How is artificial Intelligence Impacting on Cybersecurity?

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artificial Intelligence Impacting on Cybersecurity

A big controversy is currently raging on whether Artificial Intelligence ( AI) is good or bad in terms of its effect on human life. As more and more businesses are using AI for their needs, it is time to test the potential implications of applying AI in cybersecurity.

Role of Artificial Intelligence in Cybersecurity

Artificial intelligence (AI) can be described as an artificial decision based on a specific algorithm and related mathematical calculations, which is the same as human decision making. On the other hand, cybersecurity is a step towards getting rid of the virtual world from cyber-attacks.

Identify Cyber Attacks

Traditional strategies fail to identify risks and malware with cyberattacks on both nature and scale. Cybercriminals are always creating new and smart ways to bypass restrictions on access, firewalls and highly secure networks. The only way to counter this attack is to get more training from hackers.

AI will help the security system to stay ahead of the current risk. Using AI, We will expand the scope of existing cybersecurity solutions and pave the way for new, powerful creation.

Simply put, the increasing complexity of threats to the network and security is beyond human control. We need a new, AI-driven approach to addressing today’s and tomorrow’s security challenges.

If an infiltration or suspicious activity is detected, the AI can make significant improvements to the security infrastructure by using millions of dollars to reduce criminal intelligence.

Future of AI in cybersecurity

Not surprisingly, cybersecurity is a priority for all organizations, especially when the world moves towards digitalization. AI consultants and top RPA vendors are keen to build innovative technologies to provide a framework for a deeper and stronger solid defense. Here are some ideas on how AI can improve cybersecurity with powered devices:

1. Application of AI devices to track security incidents
2. Combine machine learning to flag some abnormalities in the firewall.
3. Identify the causes of cyberattacks through NLP applications.
4. Use RPA bots to automate work and processes as per the rules.
5. Track and evaluate mobile cyber-threat endpoints

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