AI is a growing movement with advances like IBM’s Watson and Hanson Robotic’s Sophia, and these supercomputers are starting to have a more human-like intelligence.
The future of AI is promising as it will impact big data and cybersecurity by bringing mechanical accuracy together with reasoning, self-correction, and learning through activities.
With the implementation of AI in cybersecurity, AI will be able to locate and flag threats. This will help increase the protection of information and data while decreasing response time to threat risks. With an advanced AI program that’s able to learn and adapt, AI-based cybersecurity will be able to implement timely plans to block both complex and simple security incidents.
AI based on neural nets, a way for AI to learn and adapt, can help identify new weaknesses and exploits in systems to help mitigate potential future attacks. AI systems that can mimic the decision-making abilities of a human will be able to provide similar amounts of security to databases and systems that already exist.
Traditional technologies of authentication depend on three methods for certification: biometric, password, or ID. However, in a big data environment where consumer habits and behavior are accessible to companies, it’s possible for AI to authenticate users according to behavior.
Using behavioral characteristics provided by big data would make it harder for forgery attempts while reducing the burden on users by reducing the number of complex passwords and login credentials, or even the use of an ID card.
Big data has its flaws and needs to be validated and compared to real data to determine the authenticity of the information. AI, however, can analyze the authenticity of the data to validate true data and eliminate false data.
It’s possible for AI to use big data to differentiate between fake or spam users and genuine communication. This can even include distinguishing which comment in a comment network is false or identifying incorrect data in a production system.
Learning with Natural Language Process (NLP)
AI-based systems can collect data by scanning articles, studies, and news about subjects like cyber threats or cybersecurity. Using NLP, the AI system is able to assimilate information and then determine value and meaning from it.
Not only can AI learn from its own interactions with data but also from experiences through text. This would further enhance AI’s speed and ability to progress and adapt to security threats.
Integration of AI in cyber security
AI that specializes in cybersecurity is able to protect and defend against potential cyberattacks, but only for the systems and databases it is integrated with. Sensitive information like your business records and client information needs to have the best protection possible.
What you need is an AI system that’s able to integrate with programs that help run your business, like eCommerce platforms and your CRM and ERP of choice, but can also custom integrate with the platforms built to protect that information. An integrated AI focused on cybersecurity would not only be able to protect customer information, but ensure the safety of the entire business.