The implementation of Artificial Intelligence (A.I.) has quickly become an industry standard across cybersecurity efforts. However, how we understand A.I. and it’s functionality often gets exaggerated. This technology has very practical implementations that can bolster security efforts and help create resilient digital environments.
How Real is the Risk of a Data Breach?
This seems like a simple question, but is actually quite complicated when thinking about the overall changes of digital transformation. Taking steps in a transformation journey means that as a business, you are creating a digital environment with dedicated pathways to connect your business to the internet. As this system becomes more complex, as more pathways are created and more users fill out the network, the risk of data breach grows.
Ultimately, cyberattacks are conducted by people who see personal information as currency, and in the case of a successful breach, personal credentials are often literally sold to the highest bidder. As company databases grow bigger, hackers see more opportunity. Consequently as digital environments have grown, the rate of cybercrime has risen as well.
However, digital environments also offer more tools for companies to protect their employees and their data in the event of a successful attack. More often than not, cloud recovery offers one of the best remediation strategies and proper end user identity authentication measures can thwart breaches before they begin.
The risk of a breach is very real, companies must prioritize their security measures and should consider this a vital portion of their overall digital transformation efforts.
How are Hackers using AI?
The reality of today’s threat landscape is that hackers often have access to many of the same tools that our security personnel have and likely they have both received similar training at some point. This means that even as security personnel are implementing AI applications to bolster company defenses, cybercriminals are adding AI tools to their arsenal as well.
To this end, AI’s most important functionality is in how it enables the rapid processing of large volumes of data. Hackers are vigilant in their search for points of entry in company firewalls, and AI tools enable them to rapidly scan all company resources visible on the internet and determine a plan of attack.
This becomes even more concerning when considering how hackers leverage social engineering as part of their strategy. Bad actors commonly generate profiles on employees, pulling any exposed personal details visible online (social media, job boards, websites, etc.) in order to break authentication protocols. Where this may have taken a user quite some time in the past, AI can pull exposed credentials quickly and en masse.
What are Common Applications of AI in Cybersecurity?
On the other hand, companies can use AI to implement better protections and improve the resilience of their security protocols. Security personnel are forced to imagine how hackers will behave from behind the company’s firewall. AI represents another tool in the arsenal to help human operators consider the importance and priority of existing threats.
Enhanced Threat Intelligence
While AI can enable stronger threat detection, it cannot determine threat priority on its own. Creating threat intelligence requires oversight of several different processes and building AI tools to facilitate and manage information and create visibility for several different data sources is a challenge in its own right. However, by combining different sources of data analysts can get a stronger understanding of hacker behavior then to classify level of risk and determine next steps.
Increasingly, hacking attacks are focused on applications as they often have different security requirements from the main system. AI can be used to test security protocols in real-time and determine what vulnerabilities need to be closed before the application is deployed in the business environment.
Examples of AI Enabled Security Automations
The shift to remote work has caused an increased cybersecurity cost with a higher amount of vulnerable endpoints. As a company’s digital environment expands, the volume of data that a security team must consider expands.
Consequently, AI applications can enable security personnel to automate a variety of tasks that would involve the analysis of large bodies of data and create reliable means of monitoring expanded digital networks.
Here are a few examples:
- Malware detection: Malware and Ransomware remains one of the most common forms of cyberattacks. On average it can take companies up to 300 days to discover that a data breach has occurred. This number will vary depending on what security protocols are already in place, and AI-powered malware detection can drastically reduce the length of time it takes to detect and respond to a breach, which in turn reduces the costs related with recovery and remediation.
- Code Vulnerabilities Analysis: Leveraging machine learning capabilities, AI can be trained to recognize vulnerable code structures. This offers the potential to automate the task of scanning the vast amounts of code that comprise a digital environment to identify vulnerable code.
- Fraud detection: Similarly, AI can be trained to flag fraudulent transactions, authentications, or activity in real-time, giving security personnel immediate notifications of suspicious actions. This technique is also known as anomaly detection and serves as one of the best use cases for AI, as the manual review of event logs is nearly an impossibility for human operators.
What AI Can’t Do
While we are moving away from the perception that AI bots will formally replace human operators, we still tend to exaggerate the capabilities AI presents. This technology is at its best when it is deployed to support us in our daily activities. The work of understanding and managing vulnerabilities will continue be a task that requires human oversight.
Likewise, AI will not replace hackers. Cybercriminals are human as well, and trained security professionals can recognize criminal behavior and take action must faster than an AI system can. This technology is another tool in the kit to enable to a security team to do their work more efficiently.
To learn more about this topic, listen to our Steftalks Podcast episode with Natal Da Silva, Stefanini Rafael CEO. Discover how to start embedding AI into your security processes and create a secure digital environment.
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