Have you ever used your face to unlock your phone? Used a fingerprint scanner to get access to your gym? That's biometric data in action.
\ Biometric data comprises distinct measurable biological or behavioral traits unique to individuals, utilized for identification or authentication. In contrast to conventional forms like passwords, PINs, or ID cards, it relies on inherent physical or behavioral attributes. Examples of biometric data include fingerprints, facial features, iris patterns, voiceprints, and behavioral traits such as gait or typing patterns.
\ Biometric data is becoming increasingly important for both the enterprise and consumer in a variety of ways, from making it easier to confirm access to only authorized individuals gain access when entering physical locations or adding an extra layer of security to reduce the risk of unauthorized financial transactions.
\ Our healthcare system also uses biometric data to verify the identity of the patient, ensure alignment with the correct medical records, and ensure the appropriate treatment. Another example of how our society uses biometric data can be seen in law enforcement, where it plays an important role in criminal investigations for identifying and tracking individuals.
\ However, even though biometric data offers us convenience and ease of use, it also opens Pandora's box to a whole host of security and privacy risks.
Sensitivity & Risks of Handling Biometric DataAlthough biometric data elevates security and offers a sense of personalization, its sensitive nature demands the utmost protection. Unlike passwords, you can't simply reset your iris pattern or fingerprint if compromised. In a data breach, the permanent and immutable nature of biometric data makes it vulnerable to malicious misuse.
\ Moreover, being a form of unstructured data akin to emails and audio files, it is difficult to identify, classify, and/or categorize when stored, presenting both challenges and opportunities for IT and security teams to properly manage and protect this type of information.
\ Careful consideration must be given to security, privacy, and ethical concerns to ensure responsible, secure, and transparent use. Some of the challenges with using biometric data include: \n
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Want to know how you can better secure and protect highly sensitive biometric data from unwanted exposure? Here are six steps to get you there:
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Classify & Identify Sensitive Data With Context: After taking inventory of all of the sensitive data that your company stores, the next step is to classify and categorize challenging and elusive unstructured data, including biometric data.
\ Combine traditional pattern-matching techniques with advanced, ML and NLP-based classification to achieve unparalleled accuracy and scalability in data classification. Leaders need to build a complete and dynamic sensitive data inventory with contextual attributes for holistic understanding.
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