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By Deniz Yurdasen, Sales Manager, Aratek Biometrics
According to multiple surveys, "behavioral biometrics" and "behavior recognition" have sparked a lot of interest in recent years. Once a sci-fi movie feature with only imaginable technology, it is slowly becoming a reality. Exciting and scary at the same time, depends on which end you are located at, behavior recognition and identification will be more discussed in upcoming years.
This post provides a basic overview of behavioral biometrics and behavior recognition, as well as how they will be used in the future. Let's get started.
Behavioral biometrics is a type of biometric that measures and analyzes a person's behaviors. Unlike other biometrics, behavioral biometrics focuses on the patterns of human behavior (such as typing speed and keystroke rhythm) rather than on physiological features (faces, fingerprints, or iris recognition).
Gait, keystroke rhythm, signature analysis, and even mouse movements are examples of behavioral biometrics, they can be collected in a variety of ways, including by video surveillance, smart sensors, mobile devices, some biometric devices, and more. The behavioral biometrics data can then be utilized to identify or authenticate a person using behavior recognition to prevent fraud, control access, and serve other purposes.
Although the behavioral biometrics and behavior recognition field mostly focuses on the human race, in parallel, we have seen studies, publications, and tests about animal behavior recognition. In this direction, the concept is to identify what species of four-legged animal it is (dog, fox, wolf, etc.), rather than identifying a single animal among the same kind, by observing its natural behavior.
Behavioral biometrics include gaits, keystroke rhythms, signature analyses, mouse movements, and other human behavior-related metrics.
Classifying and identifying human behaviors is not a new concept. It is a skill that humans have honed over thousands of years of evolution. In recent years, automated systems that can classify and recognize human behavior have made it easier to gather information about how people act. This method is now widely used to improve the security of a variety of applications.
"Behavior recognition" is a subfield of behavioral biometrics that refers to the fine-grained study of human behavior. Computer vision, deep machine learning (DML), artificial intelligence, and human-computer interaction are all part of this multidisciplinary field of study.
Recognizing human behavior is a complex process that includes measuring everything from how the user holds the phone or swipes the screen to which keyboard or gestural shortcuts they use, as well as routine patterns in human activity. Following that, a unique user profile is created using software algorithms to confirm the user's identity during subsequent interactions.
For behavior recognition, there are 2+1 steps to identify and authenticate users:
The goal of behavior recognition is to build computational models that can represent human behavior well enough to recognize and anticipate events in real time.
In the last decade, we have actually witnessed behavior recognition trials. Remember the supermarkets where people are tracked and watched to find out which aisle or product they look at the most? Or some retail store windows where a camera traces a consumer’s eye direction to identify which product gets more attention? These were the baby steps of behavior recognition, to improve marketing and sales efficiency, not to identify the person.
Behavioral biometrics is a rapidly expanding field of research and application, and the development and potential market can be huge. According to a market intelligence report, the Global Behavioral Biometrics Market was valued at USD 1.06 billion in 2020, and it is projected to be worth USD 3.91 billion by 2026, registering a CAGR of 25.62% during the period of 2021–2026.
This technology is often used for security purposes, as it can be difficult for criminals to mimic someone's behavior. Behavioral biometrics can be used to track a person's behavior over time, allowing for changes to be detected. This information can be used to improve security, as it can help identify potential threats.
Popular behavioral biometric tools currently only have limited ability to identify people based on patterns in activity like keystrokes, gaits, and signature dynamics. More AI tools are being developed to add extra behavior recognition models, such as eye movements and emotional responses. The technology can be implemented as part of
However, it is good to mention that behavioral biometrics probably will not replace the password or other forms of identity authentication, but it will help reduce the burden placed on them to protect sensitive information. Even the strongest password is only secure so long as it is secret. By offering an additional, continuous layer of identity assurance, behavioral biometrics prevent the password from being a single point of security failure. According to Finances Online, 81% of company data breaches are caused by poor passwords.
To get a better idea of how behavioral biometrics are useful, it's better to consider them with other types of biometrics. There are 3 types of biometrics:
Unlike traditional authentication methods for strong biometrics that work when a person’s data is collected, for example by touching a sensor, an advanced behavioral biometric system can authenticate continuously regardless of place and time, which is more charming than on-point or time-scheduled security measures.
First generation biometric techniques focused on strong biometrics due to their unique features and high identification success ratio. However, interestingly, second-generation biometrics turned their heads toward weak biometrics. Because as computation power, AI tools, cameras, sensors, and data mining technologies advanced, signals from the body or our natural behaviors suddenly became easier to read, analyze, and "identify."
There are some benefits of using behavioral biometrics, such as:
Behaviors are hard to mimic.
Unlike fingerprints, facial images, and iris scans, which require physical contact, behavioral biometrics can be collected without the subject having to come close to the device. This saves time and money and makes things much easier.
Since behavior recognition relies heavily on software algorithms, you can save the money for hardware devices. Also, it can be easily added to existing security systems with little or no cost.
Behavioral biometrics is a promising technology that has the potential to improve security while also being convenient for users. As this technology continues to develop, it is likely that we will see more and more applications for it.
When using behavioral biometrics, there are some challenges that must be overcome:
If a user is unaware that they are being tracked, it can be perceived as an invasion of their privacy. Some may find this to be an invasion of their right to privacy and refuse to use a system that employs behavioral biometrics. Traditional biometrics (fingerprints, face, iris) were already gaining so much privacy concern that western countries such as USA, EU didn’t implemented them at national level, like in Africa or Asia."Behavior Recognition" puts these concerns one-step further, where people are afraid of stricter society control through 7/24 continuous surveillance.
Users' behaviors can change over time. If the system does not track these changes and adapt to them, then it may lead to failure in the authentication process. This change can be the result of many factors including learning new habits, developing disease-related disorders, and physical disability.
Overall, although there are challenges to behavior recognition systems, the potential benefits are becoming more and more clear. As we've seen with the cases of authentication, behavior-based recognition systems can be a powerful tool that can help manage and control the world's growing population. As more research is done on this subject, more solutions are found to overcome the current challenges.
Behavioral biometrics is not a new science. It's been around since the early days of humankind. However, it did not gain popularity until now. The recent advancements in digital and smart technologies have opened many doors to this field. This has allowed behavioral biometrics and behavior recognition to be applied to many different areas in ways that were not possible before, from security to business to medicine, and more. Future is now, it's time for behavioral biometrics and behavior recognition to take the world by storm!
