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Implement Automated Threat Intelligence for Improved Incident Response | #cybercrime | #infosec








Implement Automated Threat Intelligence for Improved Incident Response

“Know thy enemy” is as relevant to cybersecurity as it has been to physical defenses throughout millennia. Unlike many conventional threats, though, cybercrime is always changing. While staying on top of these shifts can be tricky, automated threat intelligence makes it easier.



What is automated threat intelligence?


Threat intelligence is the process of identifying, classifying and studying cyber threats to protect against them more effectively. Once businesses know more about their attackers—including their motives, methods, abilities and targets—they can find better ways to stop them. Automated threat intelligence automates steps within that process.

 

Manual threat intelligence approaches are still the standard for many companies. However, they’re quickly becoming outdated. Researchers detected 40 never-before-seen vulnerabilities in 2022 alone. Manual methods can’t keep up with that, so automation is necessary.



How does automated threat intelligence work?


AI hasn’t yet reached the point of being able to automate the entire threat intelligence process. However, it can streamline many individual steps under that umbrella.

The simplest form is to automatically gather threat data into one place for easier analysis. Many systems also analyze this data, with some even factoring in real-time information. In some cases, these AI models may summarize findings and suggest responses to aid faster decision-making.

Some businesses use automated threat intelligence to detect and contain possible threats in real-time. These automatic response tools save $1.76 million on average in data breach costs by acting faster.



Benefits of automated threat intelligence


Across all these use cases, automated threat intelligence has several key advantages over manual methods. Here are three of the most significant.

Reduced cybersecurity workloads

One of automation’s biggest benefits is its ability to reduce workloads and stress on security teams. A growing talent gap makes it hard for cybersecurity workers to accomplish everything, and 93% of organizations today find manual malware analysis tedious and challenging.

 

Automated threat intelligence handles the most repetitive parts of the job so security pros can focus on other, more engaging work. These workers may perform better with less on their plates and will be able to accomplish more in less time.

Improved accuracy

Automated threat intelligence is also often more accurate than manual alternatives. AI is adept at spotting subtle patterns in vast amounts of data. That can be tricky for humans, especially when managing hundreds of data points on dozens of potential threats.

 

Automating this analysis also minimizes risks from human error. Over half of all cybersecurity professionals have made mistakes at work and unengaging, repetitive workflows make this oversight easier. That’s no longer an issue if error-prone humans don’t perform this work.

Higher efficiency

In addition to recognizing threat patterns more accurately, automation does it faster than humans can. Quicker analysis aside, automated threat intelligence can streamline processes by enabling real-time alerts, consolidating data and summarizing reports for faster understanding.

 

This speed produces crucial financial improvements. Shorter identification and containment timelines coincide with millions in savings from lower data breach costs.



Best practices for automating threat intelligence


As with any technology, businesses must follow best practices to achieve the benefits. That starts with determining the best way to automate threat intelligence workflows. There are multiple types of malware analysis tools available today, and organizations can automate other processes as well, such as data aggregation or detection and response.

 

Businesses can determine the best automation strategy by finding their current weakest link. Workflow audits can reveal which steps take the most time or produce the most errors. These mistakes suggest ideal use cases for automated threat intelligence.

 

In cases where organizations must train their own threat intelligence AI, they must pay close attention to training data sets. These data sets must be large enough to provide a statistically significant baseline but relevant to the specific use case to right-size the model and boost accuracy.

 

Similarly, businesses must secure their training data sets from poisoning attacks. Attackers can reduce AI accuracy to 75% by making just 8% of its data erroneous or misleading.

 

As impressive as automated threat intelligence is, human experts must always have the final say. Over-reliance on AI could lead to missed bias or overcorrection.



Businesses today need automated threat intelligence


While automated threat intelligence isn’t perfect, it’s a substantial improvement over entirely manual alternatives. Given how quickly cybercrime evolves today, businesses cannot afford to overlook that potential. Recognizing these benefits and learning how to act on them is the first step to modernizing an organization’s defenses.



About The Author


Zac Amos is the features editor at ReHack, where he covers trending tech news in cybersecurity and artificial intelligence. For more of his work, follow him on Twitter or LinkedIn.



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