The Cube: AI-enhanced Cybersecurity
- Oct 1, 2025
- 4 min read
As a Cube insider, you'll get access to interesting new trends, what we think about them and how you can benefit.
New Trend: Traditional Cybersecurity vs. AI-Enhanced Cybersecurity
Is your data safe from cyberattacks in the age of AI? Traditional cybersecurity relies heavily on predefined rules, static signatures, and manual oversight to detect and respond to threats with firewalls, intrusion detection systems (IDS), and antivirus software that operate based on known threat patterns and require frequent updates. Their tools are only effective against known vulnerabilities, but they struggle with identifying novel attacks that use social engineering tactics.
AI-enhanced cybersecurity introduces adaptive and predictive capabilities by leveraging machine learning models to detect anomalies and evolving threat patterns in real time. Instead of depending on static rules, AI systems learn from large volumes of network data and user behavior to identify suspicious activities that deviate from established norms. It enables faster detection of zero-day threats, advanced persistent threats (APTs), and insider attacks. Traditional systems often falter under the volume of modern data traffic, but AI can process and analyze vast datasets rapidly, flagging potential threats faster than human analysts. AI-enhanced tools can automate incident response, reducing the time between detection and mitigation.
Ashish Khana provides a good argument as to why AI systems belong in the cybersecurity space in her article: “AI’s ability to analyze vast datasets effectively has led to the development of tactical techniques and procedures for threat intelligence, such as automated attack pattern recognition and threat hunting… By leveraging AI’s prowess, analysts can focus on more strategic aspects of cybersecurity, optimizing their efforts and strengthening the overall security posture of an organization.” While it’s clear that AI-enhanced cybersecurity systems are the best solutions in our world today, they can bring plenty of benefits and challenges to your company.
New Insight: The Benefits and Risks of AI-Cybersecurity
If you are considering a new AI-enhanced cybersecurity system, you should know about the benefits and risks of trusting an AI system with your business’s or organization’s data. While you can hire cybersecurity professionals who have experience working with AI systems, there is also plenty of information for you to know about managing these systems other than following guidelines and policies for AI-powered systems.
AI can detect vulnerabilities in network traffic by analyzing patterns in network traffic data.
AI systems can identify potential threats and alert cybersecurity. It can even analyze large amounts of data for potential threats. It’s particularly useful in identifying threats that might not be immediately obvious to human analysts.
AI in cybersecurity allows for automating routine tasks to be less time-consuming. For example, it can be used to automatically patch and update systems, freeing up cybersecurity professionals to focus on more complex tasks.
It makes generating reports and alerts easier in providing valuable information to make better cybersecurity decisions. Improving the speed and accuracy of threat detection and response will allow AI to reduce the impact of cyberattacks.
AI can also improve the efficiency of cybersecurity operations, freeing up valuable time and resources for other tasks.
AI’s great potential can also come with great risks and challenges. Hackers may use AI to develop more sophisticated cyber threats, such as generating realistic phishing emails, deploying malware, or creating convincing deepfake videos. As AI becomes more advanced, hackers are more likely to find new and creative strategies to use it to their own advantage. AI systems can only function by the data they are trained on. If that data is biased or incomplete, the AI system will produce biased results. It can be an issue when it comes to facial recognition, which can lead to false identification and discriminatory outcomes. There’s also the possibility of AI systems making decisions without human oversight. While automation is useful in different areas, it’s important to ensure that humans are still involved in the decision-making process to keep track of an AI system so it appropriately responds to a perceived threat.
While these risks may seem alarming, they shouldn’t deter us from utilizing its potential. According to Chuck Brooks in his article on AI in Cybersecurity, he states, “The most effective approaches for preventing and detecting spoofs and hacks entail always being vigilant. Avoid clicking on links in emails or websites without first checking the sender’s identity. Install antivirus and AI-enabled spoof detection software, and consider using packet filtering capabilities provided by multiple manufacturers. In addition, with AI-enabled attacks expanding, Zero Trust identity-centric security is important for recognizing identity access and management as the point of greatest marginal risk reduction.” By improving the speed and accuracy of threat detection and incident response, using AI can help reduce the impact of cyberattacks and malicious activities and improve the efficiency of cybersecurity operations.
New Action: How to Utilize AL Systems in the Digital Age
As businesses and organizations depend on technology and information more and more for their operations, it makes them more vulnerable to cyberattacks. Of course, AI has been helpful for them to protect their data and information from being stolen and other manipulative events. It’s important to monitor AI and keep in charge of its decision-making process.
While traditional cybersecurity is programmed to detect and respond to threats, AI cybersecurity has the tools to identify and respond to anomalies and evolving threat patterns over time.
AI-enhanced systems have plenty of benefits, such as analyzing traffic data for potential threats that no human analysts or cyberprofessionals may notice.
There is the risk of hackers utilizing AI to develop more sophisticated cyber threats for their own advantage.
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