AI-Powered Cybersecurity Solutions With the Biggest Impact in K–12

Investing in a spectrum of technologies, IT professionals are serious about implementing cybersecurity solutions with AI. This interest in adopting AI-based tools comes on the heels of digital learning having intensified the need for cybersecurity protection.

“Almost every vendor in a school system today — around cybersecurity, network security, application security, endpoint security, MDR, you name it — every one of them is talking about AI. And they’re all bringing AI to school districts rather quickly,” says David Waugh, chief revenue officer at ManagedMethods.

“That type of technology is getting an overhaul in real time,” he adds.

Cybersecurity tools equipped with predictive analytics allow schools to classify and analyze the root cause of cybersecurity incidents, says Kapil Bakshi, distinguished systems engineer for the U.S. public sector at Cisco.

“We’re not just protecting networks and end users, we’re protecting AI models and services because we embed AI into our security solutions,” Bakshi says.

Here are some key areas in which IT leaders can implement AI-powered cybersecurity solutions in K–12 schools.

End-to-End Security Addresses AI Safety Concerns

Some solutions provide security for applications from development to deployment. These end-to-end solutions can put policies or constraints in place for AI, Bakshi explains. They also protect K–12 schools from AI safety issues such as hallucinations.

DISCOVER: Secure AI tools within your digital learning environment.

Bakshi notes the danger of AI-based applications with large language models providing toxic content to children. Solutions like Cisco AI Defense can address these safety concerns by providing guardrails for every AI application. The platform can detect shadow and sanctioned AI applications in public and private clouds, according to Cisco. Access control features prevent employees from using unsanctioned AI tools.

Cisco AI Defense also incorporates algorithmic AI red teaming, a “behind-the-scenes” security technique to test AI applications and models against multiple attack and threat categories, which identifies AI safety risks and provides guardrails around them, Bakshi says.

Managed Detection and Response Uses AI to Watch for Threats

MDR provides around-the-clock monitoring and threat detection and can investigate alerts.

Cisco offers extended detection and response to streamline tasks such as security event correlation, incident summarization and reporting. XDR can analyze data on security incidents and provide a summary for human analysts. AI can draft incident reports that serve as templates for generating reports on future incidents.

AI has also improved managed detection technology by allowing schools to pattern-match, which entails analyzing data sets using generative models to identify threats, says Waugh.

“MDR is becoming drastically enhanced by generative AI, chain-of-thought reasoning and LLMs, because AI can automate the review process that included traditional data loss prevention and detection and remediation rules,” Waugh says. “Even tech that’s come out within the past few years used different types of rules, whether it was regular expressions, keywords, pattern-matching signature or known-threat signatures.”

Email Security Is More Robust With AI Capabilities

AI can protect users from email phishing, scams and other types of social engineering. For example, ManagedMethods recently introduced an AI-powered phishing tool, a component of the company’s Cloud Monitor platform, which protects and monitors Google Workspace for Education and Microsoft 365 for Education.

The AI tool can protect school administrators from being impersonated.

“AI has become not only the protector with cybersecurity but also the villain, because the hackers are using it,” Waugh says. “Social engineering, behavioral analytics, deepfakes, malware synthesis — these are all being incorporated by AI into managed detection and response and endpoint protection.”

RELATED: These security solutions protect schools against phishing threats.

Chain-of-thought AI technology can improve a system’s judgment by leading it through step-by-step reasoning. “With the advancements of AI, our chain-of-thought reasoning models help detect more quickly whether this email is a threat to a recipient’s mailbox,” Waugh explains.

“We can spot unusual behaviors or patterns across accounts,” he continues. “For example, flagging a suspicious activity that might be difficult for a human to catch if they’re not trained to look at it shows whether there have been compromised credentials and helps identify lateral phishing activity.”

Phishing emails could appear to be coming from a legitimate person, but the return address could be an automated bot. “You see a lot of impersonation generated by AI,” Waugh says.

An international study by Sophos, The State of Ransomware in Education 2024, revealed that malicious emails were the second most common root cause of ransomware attacks in lower education.

Tools like Cisco Secure Email Threat Defense can help by processing and accurately classifying malicious business email compromise attacks, which the FBI calls “one of the most financially damaging online crimes.” The cloud-based Cisco Umbrella incorporates a DNS security layer to block phishing and malware threats, Bakshi says.

Endpoint Protection Defends Against Cyberthreats

Endpoint devices, including laptops, smartphones and tablets, are the “connection vehicle” for staff or students, Waugh says.

Endpoint protection solutions provide real-time monitoring of devices and networks, and now these technologies incorporate AI and machine learning. On a desktop, laptop or any kind of device a student or staff member might use, behavioral monitoring engines use ML to protect against malware and ransomware.

ML-based behavioral engines can look for malware or ransomware threats, isolate the endpoints and then manage those threats going forward, Bakshi explains.

“Some of these systems are running in the background of your endpoint,” he says. “There’s not much to do other than installing and enabling it.”

Next-Gen Firewalls Rely on AI for Analysis and Communication

Next-generation firewalls incorporate AI technologies such as machine learning to analyze traffic and develop security policies. Firewalls also rely on AI assistants for troubleshooting, help with policy identification and reporting, and lifecycle management.

Chatbots provide a way for school IT leaders to manage firewalls.

“Our solutions enable AI chatbots to communicate with these systems and make their operations much simpler,” Bakshi says. “They're taking away the complexity from the IT security teams.”

To learn more about AI in cybersecurity for K–12, IT professionals can consult organizations such as CoSN, the Multi-State Information Sharing and Analysis Center (MS-ISAC) and the K12 Security Information eXchange (K12 SIX).

“AI is eventually, in the next few years, going to greatly enhance the capabilities that school districts have to protect themselves against cyberthreats, because you can do more with less resources of human capital,” Waugh says.

UP NEXT: NPUs help optimize school devices for artificial intelligence.