How AI & ML are enhancing User Authentication technology?
Who doesn’t know about user authentication technologies? They have become part of our daily lives. They are so common that common people don’t usually feel amused by user authentication technology anymore. Now user authentication systems have become our need and the only time a user authentication system attracts our attention is when it uses a new enabling technology that wasn’t seen before.
Your smartphone lock, laptop password, the key to the home door lock, password to your social media accounts, fingerprint authentication to access your devices, RFID cards to enter your office, etc. are all the end applications of user authentication technologies playing their role to make sure it is you who access the resource.
But as user authentication is becoming an integral part of our lives, the technology is not safe from predators who are trying to steal your data, resource, and ownership. The success of a company now depends on how good its user authentication technologies are? That’s why a lot of research is going into the various authentication technologies and verifying the right owner.
This article covers the various prominent user authentication systems and futuristic user authentication systems.
The user authentication systems primarily can be divided into two types:
- Non-Smart User Authentication
- Smart User Authentication
Non-Smart User Authentication
Non-smart user authentication systems are unable to improvise on their own. They don’t make decisions and don’t use machine learning to identify “if the authentication attempt is a suspicious event”.
The prominent non-smart user authentication systems are mechanical systems where the user needs to input some identity to access the resource. These are usually suited for protecting resources of low value. The cost of such authentication systems varies from a few dollars to a few thousand dollars.
Lock & keys, User ID & Passwords, RFID & NFC tags, 3D QR codes, Fingerprint & biometric sensors, etc. are prominent non-smart user authentication systems.
A non-smart user authentication system stores the password, biometric pattern, other physical patterns, and frequency as an authentication command, and whenever it receives the same command, it grants access to the resource. It doesn’t care if that authentication command is given by the same owner or someone else.
Even the high-cost retina and heartbeat scanners are non-smart systems and can be fooled.
Smart User Authentication
Since there is a lot of emphasis on privacy and protecting critical resources. The demand for smart authentication technologies is rising. These authentication systems detect a lot of things before granting access to the resource. Even after granting the access, they continue recording the data to verify if the user is authentic or not.
Since the authentication here is not one-time activity but a continuous monitoring process, they rely on sensors to record data and processors to process the data. There are dedicated machine learning, neural network, and AI modules that keep working in the background to make sure the user is the same.
AI & ML is the living force for these systems.
With minor updates, the existing systems are upgraded to smart user authentication systems and they don’t cost a fortune. But they result in privacy and protection of the resource.
User ID & Password
The existing password systems only cared about the input value. The new smart systems continuously monitor the resource and decide if the user is authentic.
E.g. Earlier if you would want to log in to your device and/ or social media account from a new location, it would grant you access if the password and user ID match the stored values. But now, the devices use location sensors and once the identified location is new, the system prompts you to use a second authentication password or identifier to enhance your privacy.
User Profiling
User profiling is the soul of smart user authentication systems. Each person is unique and they uniquely live life. Your walking style, talking style, breathing pattern, biological footprints, biometrics, etc. are all unique.
On top of that, the way a user experiences a product is also unique and varies from one person to another person.
The technology firms are using it to profile you. They create systems that understand you beneath your physical existence. The device keeps on recording:
- How much time do you spend on various activities? Your likes & dislikes?
- How do you react to various icons?
- How do you breathe? Where do you look? How do you hold the device?
- How do you type? Your speed? Your choice of words? Your favorite emojis?
Every minute detail about you is noted by the device and a user profile is created. This profile contains your likes, dislikes, and your way of interacting with the device and with various apps. It contains how much time you spend on various components, programs, etc.
The smart systems keep on recording and updating your profile. The more you use the device and the more you interact in the ecosystem of the software developer, the more they record and understand you. After a time, the device knows a lot about you and whenever it spots a new pattern of usage, it asks for re-authentication.
The use of AI & ML comes in making decisions and correlating the newly recorded data with the existing data. Various algorithms are used to detect the anomalies in the data and verify if the user is authentic or not.
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