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Artificial Intelligence – Revolutionizing the Biometrics

Artificial Intelligence - Revolutionizing the Biometrics

By: Arpita Soni

In today’s digital era, a collaboration of Artificial Intelligence (AI) and Biometrics has emerged as innovative and groundbreaking powers that have changed the paradigm of identity verification. Artificial Intelligence (AI) has started a new era of technological revolution that impacts numerous sectors.                                                                                                                   

Influencing everything from securing important buildings to smartphone access or unlocking smartphones to storing sensitive data, Biometrics has evolved as a strong leader in authentication and security, thus providing techniques and sophisticated approaches to identifying individuals based on their unique biological characteristics. 

What is Biometrics

Biometrics are physical characteristics or biological measurements — that could be used to identify individuals. For example, retina scans, facial recognition, behavioral recognition, and fingerprint mapping are all diverse types of Biometrics. These are the few commonly used biometric methods, though there exist more. Passwords are not enough to secure identity, and there have been numerous incidents of stolen password credentials, which amounted to 60% of all company data breaches last year.

How is AI enhancing different types of Biometrics?

  • Fingerprints. This is one of the commonly used and old forms of Biometrics. It measures your unique finger ridges to identify an individual. Machine learning techniques such as Artificial Neural Networks (ANN), Deep Neural Networks (DNN), Support Vector Machine (SVM) and Genetic Algorithms (GA) are commonly used techniques for fingerprints.

Convolutional neural networks (CNN) in deep learning have made a huge success in pattern recognition and make a good choice for fingerprint recognition.

  • Facial Recognition – Facial Recognition is a type of Biometric identification that uses a face analyzer feature in order to identify a person’s face. Once the application identifies a human interaction through the camera lens, CAPTCHA testing is no longer unnecessary.

Deep Learning and Machine Learning are very popular for face analysis.

  • Voice Recognition – Speech recognition is a capability in which human speech is converted to text using programs. AI and machine learning methods like deep learning, natural language processing and neural networks are common in advanced speech recognition. Some examples include but are not restricted to searching for items or tickets or sending emails or placing an order, among others. Google, Alexa, Siri, and more.
  • AI in voice commands, also known as Voice Command Recognition or Voice User Interface (VUI), refers to the integration of artificial intelligence (AI) technologies into systems that allow users to interact with devices using spoken language.
  • Lip Movement – Automatic lip reading (ALR) technology, which accurately translates real-time speech into understandable text by analyzing video content, serves as a valuable assistive tool for hearing-impaired users.
  • Emotion Recognition – Emotion recognition, also referred to as Affective Computing or Emotion Intelligence Computing, utilizes facial expressions, body language, or voice tone to discern a user’s emotional state. AI continuously analyzes the face expressions, minute movements of face muscle and creates the profile.

Transforming Various Sectors of Industry 

  • Healthcare
    • In healthcare, AI contributes to the accurate recognition of patient identity, enhances the security of health data, and is efficient in reducing medical errors.
  • Protection of Data
    • Data protection is critical for any technological advancement. AI systems play a key role in data protection, especially protecting and storing sensitive information with biometric access control systems.
  • Banking and Finance
    • Anti-money laundering and fraud detection are key challenges in banking and financial institutes. AL and ML techniques are gaining momentum in identifying the patterns and identifying fraudulent activities. They highlight the spot fraudulent transactions and hence help in protecting users from identity theft and financial losses.
  • Border Security
    • Border control and immigration have been accelerated by using AI-powered biometric methods for identity verification through facial recognition and fingerprint scans, thereby improving security and efficiency.

Challenges in AI-Powered Biometrics

While AI is assisting in improving the performance of biometric identification, unethical or irresponsible people misuse the technology to hack into the biometric systems.

A few examples are:

  • Fake Digital Fingerprints that can bypass the locks on the phone. They are called “Deep Master Prints.”
  • Similarly, for Face recognition biometrics, a criminal can use a 3D-printed mask to bypass the original face analyzer.
  • Attackers can also contaminate AI models by introducing malicious files that AI training has labeled as safe.  

The Future of AI-Powered Biometrics

The future definitely looks promising with AI and Machine learning. With new advancement in technologies, techniques and tools it will lay a big impact on the day-to-day lives of all. With commitment of enhanced security measures, effectiveness and convenience technology will definitely improvise the security issues in Biometrics. It should be taken with extreme care that evolution should not compromise personal privacy and freedom.

With the dream of the future becoming a reality, everyone needs to be responsible and go hand in hand, end-users and technologists, to welcome the AI biometrics revolution with awareness, education, and commitment to responsible AI for a more secure future.

Author Profile

Arpita Soni has been instrumental in Transformation and Automation and emerged as a Subject Matter Expert using new and emerging technologies like Artificial Intelligence [AI], Machine Learning [ML], and Deep Learning [DL] in Information Technology. At the heart of their dedication to technical excellence, strategic foresight, and relentless pursuit of innovation is praiseworthy.

An esteemed mentor and thought leader, Arpita has authored pivotal publications that serve as key resources for professionals and enthusiasts alike. 

Arpita’s membership in prestigious bodies like IEEE depicts her professional expertise and her active engagement in fostering a collaborative ecosystem for technological advancement. She has strategic leadership and a passion for mentorship. Arpita Soni stands as an outstanding figure driving the evolution of efficient and innovative digital solutions.


Published by: Khy Talara

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