ADVANTAGES OF AI IN CYBER SECURITY

AI can be used to spot cyber threats and possibly malicious activities. Traditional software systems simply cannot keep pace with the sheer number of new malware created every week, so this is an area AI can really help with.

By using sophisticated algorithms, AI systems are being trained to detect malware, run pattern recognition, and detect even the minutest behaviors of malware or ransomware attacks before it enters the system.

AI allows for superior predictive intelligence with natural language processing which curates data on its own by scraping through articles, news, and studies on cyber threats.

This can give intelligence of new anomalies, cyberattacks, and prevention strategies. After all, cybercriminals follow trends too so what’s popular with them changes constantly.

AI-based cybersecurity systems can provide the latest knowledge of global as well as industry-specific dangers to better formulate vital prioritization decisions based not merely on what could be used to attack your systems but based on what is most likely to be used to attack your systems.

Bots make up a huge chunk of internet traffic today, and they can be dangerous. From account takeovers with stolen credentials to bogus account creation and data fraud, bots can be a real menace.

You can’t tackle automated threats with manual responses alone. AI and machine learning help build a thorough understanding of website traffic and distinguish between good bots (like search engine crawlers), bad bots, and humans.

AI enables us to analyze a vast amount of data and allows cybersecurity teams to adapt their strategy to a continually altering landscape.

“By looking at behavioral patterns, businesses will get answers to the questions ‘what does an average user journey look like’ and ‘what does a risky unusual journey look like’. From here, we can unpick the intent of their website traffic, getting and staying ahead of the bad bots,” explains Mark Greenwood, Chief Technical Architect & Head of Data Science at Netacea.

AI systems help determine the IT asset inventory which is an accurate and detailed record of all devices, users, and applications with different levels of access to various systems.

Now, considering the asset inventory and threat exposure (as discussed above), AI-based systems can predict how and where you are most likely to be compromised so that you can plan and allocate resources towards areas of most vulnerabilities.

Prescriptive insights from AI-based analysis enables you to configure and improve controls and processes to reinforce your cyber resilience.

The number of devices used for working remotely is fast increasing, and AI has a crucial role to play in securing all those endpoints.

Sure, antivirus solutions and VPNs can help against remote malware and ransomware attacks, but they often work based on signatures. This means that in order to stay protected against the latest threats, it becomes necessary to keep up with signature definitions.

This can be a concern if virus definitions lag behind, either because of a failure to update the antivirus solution or a lack of awareness from the software vendor. So if a new type of malware attack occurs, signature protection may not be able to protect against it.

“AI-driven endpoint protection takes a different tack, by establishing a baseline of behavior for the endpoint through a repeated training process. If something out of the ordinary occurs, AI can flag it and take action — whether that’s sending a notification to a technician or even reverting to a safe state after a ransomware attack. This provides proactive protection against threats, rather than waiting for signature updates,” explains Tim Brown, VP of Security Architecture at SolarWinds.