Areas where AI cybersecurity is invested
The area where most investment is being made is cloud security. Artificial intelligence has gained a lot of importance in cloud security as public cloud providers introduce new capabilities to help organizations with their security structure. Enterprises are increasingly moving to the cloud to take advantage of cloud computing. Nevertheless, security teams face challenges such as misconfigurations and skills shortages. Security responsibility in the cloud lies with both the provider and the customer, with the latter being responsible for aspects such as identity management, network security and data protection.
Tip for companies
When companies are hit by an attack and experience business interruption, cyber insurance will cover at least some of the damage and provide emergency services. Capterra found that 48% of respondents said their company has cyber insurance. Cyber insurance covers many crimes, including ransomware, cyber extortion, and social engineering attacks, and is a necessity for businesses.
How are AI-powered security systems an improvement over traditional cybersecurity tools? We'll find out in the next section by looking at the responses of employees whose companies have invested in such solutions.
Different approach between traditional and AI-driven cybersecurity
Originally, traditional cybersecurity relies on signature code systems. These tools have a database that collects signatures of malicious code that correspond to known threats. Based on this information, they are able to analyze and detect suspicious traffic on computer networks and issue a security alert.
While traditional tools are based on "static" protection, reacting only philippines telegram data to a known threat to the system, tools with AI are based on a "dynamic" detection approach. Their features increase the security of networks by detecting patterns associated with known threats and, above all, by identifying new threats. In particular, using the principle of machine learning, where the AI is trained with data corresponding to the usual activity of the network to be defended, the AI can detect and report potentially abnormal activities.
Because AI can read from data how an organization's systems and users typically behave, it can detect unusual actions. Whether it's an unrecognized connection to a device or an unusual influx of traffic on a website, AI-driven systems are able to detect these impacts and quickly issue alerts. Behavioral analysis is chosen by 49% of respondents as the most important benefit of AI over traditional methods.
In particular, using machine learning algorithms, AI tools can analyze large amounts of data in real time, allowing them to more quickly identify patterns that pose a threat to systems. This allows companies to identify potential security issues as soon as they arise, which is a major advantage in the fight against cybercriminals. This advantage is considered particularly important by 48% of companies that use an AI solution.
For 40% of respondents, automation is the third most important benefit of an AI security system. A traditional approach to cybersecurity often requires IT managers to manually analyze the data collected by the tools. This includes processing and sorting alerts, analyzing security logs, and prompting to update the database when a new threat emerges. By automating most of these areas, AI can relieve affected teams of time-consuming tasks.