Machine 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.

French Government to Roll Out Digital ID Authentication With IDEMIA, Fintech News Swizterland

Machine Learning and AI Can Detect Malicious Activity

Machine learning and AI can learn normal human behaviour and will detect any variations from the norm. This is different from the use of traditional rules-based systems as it can detect new forms of attack. Machine learning algorithms are able to spot attacks within seconds and mitigate the damage. This way, customers don’t need to worry about losing sensitive data, and the organization can continue operating as usual.

Machine Learning and AI Can Automate Repetitive Security Tasks

Machine learning can free up human resources and company funds as it can automate certain security tasks. Any repetitive task can be handled by these systems. This means the security staff of the company can focus on more complicated cyber security tasks and problem-solving. Machine learning technology can collect data and understand certain patterns, and it will alert you whenever an actual problem is detected. Some repetitive tasks that can be handled by AI systems include looking up IP addresses, collecting URL intel, investigating domains, and retrieving logs. AI can perform these tasks and provide data enrichment and threat scores. Malware investigation tasks can also be handled by AI, and the common repetitive tasks here include extracting data and performing VM snapshots.

Conclusion

Machine learning and artificial intelligence can be extremely useful in protecting customer information, and they can also keep the company’s data safe. These systems are used to verify customers’ identities, and this is done using facial recognition and similar methods. Machine learning technology can also detect unusual behaviour on the network and raise the alarm. Another benefit of this technology is that it can help to automate repetitive tasks, meaning the cyber security staff will be able to focus on other useful tasks.

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