AI Shields Up: How Companies Turn the Tide With AI in Cybercrime

Gone are the days when personal, health, and business records were stored on paper and tucked away in locked filing cabinets. Now, organizations are embracing digital transformation, moving their sensitive information online, onto servers, and into the cloud.

At First National Technology Solutions (FNTS), our tech experts are dedicated to helping organizations protect their data. With data privacy and federal compliance at the forefront of business concerns, companies face significant challenges in protecting themselves from cyber threats. That’s why staying up to date with the latest security measures is essential.

More organizations are using Artificial Intelligence (AI) to increase their defenses in cybercrime strategies. AI in cybercrime isn't just about mimicking human actions; it's a powerful ally in fighting cyber threats, data breaches, and malicious attacks. From Siri on your iPhone to Google's self-driving cars, AI is reshaping how we protect and interact with the digital world.

The Role of AI in Cybercrime

More organizations are utilizing AI in cybercrime efforts to further protect their systems and data from threats, leaks, and malicious activity. AI is a machine's ability to mimic human function to act. Examples of AI include Apple’s SIRI and Google’s self-driving cars.

By operating machine learning algorithms, AI systems can continuously evolve and adapt to new threats, improving their defensive capabilities. Additionally, AI can automate routine security tasks such as vulnerability assessments and incident response, freeing up skilled professionals to focus on more complex challenges. As cyber threats grow, integrating AI into cybercrime protocols will become increasingly important for safeguarding sensitive information and maintaining organizational integrity.

There are three main types of AI used in cybersecurity: 

1. Supervised learning 
2. Unsupervised learning
3. Reinforcement learning 

Supervised learning involves feeding an AI system labeled data to train it on what is considered normal behavior for a network or system. This allows the AI to identify unusual activity, which could indicate a cyber attack. On the other hand, unsupervised learning involves analyzing large amounts of unlabeled data to find patterns and abnormalities that could signal a security threat. Reinforcement learning combines supervised and unsupervised techniques by providing feedback to the AI when it correctly identifies a potential threat or misidentifies harmless activity.

Why is AI Being Used in Business Industries?

In some cases, AI augments traditional anti-virus protections because business personnel can’t efficiently sift through every malicious event or threat alert. In addition, some businesses have limited IT budgets or critical hardware with vulnerabilities. If data is fed into an AI-infused IT security system, it can proactively take actions to isolate and protect data traffic until a more permanent solution becomes available. Additionally, it’s possible that devices still usually function after being compromised. AI can monitor and investigate traffic in real time to flag potentially harmful traffic based on behavior, source, destination, and function.

How Does Artificial Intelligence Prevent Cyber Threats?

AI learns what is “normal” to create a baseline and will take automated actions that deviate from the baseline. AI makes decisions based on pre-programmed parameters and decision-making intelligence algorithms in conjunction with a vast amount of data that has been examined to provide a history of previously seen events and actions. This allows the AI to learn and evolve. Depending on the threshold setup when the AI system is implemented, the actions can alert key personnel by immediately isolating and quarantining a device or network segment or deploying new rules to firewalls or other equipment.

AI can guard against hackers by blocking traffic based on several factors, including geographic location, application, and user. Traffic can be blocked for varying amounts of time, depending on how abnormal and malicious it is compared to the baseline and the intelligence gathered in the AI’s cloud processing engine. If ransomware is released, the abnormal activity seen by an unknown file or application will be immediately analyzed and quarantined if it deviates from what is known to be expected. 

What Does AI Do Once A Threat is Detected?

As of 2024, according to IBM Data Breach Reports, the average time for an organization to identify and contain a data breach has unfortunately increased compared to past years. On average, it takes around 204 days to identify a breach and an additional 73 days to contain it, totaling 277 days. This extended period highlights the significant lag in detection and response, allowing for substantial damage during this window​. Artificial Intelligence can take immediate actions instead of initiating action after the fact. AI can self-heal or correct actions by quarantining a threat and removing it from a network to prevent data from being leaked.

Additionally, AI can take vulnerability scan results and exploit information to move assets to a “safe zone” to prevent infection. Different security policies can also be applied to patch devices before an official patch is released virtually. Lastly, if abnormal activity is seen before execution, AI can wipe the activity and all preceding actions from the machine. Essentially, every action is recorded and monitored for playback, if necessary. One of the most widely implemented AI areas is user behavioral analytics tied to identity management. AI can immediately block an action or alert personnel if abnormal activities are seen.

As with any technology, there can be some false positives. Humans can be highly unpredictable. If the traffic AI uses to create its normal baseline is skewed in any way, it might need to be corrected or adjusted on the fly, but over time, the accuracy increases. Today’s AI solutions are much more intelligent due to the algorithm tuning, available data points, and processing power made available by cloud computing.

To seize the benefits of AI and machine learning, an organization must implement in-depth defense and multi-layer security programs and have an executive-sponsored information security function. Without those, machine learning and AI would be under-utilized tools that don’t have the opportunity to take a security program to the next level. Also, remember that machine learning and AI aren’t a one-size-fits-all solution. 

AI: Your Strategic Ally in Cybersecurity

In the dynamic world of cybersecurity, AI in cybercrime is essential for combating rising cyber threats. At FNTS, we use AI techniques such as supervised, unsupervised, and reinforcement learning to secure your digital operations proactively. AI not only improves technology—it automates key security processes, ensuring continuous protection of your sensitive data as cyber threats evolve. Consider adding an extra layer of security by exploring FNTS’s options in consulting and professional services and cyber incident response planning.

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(Editor's Note: This article was originally published in November 2017 and was recently updated.)