The rise of artificial intelligence (AI), large-scale language models (LLM), and IoT solutions has created a new security landscape. From AI tools that can generate Taught to write malicious code Enterprise IT teams find themselves constantly scrambling to keep up as attackers exploit connected devices as a means to move across networks. According to the Google Cloud Cybersecurity Forecast 2024 report, enterprises should expect a sharp increase in attacks leveraging generative AI tools and LLM technologies as they become more widely available.
The result is a harsh reality for network guardians. It's impossible to keep up the pace. While attackers benefit from a decentralized approach to exploiting everything they can to compromise business networks, businesses are better off remaining strictly secure. This creates an imbalance. Even as malicious attackers push the limits, defenders must swerve.
But it's not all bad news. A back-to-basics approach allows businesses to reduce risk, reduce impact, and develop improved threat intelligence. Here's how:
What's new becomes old again
Attack vectors are evolving. For example, her connected IoT environment creates new entry points for malicious attackers. If an attacker could get into one of her devices, they could potentially gain unfettered network access. Meanwhile, as ZDNET pointed out, LLM is currently being used to improve phishing campaigns by removing grammatical errors and adding cultural context, while generative AI solutions are being used by business users to Create legitimate-looking content, such as invoices and email instructions, with a call to action.
This makes it easy for companies to lose sight of the forest for the trees. Legitimate concerns about growing AI threats and expanding IoT risks can create a kind of hyperfocus on security teams, leaving networks unintentionally vulnerable.
There may be more attack paths, but these paths ultimately lead to the same location: the enterprise application, the network, and the database.consider We have predicted some cybersecurity trends for 2024. This includes AI-generated phishing emails, “doppelganger” users, and convincing deepfakes.
Despite the differences in approach, these new attacks still have familiar targets. As a result, businesses are best served by going back to basics.
focus on what's important
Value to an attacker comes from stealing information, compromising operations, or holding data hostage.
This creates a funnel effect. At the top are attack vectors, which include everything from AI to scam calls, vulnerability exploits, and macro malware. As the attack moves toward the network, the funnel begins to narrow. Multiple compromise vectors exist, including public clouds, user devices, and internet-connected applications, but these vectors are far fewer than their corresponding attack vectors.
At the bottom of the funnel is your protected data. This data may reside in on-site or off-site storage databases, public clouds, or within applications, but still represents a reduction in the overall attack funnel. As a result, businesses no longer need to thoroughly respond to every new attack. Instead, security teams must focus on the common end goal of disparate attack vectors: data.
Effectively addressing new attack vectors means prioritizing familiar operations such as identifying critical data, tracking indicators of attack (IoA), and implementing a zero trust model.
Accelerate your security defenses with AI
back to basics
Consider a company under threat from AI-assisted attacks. The hacker used generation tools and his LLM to create hard-to-discover code designed to target specific datasets. At first glance, this scenario may seem overwhelming. How can businesses combat unpredictable threats?
Simple: Start with the basics.
First, identify important data. Given the vast amount of information being generated and collected by businesses today, it is impossible to protect all data at the same time. By identifying critical digital assets such as financial, intellectual property, and human resources data, businesses can focus their protection efforts.
Next up is tracking IoA. By implementing processes that help pinpoint the characteristics of common attacks, your team will be better prepared to respond when threats emerge. Common IoA may include a sudden increase in certain data access requests, unexplained performance issues in widely used applications, or an increase in the number of failed login attempts. Armed with this information, teams can better predict likely attack vectors.
Finally, the Zero Trust model helps provide a bulwark of protection in the event that an attacker compromises your login and password data. By adopting an always-on verification approach that uses behavioral and geographic data in combination with a strong authentication process, enterprises frustrate attackers at the final hurdle.
Function over form: Implementing new tools
Enterprises can reduce security risks while focusing on outcomes rather than new attack vector inputs. However, there are also cases where new tools such as AI and LLM are being introduced to enhance cybersecurity efforts.
Consider generative AI tools. In the same way that GenAI can help attackers write code that is difficult to detect and counter, it can help cybersecurity teams analyze and identify common attack patterns and help businesses identify possible breaches. Helps focus on certain pathways. However, keep in mind that this identification will not be effective if your company does not have endpoint visibility to understand where attacks are coming from and which systems are at risk.
In other words, introducing new tools is not a panacea and is only effective when combined with solid security hygiene.
To improve your security, work smarter, not harder
Just as attackers leverage new technologies to increase the effectiveness of breaches, businesses can also leverage AI security to defend against potential threats.
However, malicious actors may act with impunity. If AI-enhanced malware or LLM-reviewed phishing emails don't work, you're just back to square one. But for cybersecurity professionals, failure often means compromised systems, and at worst, data theft and ransom demands.
result? Security success is about working smarter, not harder. This starts with going back to basics: identifying critical data, tracking attacks, and implementing tools to validate all users. Improved through targeted use of AI. Leveraging solutions such as IBM Security QRadar Suite with advanced AI threat intelligence and IBM Security Guardian with built-in AI outlier detection, businesses can combat current threats and reduce the risk of future breaches. You can prepare for it.
