How AI and Machine Learning are Changing the Game for Small Business Cybersecurity Programs

BY: JEFF WILLIAMS

When I was younger, losing power over the summer was so common it was almost a tradition. The heat or a sudden storm would plunge the house into darkness. We’d fumble around for candles or flashlights, throw open windows, and share stories by the dim light. I used to look forward to these events. But for my kids today, a power outage is a digital disaster. The internet goes down, streaming stops, and suddenly, the battery life on their devices becomes the top priority.

This heavy reliance on technology and connectivity isn’t limited to our homes; it’s also evident in the business world. The recent Microsoft outage highlighted our dependence on interconnectivity and underscored the critical importance of cybersecurity and risk management.

Maintaining a robust cyber environment is a constant challenge. It requires significant time and effort to assess current risks, maintain a security program, and monitor its effectiveness. This task is particularly daunting for small to medium-sized businesses with limited resources that often rely on external vendors for tech support. Thankfully, advancements in Artificial Intelligence (AI), particularly in machine learning, offer a lifeline. By integrating AI into cybersecurity solutions, organizations can enhance their security programs while reducing the time and resources invested.

Here are a few ways AI is transforming cybersecurity, especially for small to mid-sized companies:

Predictive Analysis
A healthy cyber environment depends on vast amounts of data, which must be collected, filtered, and analyzed—an endeavor that consumes significant time and resources. AI can automate much of this process and identify patterns within a business to forecast potential attack vectors and proactively strengthen defenses.

• Example: Webroot's Business Endpoint Protection uses AI for predictive threat analytics. By continuously analyzing threat data and identifying trends, Webroot provides actionable insights and recommendations, helping small businesses fortify their defenses against emerging threats.

Proactive Threat Detection
Traditional cybersecurity measures, like antivirus software, rely on signature-based detection to identify known threats. These signatures require frequent updates, leaving organizations vulnerable in the interim. AI-powered systems, however, use machine learning to analyze patterns and behaviors, detecting anomalies that could indicate new or unknown threats.

• Example: Huntress is an AI-driven cybersecurity tool designed for small businesses. It uses machine learning to monitor endpoints for signs of malicious activity. Learning and understanding "normal" behavior allows the tool to pinpoint deviations in real time and swiftly intervene.

AI can also reduce false positives, which traditional measures often generate in abundance, leading to complacency or fatigue. AI systems can compare data from various sources to minimize false positives, ensuring no real threat goes unnoticed.

• Example: Fortinet's FortiAI correlates data from multiple sources and eliminates false positives by applying machine learning to contextualize alerts, allowing small business security teams to focus on genuine threats.

Cost-Effective Speed and Efficiency
For small to medium-sized organizations, time and resources are often scarce. Sifting through vast amounts of data can be a full-time job for multiple individuals. AI processes large datasets quickly, identifying potential threats faster and allowing quicker responses.

• Example: CylancePROTECT provides endpoint security using AI. By analyzing large volumes of security data and correlating it with global threat intelligence, it reduces the time needed to identify and understand threats, accelerating response times without extensive in-house expertise.

Automated Response and Remediation
Detecting a cyber incident is only half the battle. Proper handling is crucial, yet incident response plans often lack detail, and critical steps may be missed. AI can automate much of the response and remediation processes, executing predefined actions to contain and neutralize threats, reducing the need for human intervention and minimizing response delays.

• Example: Trend Micro's Worry-Free Services Suite uses AI to automate incident response workflows. When a threat is detected, it can automatically isolate affected systems, block malicious IP addresses, and initiate forensic investigations, reducing response times and mitigating damage.

Enhanced User Authentication
Traditional user authentication often relies on knowing the correct username and password, ignoring the user's location and behavior. AI-driven authentication systems analyze user behavior, device characteristics, biometric data, and location to verify identities more accurately.

• Example: Duo Security by Cisco uses AI to analyze user behavior and device characteristics, providing secure authentication. This continuous process makes it difficult for attackers to impersonate legitimate users, adding a layer of security beyond traditional methods.

Enhancing Employee Awareness and Behavior
The nature of routine work can lead to employees overlooking small changes, such as an unusual email address or a questionable-appearing website, that could indicate risk. AI enhances awareness by notifying users of changes and analyzing work patterns to identify risky behaviors, providing personalized insights and training to improve cybersecurity hygiene.

• Example: Microsoft Viva Insights uses AI to analyze workplace data and offer recommendations to improve productivity and well-being. For small businesses, it identifies risky behaviors, such as sharing sensitive information insecurely, and provides tailored insights and training to help employees adopt safer practices.

While AI in cybersecurity is still a developing technology, its impact on how small businesses protect themselves is undeniable. As cyber threats continue to evolve, AI’s role in cybersecurity will become increasingly critical. However, AI is not a silver bullet. Organizations must continually analyze their security programs, evaluate risks, and assess the performance of their tools, including AI solutions where applicable.

By leveraging AI, small to mid-sized businesses can enhance their cybersecurity measures, ensuring they stay one step ahead of potential threats while optimizing their resources effectively. Contact MMTC to see how we can help keep your business cyber secure.

MEET OUR EXPERT: Jeff Williams, Program Manager, Cybersecurity
Jeff Williams leads The Center's efforts to educate and equip small and medium-sized manufacturers to guard against the growing threat of cyber-attacks. One of his main areas of focus relates to the cybersecurity requirements outlined in NIST Special Publication 800-171, designed to protect the information security systems of contractors working with the Department of Defense. In addition to serving Michigan’s manufacturing community, Jeff also is involved with training other Manufacturing Extension Partnership (MEP) centers across the U.S. This effort will enable those centers to provide cybersecurity services to manufacturers in their states.

Since 1991, the Michigan Manufacturing Technology Center has assisted Michigan’s small and medium-sized businesses to successfully compete and grow. Through personalized services designed to meet the needs of clients, we develop more effective business leaders, drive product and process innovation, promote company-wide operational excellence and foster creative strategies for business growth and greater profitability. Find us at www.the-center.org.