Applications of AI in Cyber Security

Adding an additional layer of protection to existing enterprise security

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Next-Gen Antivirus

Artificial Intelligence techniques are playing an increasingly important role in antivirus detection. Heuristic techniques, data mining, agent techniques, artificial immune, and artificial neural networks are some of the AI techniques proposed to be applied in antivirus detection.

Vulnerability Management

The AI-based vulnerability management systems are proactive in detecting the vulnerabilities instead of waiting for the IT team to take the necessary actions on them. They can analyze the pattern and discover the loose ends that can be the potential vulnerability.

User and Entity Behavior Analytics

User and Entity Behavior Analytics or UEBA is a cybersecurity process that detects insider threats, targeted attacks, and financial fraud. AI in UEBA can enhance the pattern recognition abilities to find any anomalies. If any malware is introduced in the system, the working way would be changed, and that’s where the AI would detect the abnormality and report it to the authorities.

Improving Authentication

Most organizations and individuals still use the traditional methods of authentication of username/email and password. And the major drawback of a simple username-password is that most people use the same password for most of their accounts. And not a lot of those passwords are strong. AI can help detect weak passwords and suggest best practices to strengthen them.

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Drawbacks of AI in Cyber Security

While implementing AI in this field has its own advantages, there are a few hindrances.

The solution to the drawbacks

Knowing these limitations and drawbacks, it’s obvious that AI is a long way from becoming the only cybersecurity solution. The best way is to implement traditional techniques with AI systems.

Programmer | Tech Lead | Cybersecurity Enthusiast | Traveller.

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