22 Jul Top 6 Artificial Intelligence solutions for cybersecurity
AI (Artificial Intelligence) is rapidly transforming the cybersecurity industry while simultaneously rendering many of the existing methods obsolete. Historically, cybersecurity has been a resource-dependent effort. The duties cybersecurity specialists attend to are time-intensive, which can delay remediation and open a system to additional threats.
By automating the laborious processes involved in cybersecurity work, AI can transform the cyber workflow and allow for a streamlined process that maximizes protection. Many organizations are now beginning to see how crucial AI integration is to their cyber-security efforts, with nearly two-thirds of companies agreeing that AI will be integral in identifying system vulnerabilities and critical cyber threats.
Here are the top 6 AI solutions that will augment the cybersecurity efforts of organizations:
1. Automated threat detection
The best solution to a problem is always preventing the problem in the first place. This is precisely what AI can do for cybersecurity systems. The significance of the automated threat detection method is that algorithms will work around the clock, 24/7 to detect, identify, and inform security personnel about suspicious or anomalous network activity and hostile communications, reducing the time it takes to identify a threat.
2. Self–learning systems
Because of AI’s ability to learn, cybersecurity systems will become smarter the longer they’re active. With each failure, the system will be able to essentially learn from their mistakes and self-tune. As time goes, the system becomes more efficient and effective in its threat-detection.
3. Breach risk prediction
Self-learning systems can predict potential risks as well as existing threats. An AI system will be able to predict risks of breaching under a wide array of scenarios and prioritize risks. By prioritizing risks, cybersecurity professionals can effectively manage their time and focus on the most pressing concerns.
4. Incident response
After an attack, it’s important to know how the attack happened to defend against similar threats. AI can provide a detailed report on the attack so that cybersecurity professionals can know what’s happening behind the scenes and improve the current cybersecurity system. Using artificial intelligence to automate the incident response process makes it much easier to address more problems in less time and with less effort on the part of the team members.
5. Threat hunting
Threat hunting involves automated threat scanning which takes a proactive rather than reactive approach. This system is effective when it comes to 90% of known threats. However, AI can fill in the missing 10% gap by analyzing network traffic data and picking up on patterns that would evade most cybersecurity specialists’ trained eyes.
6. Network security
Although it might seem like a mundane concern, many attacks succeed due to rules and/or policies being distributed in an untimely manner. Through the use of an AI-driven policy, cybersecurity team can continuously strengthen the network against new threats and attacks produced by hackers.
The bottom line
Cybersecurity specialists must incorporate AI methods into their skill set and organizations should become familiar with the shifting security landscape. Automated Threat Detection, self-learning systems, breach risk prediction, threat hunting, and network security, are just a few of the methods being altered by AI.
The future of AI in cybersecurity will not be a purely automatic process, it will require human supervision and intervention. AI-Human hybrid systems will offer a balance of human ingenuity and common sense along with sophisticated pattern recognition that only AI can offer.
As cybersecurity solutions become integrated with AI, so will the means of attack. That’s why it’s integral that professionals keep up to date with the technology and organizations hire cybersecurity specialists equipped with the skills and knowledge to utilize and defend against imminent AI threats.
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