4 Benefits of Using AI For Cyber Security

Updated: Sep 20


While cyberattacks continue to grow in volume and sophistication and skilled cyber security experts are in critically short supply, organizations are under huge pressure to find new technologies that can help mitigate the cyber risk.


Here comes AI to the scenery, AI is the result of the integration of several technologies leading to the creation of intelligent hardware and software, capable of replicating human behavior in learning and problem-solving. AI can help in cyber risk mitigation, it can learn from security analysts and improve its performance over time, leading to time-saving and better decisions.

Is AI needed in Cyber Security?

Like all other industry sectors, AI is becoming a game changer in cyber security not only in defense but in crime as well. Now, Cybersecurity solutions require to be much more intelligent because of the danger of the rise of AI-powered cyberattacks, which could enable cybercriminals to fly under the radar of traditional defense methods.

Importance of AI in cyber security

AI-based security solutions can identify, and prioritize risks, instantly spot any malware on a network, guide incident response, and detect intrusions before they start. This will help identify the organization’s weak points and act proactively to leave no tolerance for AI-powered cyberattacks. Building efficient defensive AI solutions need to be an ongoing process that always learns from previous experience, and global threat attacks to increase performance over time and be able to detect the patterns of any abnormal behavior that might emerge in the future. Here are some of the cyber security applications that use Artificial intelligence:

1. Vulnerability management solutions


We have already seen that organizations started to adopt a wide range of AI-based security solutions.

AI-based vulnerability management solutions now provide more accurate results through the elimination of false positives. It also can rank vulnerabilities based on the severity and criticality of the asset being affected. They can help provide corrective recommended actions to be done.

2. Threat Intelligence


The next generation of threat intelligence tools capitalizes on artificial intelligence's different techniques and algorithms to increase their capabilities. Advancements in research in machine learning, deep learning, and natural language processing and the availability of GPUs "Graphical processing units" allowed for handling large volumes of threat data that is constantly changing and increasing.

Machine Learning and Natural Language Processing techniques are improving threat intelligence and threat hunting capabilities either through coping with a huge amount of unstructured data or extracting useful insights from the data. AI-based TI tools now can provide more insightful analytics on trending attacks, anomalies, vulnerabilities, and prevention strategies.

3. Offensive Security Simulation

Using AI in offensive security and attack simulation started to gain attraction recently. Ai is used now to automate penetration testing and red teaming activities. CART “continuous automated red teaming” is now an emerging technology that automates red teaming activities to achieve the breadth and depth of the process as well as scale it and seamlessly conducts it on a continuous basis.

The process of CART includes an automatic search of dark and surface web to discover attack surfaces including unknown exposed databases, cloud buckets, code leaks, exposed credentials, risky cloud assets, and open ports. Once the attack surface is recognized, the attack engine launches multistage attacks to identify security blind spots and attack paths before hackers do. The platform then prioritizes the risks and recommends the next steps for mitigation.

AI is being used at multiple stages in this process, first at the discovery phase of the attack surface and then at the vulnerability's verification, prioritization, and finally recommendation of best actions.

4. Data Classification


Data security and protection are becoming the top priority of any organization now. A proper data protection strategy always starts with the right data classification solution. AI now enables automatic data classification with a very low false positive rate unlike traditional rule-based methods; we can now teach the machines through ML/DL how to classify the different documents into the public, confidential, critical, or any other category specific to each industry.


Data classification solutions also support categories based on data privacy regulations like GDPR and HIPA. Once data is classified in the right categories, it is much easier to control and protect it. And then comes the rule of the other solutions like encryption, DLP, and backup.

Conclusion

The journey of AI-powered cybersecurity has just started, with the advances in AI research every day and the availability of huge pools of data, we are moving towards AI solutions that can exhibit human-level curiosity, persuasion, and explainability. This will make cyberattacks more and more sophisticated.

So, it is time for organizations to start adapting defensive AI solutions to be able to keep up with the drastic changes and emerging attacks.

For more information on the benefits of AI in Cyber security, please contact us and one of our experts will be glad to assist you.

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