If you’ve been following tech news lately, you’ll know that cybersecurity experts are sound the alarm on the increasing use of AI to design and deploy sophisticated cyberattacksIn fact, thanks to AI, the barrier to becoming a hacker is much lower Now, as this technology helps to refine social engineering, PhishingAnd network penetration efforts.
Unfortunately, cyber security Professionals have not embraced the AI trend as quickly as malicious actors. Although several new graduates are entering the sector, 84 percent professionals have little or no AI And ML knowledge. As a result, workers in the sector are facing a wave of new cyberattacks that they are ill-equipped to deal with. As if that weren’t enough, even U.S. government agencies like the FBI warn individuals and businesses of the rise of AI-powered cyberattacks.
As serious as the problem is, it’s never too late to get aware and take action. Business leaders are usually left to their own devices, but closing the AI skills gap is a problem they can confidently tackle alongside their CTOs with a few practical tools.
Let’s explore how cybersecurity leaders can prepare engineers to manage and mitigate AI threats and successfully implement the technology into their operations.
3 Ways to Prepare for AI-Based Cyber Threats
- Building a culture of continuous learning around AI.
- AI-based red team simulations.
- Safety verification and evaluation of AI tools.
Training to integrate the unique capabilities of AI
It’s no wonder that today’s engineers aren’t yet accustomed to tackling AI head-on. While the technology isn’t new, it has evolved rapidly over the past couple of years. So, those who completed their education before or during this time probably didn’t have a curriculum that addressed AI. But how did hackers manage to implement it so quickly?
The answer might just be tinkering and a collaborative approach to learning. recent study confirms this, revealing that Cultivating a culture of learning Increasing the number of engineers and software developers can potentially reduce the threat of AI skills. Industry professionals should not be left alone to acquire these skills; CTOs and business leaders should facilitate upskilling opportunities for their staff to get ahead in the AI space. This way, they can improve their own AI cybersecurity or do so for customers (if they are vendors) with the most skilled workforce.
Although staff can use AI Chatbots To answer questions and code to solve them, the real challenge is to improve productivity, make systems foolproof against AI cyberattacks, and integrate AI capabilities into existing processes and environments. These high-level skills require more than a few Google searches, so investing in specialized AI training programs can be very valuable for today’s cybersecurity companies.
To prepare their workforce accordingly, companies can hire AI experts to teach task-specific courses or simply look for online courses that certify their engineers in the latest AI skills. These learning programs can be as rigorous as you want them to be, from Udemy online courses to Harvard online courses. It’s up to you to decide how and in what areas of expertise you want to equip your employees.
If you already know industry experts, the best place to start is to reach out to them so they can share their knowledge of AI cybersecurity basics with your team via a call or quick presentation. Otherwise, it’s best to take a bottom-up approach: browse online courses that cover the basics and look for prices and durations that fit your budget and workload. Then, move on to more rigorous courses based on your security team’s response and your priorities. The possibilities are endless when it comes to learning in this ever-evolving topic.
Launching AI attacks to improve threat identification
The journey doesn’t end with upskilling your workforce. Like any technology, AI is a constantly evolving tool, and hackers are always looking for ways to modernize their techniques using it. So the learning shouldn’t stop.
A great way to continue is to run simulated red team attack scenarios with a twist. Nearly two-thirds organizations are already adopting this practice to strengthen their cybersecurity posture. However, as new threats emerge, red team must take a new form.
Typically, red teaming involves a group of engineers attacking their own systems to find vulnerabilities and fix them. Now, AI must lead the attack, so employees learn to think like AI and build resilient systems against it. The race between defenders and attackers has become more intense, with attackers generally more adept at exploiting new technologies. As a result, they end up outpacing engineers by quickly designing and executing innovative attacks, especially when implementing AI.
Cybersecurity experts are already using this technology to recreate red teaming activities, mimicking how hackers would use AI to break into their systems. This approach can help teams better understand how AI works, anticipate potential threats, and discover new ways to defend against attacks that traditional methods might overlook.
As AI becomes an integral part of cybersecurity offerings, it is critical to secure its implementation against potential vulnerabilities from all sides, including security attacks. Security teams can achieve this by adopting offensive tactics such as vulnerability discovery, so that their newly integrated AI tools have no exposed attack surface to exploit. This way, organizations are better prepared to protect their AI systems against these increasingly sophisticated attacks.
Assessments for proper AI verification
Whether your cybersecurity team is already developing and implementing AI capabilities or looking for vendors to do so, it’s critical to vet the security of these new tools in your arsenal. This is especially important now that the National Institute of Standards and Technology (NIST) has highlighted latent vulnerabilities Cyber risks related to AI Companies must protect their systems against.
One such risk is exposure to untrusted data or data poisoning, which hackers use to penetrate AI systems, causing them to malfunction and weakening an organization’s entire infrastructure.
As AI introduces these new complexities, Engineers must improve their internal security. A great way to do this is to integrate security assessments into the development process of every new feature or product that uses AI. This allows cybersecurity teams to be proactive in securing their infrastructure and be aware of interactions with AI from the start, fostering a culture of security-first thinking.
Many services already offer such assessments so that engineers can follow guides and learn how to run security tests tailored to their organization’s needs. For example, OWASP offers a free test AI Security and Privacy Guide to train cybersecurity teams on what to look for when reviewing AI systems – a good starting point for employees to become familiar with innovative security practices.
Hackers Are Getting Smarter – So Should You Be Too
Cybersecurity professionals are tasked with protecting an increasingly vulnerable digital world. AI has proven that malicious actors move as quickly as available technology evolves. This means engineers must move even faster to address new threats. Industry leaders must ensure their employees are ready to take on this daunting challenge. Upskilling, AI red teaming simulations, and security assessments are the best approaches to properly train them for the new landscape.
