How liveness detection catches deepfakes and spoofing attacks

<p>Many security experts believe biometrics-based verification — for example, capturing users’ faces through their device cameras to confirm their identities — is critical for achieving strong cybersecurity in a user-friendly way.</p>
<div class=”ad-wrapper ad-embedded”>
<div id=”halfpage” class=”ad ad-hp”>
<script>GPT.display(‘halfpage’)</script>
</div>
<div id=”mu-1″ class=”ad ad-mu”>
<script>GPT.display(‘mu-1’)</script>
</div>
</div>
<p>However, fraudsters can now <a href=”https://www.techtarget.com/searchsecurity/tip/How-deepfakes-threaten-biometric-security-controls”>use generative AI technology to impersonate users</a> and access their private accounts, threatening the viability of <a href=”https://www.techtarget.com/searchsecurity/definition/biometrics”>biometric</a> systems. Defenders need tools and techniques to differentiate real humans from deepfake doppelgangers and other spoofing attempts.</p>
<p>One of the key techniques for spotting <a href=”https://www.techtarget.com/whatis/definition/deepfake”>deepfakes</a> is known as <i>liveness detection</i>: the use of an algorithm to verify that a live person is generating biometric data in real time. In addition to thwarting the use of AI-generated deepfakes for biometric authentication, liveness verification technology can also identify if an attacker is using prerecorded biometric data. Liveness detection complements <a href=”https://www.techtarget.com/searchsecurity/definition/authentication”>authentication</a> mechanisms, which are still responsible for determining whether the biometric data corresponds to a particular person, by making sure the identified person is authenticating now.</p>
<p>In this article, we look at how liveness detection — also known as <i>liveness tests </i>and <i>liveness checks</i> — can help cybersecurity practitioners to protect against fraud.</p>
<blockquote class=”main-article-pullquote”>
<div class=”main-article-pullquote-inner”>
<figure>
Defenders need tools and techniques to differentiate real humans from deepfake doppelgangers.
</figure>
<i class=”icon” data-icon=”z”></i>
</div>
</blockquote>
<section class=”section main-article-chapter” data-menu-title=”Types of liveness detection”>
<

[…]
Content was cut in order to protect the source.Please visit the source for the rest of the article.