences for the personal benefit of hackers. But by few safety measures, we can use it for intelligent work. It is estimated that the interaction between facial scanning and human rights and personal privacy will take at least 3 -4 years. We can then wait and expect huge industries to make it more user-friendly, transparent, and secure to enable everybody to benefit.

Source: eccouncil.org

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The Average Salary of a Certified Ethical Hacker (CEH)

A Certified Ethical Hacker (CEH) is an individual whom organizations hire to investigate the security of their online systems by trying to hack into them.

These ethical hackers, who are usually called “penetration testers,” recognize flaws in the system that an unethical hacker would exploit. By finding the hacks before a thief does, an organization can better protect itself against fraud. Nowadays, almost every organization across the world, whether it be online commerce and retail, hospitality, logistics and transport, real estate, healthcare, or any industry in between. Ethical hackers utilize some variant of ethical hacking to maintain their information the way it should be: secured! The average CEH salary ranges based on the geographics. Within each country, particular cities, states, or regions lean to pay more than others.

Median CEH Salary Ranges by Country:

United States

The average pay scale for a CEH is $71,331 per year. The salary can stretch from $24,760 to $111,502, with a bonus payoff between $0.00 and $17,500. Therefore, the total salary is roughly $24,760 – $132,322, all depending on what particular roles he or she executes, and the number of years of experience.
As a whole, a first-year CEH can presume to make around $60,000. After five to nine years of experience, that figure increases to approximately $71,000. After ten years of experience, a CEH can aspirer to earn roughly $91,500, expanding to $105,000 after 20 years.

The top five states or regions with the highest CEH salary are:

1. California– $103,459
2. Washington, D.C.- $97,081
3. Maryland– $93,768
4. New York– $92,606
5. Virginia– $92,056

CEH Salary Varies by Job Profiles:

• Cyber Security Analyst: $49,648 – $127,426
• Security Analyst: $50,180 – $126,205
• Penetration Tester: $50,684 – $126,205
• Security Engineer: $64,385 – $124,877
• Information Security Analyst: $53,743 – $106,875

Canada

In Canada, a CEH salary can ranges between C$62,288 and C$74,000 (almost $64,387 to $76,400). Those with experience of one to four years make about C$48,000. Those with 5 to 9 years earn almost C$63,300, while those with 10 to 19 years of experience in the ethical hacking field earn $C66,100 yearly.

The top five regions with the highest paying salary are:

1. New Brunswick– C$108,000
2. British Columbia- C$98,000
3. Quebec- C$75,000
4. Manitoba– C$72,166
5. Ontario– C$71,842

CEH Salary Varies by Job:

• Security Consultant: C$52,853 – C$113,044
•  Security Engineer: C$48,102 – C$135,353
• Cyber Security Analyst: C$44,335 – C$99,844
• Security Analyst: C$41,814 – C$91,895
• Penetration Tester: C$35,000 – C$96,000

How to Earn CEH Certification?

To be officially identified a CEH, an individual must be certified by the EC Council known as the International Council of Electronic Commerce Consultants. The EC-Council is an organization of individuals who are committed to staying up-to-date of any advanced technology advancements and distributing that knowledge to those who pass the certification exams. The Council honors itself on regularly contacting with professionals in the field and integrating examples from actual successful hacks.

The certification method requires several different components, including ethical hacking and countermeasures and penetration testing. The areas of study comprise foot-printing and survey, studying how to scan networks, viruses, system hacking, and worms, enumeration, SQL injection, denial of service attacks, hacking web applications and web servers, Trojans and backdoors, and cryptography, among others.

The program also demands all those who want to obtain the CEH title to listen to testimonials by practicing information security professionals. The idea is that by developing a community of information sharing, individual hacks are more straightforward to both detect and defeat. Many of the security professionals who give talks at the CEH training center have had comprehensive experience dealing with reasonably high profile systems which require rigorous testing regularly.

Summary

The earnings prospective of any individual is therefore very much affected not only by his or her training, but the conditions in which he chooses to work in, and his previous experience in the field. A freelance penetration tester, for instance, may charge higher “consultant” charges than a domestic CEH, based on that particular individual’s experience with the organization.

A software professional who determines to become certified may or may not experience an equivalent rise in salary based on the policies of his employer, and how much that certification and its equivalent skills are measured within the organization. Also, it is determined by the country you reside in; for example, the United States has a higher salary scale with the five jobs listed above, compared to Canada. CEH positions are challenging, interesting, and play exceptionally well, aspiring professionals to consider CEH as an excellent career booster.

If you want to get off from the beaten track, have a sharp eye for solving issues and a passion for security, the CEH certification is an excellent way for you to moveforward in your career.

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