Cybersecurity

How Can Artificial Intelligence and Machine Learning Boost Cyber Security?

achine learning is the use of data and algorithms to allow machines to imitate human behaviour. This technology is applied in many different ways. One of these is in the boosting of cyber security, an issue that has become quite sensitive over the past few years. Cyber security can lead to the complete failure of an organization, especially if crucial data is lost to the competition. Customers are also likely to abandon a company if it develops a reputation for poor cyber security. So, how exactly can companies use machine learning to boost customer security? Let’s find out.

Using AI-Powered Identity Verification

Automated ID verification “Automated identity proofing” is becoming quite common. One such verification system is known as Autoldent. This is an AI-powered identity verification system that features high levels of fraud detection. The system was developed by top identity and fraud specialists, and it can quickly identify specific users of your platform.

Typically, AI-powered identity verification systems like IDEMIA use biometric data of the customer’s face to determine their identity and personal details. It may also use facial expressions and gestures to determine the authenticity of the customer. This makes it extremely difficult for strangers to access customer accounts. Another method used to verify customer data is the use of ID Card scans. In this case, the programs will check for some badge-specific security features, and this will be used to extract personal and biometric data.

Read more

https://veille-cyber.com/three-key-pillars-of-smart-identity/

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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