Artificial Intelligence as a Cybersecurity Tool for Small and Medium Businesses

Cybersecurity is a matter of increased concern for most business owners since there is not much that a traditional firewall can do to prevent today’s outside threats. The only way to maintain control over new unknown risks is to take a proactive approach and move from a conventional firewall to a smarter form of defense, that is, using artificial intelligence (AI) solutions.

By understanding the objectives of attacks and their consequences, as a business leader, you can minimize potential, benefit from your cybersecurity efforts, and even prevent future attacks. Thus, in the post, we will talk about the reasons why small and medium businesses (SMB) are the easy target for cybercriminals, how effective AI is in protecting the business, and the solutions it currently offers.


  1. Cybercrime in small and medium businesses. Statistics.
  2. Top 5 reasons cybercriminals attack SMB segment.
  3. AI-based solutions against cyberattacks.
  4. Conclusion. 

Cybercrime in small and medium businesses (SMB). Statistics. 

Cyberattacks on SMB are today becoming more frequent, targeted, and complex. 

According to the Data Breach Investigations Report by Verizon, 43% of cybersecurity breach victims are SMB, but only 14% are willing to defend themselves.

Further, according to Fundera, the most common types of attacks on SMB include:

  • phishing and social engineering attacks (62% of companies experienced it),
  • malicious code and botnets (59%),
  • denial of service attacks (51%). 

However, more than half of SMB don’t even have a plan to respond to cyberattacks on their companies. Insurance Bee reports that 54% of small businesses have not taken the time to actively plan in the event of a potential cyberattack. To make matters worse, 83% do not have the beside allocated funds to deal with the consequences of one of them.

As a result, the crucial question arises – why are the cybercriminals so intense to attack the SMB, rather than scaled enterprises? Is it so beneficial to affect this segment? Or just the quick way to get profit? Let’s explore more precisely. 

Top 5 reasons cybercriminals attack SMB segment

  1. Lack of IT department

    SMB rarely have a separate IT department or technological reliable partner. This means that the devices, networks, websites, and servers used in business are hardly ultramodern. Software updates are chaotic and unplanned. And, in case of an attack, there is no way to repel it.

    Read also: “IT Outstaffing Is A Bringing In Returns Engagement Model

  2. Unsecured networks and systems

    SMB usually have much simpler networks than large businesses. A big-scaled organization may include a separate division or even a couple of server rooms for connection between hundreds of computers and devices designed for various tasks. Small businesses, if any, have only one server and a few computers or devices with minimal security that can easily be breached.

    Image source: pexels
  3. The use of third-party software, websites, SaaS, PaaS

    Small businesses usually leverage third-party software packages, websites, SaaS, or PaaS to meet the challenges of serving their digital needs over the Internet. On the contrary, large businesses mostly use their own specialists to solve IT problems. Meanwhile, using third parties make it easier for hackers to orchestrate an attack on these services in order to use them as a gateway to the company’s network of computers.

  4. Mistaken position

    There is no need to waste time examining and preparing detailed specifications.Often, small business owners mistakenly believe that the likelihood of a hacker attack is minimal because their organizations have few staff or low turnover. Therefore, they do not deal with IT security issues. That is a mistaken assumption and completely unfounded, since modern hacker attacks are mostly automated. Bots, that are looking for vulnerabilities of all accessible nodes on the Internet, do not choose their targets. Thus, their victims are equally likely to be companies of any scales.

  5. Easy target

    It is more profitable for cybercriminals to hit such an easy target as SMB than to spend time and energy on attacking the protected networks of large companies. Enterprises have more opportunities, finances, and specialists to use the latest IT technologies to protect corporate networks and all company data, than the SMB do.

    However, this does not mean that small businesses cannot be cyber secure. In fact, this task is not as difficult as it might seem. Getting to know the cybersecurity solutions can be a good starting point for creating a working plan towards protecting the business. Further in the article, we will concentrate our attention on how AI-powered cybersecurity can provide greater safety to your business.

AI-based solutions for cybersecurity

The construction of protection depends on the budget, resources, business processes, and threat models of the company. To ensure maximally high protection, we recommend implementing a complex cybersecurity solution. That is perimeter protection, sandbox, network monitoring, Threat Intelligence, detection and response services from an Integrator, NTA (network traffic analysis), SIEM (security information and event management), antivirus. However, only after defining the goals and outputs of the business, you should select the most appropriate cybersecurity services.


The methods against cyberattacks can be divided into external ones, which are aimed at analyzing user actions and events outside the protective perimeter of the organization, and internal ones, aimed at analyzing events and user behavior within the organization. Let’s take a closer look at the major solutions that successfully apply AI technology. 

  1. User and Entity Behavior Analytics (UEBA)

    That is the analysis of user behavior and other entities. Thanks to well-tuned algorithms for cluster and statistical analysis, modern UEBA solutions accurately form user and asset behavioral baseline. After that, classification and regression analysis algorithms look for anomalies in the built profiles of behavior. On their basis the classical rules of correlation signal possible incidents. In other words, AI-based analysis can provide your business with detecting anomalies in employees/clients’ systems, and in a timely manner prevent them.

    To clarify, let’s take a simple example of the activity of an accountant. The analysis shows, for instance, that the employee is active from 10 am to 7 pm and exchanges information with approximately the same contacts, uses a certain set of resources. The AI ​​system is patterning the behavior of this account. One day, the system finds that the employee’s account suddenly became active at 2 am, requesting information from an unusual source for it. This is already an anomaly, suspicious behavior that is recorded by the system. Further, it clarifies the reason for the activity of the account and then either blocks the action (if what is happening results from a hack) or not (after all; it is possible that the accountant is making an urgent report, for the preparation of which he needs additional data). 

    Similarly, the actions of the business clients can be analyzed, for example, in a bank, insurance or other industry-specific companies. If the system notices the unusual behavior for a certain user, such as transferring an extensive amount of funds to contact not from the trusted list, the operation may be blocked.

  2. Anti-Fraud System

    Banking and financial organizations are actively using AI-based fraud monitoring systems to effectively detect and prevent fraud in businesses concerning credit cards, accounting, etc. These are systems that evaluate online financial transactions for signs of fraud. They are based on machine learning technology, both with a teacher (supervised learning) and without it (unsupervised learning).

    Anti-fraud solutions allow not only to prevent fraudulent transactions but also to manage risks. Check out our recent article “How Can Machine Learning Help in Fraud Detection?” to find more about the topic. 

  3. Threat Intelligence

    Here we imply active protection with the search for information about possible threats. This method makes it possible to find the threat to the business before it entails damage. The analysts collect, analyze and process information from data streams containing indicators of compromise. Those are the signs by which a potential threat can be identified, such as hashes of malicious files, IP addresses, and domains associated with criminal activity.

    This technique improves both the quality and the speed of incident response. Better to use in conjunction with other information security processes, including risk and vulnerability management, and fraud detection.

  4. Threat Hunting

    Hunting for cyber threats is a proactive approach to countering them. Instead of reacting to an incident that has already happened, Threat Hunting offers to identify cybercrime risks with the help of real-time telemetry. It allows you to get all the necessary data for in-depth analysis of potential threats.

    We can also describe this technique as simulating an attack. An information security expert examines the methods used by intruders to penetrate the corporate network, as well as how a certain attack proceeds. After, he draws conclusions about where penetration or infection can take place, and implements preventive measures. Thus, Threat Hunting makes it possible to prevent complex threats.

  5. Anti-APT (Advanced Persistent Threat)

    An APT is a type of targeted attack. Here cybercriminals actively use sophisticated attacks aimed at penetrating a company’s infrastructure. The goals that cybercriminals pursue in an APT attack are often finances, data theft, reputation, and infrastructure destruction. As part of APT attacks, there are various leveraged tools, among which are phishing, exploits, botnets, Trojans, post-update backdoors.

    With AI technology, professional engineers are able to quickly detect the presence of an attacker on the network and recreate the complete picture of an attack for detailed investigation. To dive deeper, the engineers conduct the process of attack discovery with an in-depth network traffic analysis (NTA) system. It gives an understanding of what is happening on the network, detects the activity of intruders even in encrypted traffic, and further helps in investigations. Like wisely, AI-based SIEM (security information and event management) systems are being deployed to aggregate and analyze events in the company’s IT infrastructure.


Cybersecurity is an integral part of the modern information world. It penetrates almost all its spheres, starting with simple data protection, combating network fraud, and ending with multistage systems of corporate information security, which means combating botnets, countering fakes, etc. 

Following the mentioned information, we got a clear vision that it’s time for SMB to wake up, stop waging a lost and invisible battle against malware and cyber threats. Systems like the ones described above are badly needed by many industrial businesses, in particular, insurance, banking, and financial companies, and a number of critical government organizations.

FreySoft is ready to offer proven AI-based cybersecurity consulting services and support. We are a team of specialists providing relevant services that meet all the requirements of modern business and ensure information security.

If you have unanswered questions, please feel free to contact us within a request or via e-mail

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