Robotic defender: how is AI applied in cybersecurity? Robotic defender: how is AI applied in cybersecurity?

Today, the number and intensity of cyber-attacks is increasing, so that existing security systems do not always cope with hacking attacks. The number of specialists in the field is also insufficient, so companies automate cybersecurity using AI. Let’s understand how artificial intelligence protects data and which security systems have already been created.

AI-based protection systems

According to a study carried oud by the consulting company Nemertes Research, an organization needs about 39 days to detect an attack and react to it.

The reaction rate depends on how much the cyber security system is automated. Therefore, using machine learning algorithms, companies can reduce the time needed to detect an attack to one hour or several minutes.

ML algorithms are also capable of analyzing large amounts of data, which takes a lot of time if processed manually. In addition, by introducing AI into cybersecurity systems, companies no longer need a large number of analysts. This results in the reduction of costs.

Artificial intelligence can improve cybersecurity in several ways.

Strategies for dealing with attacks

Special machine learning algorithms are able to automatically analyze successful hacker attacks. Based on the information collected, they generate a strategy to combat future hacks.

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Prediction of possible attacks

When analyzing previous hacks, algorithms can also predict potential attacks. The available data will help to determine the possible time of hacking, so that the company will be able to prepare for cyber-attack and prevent it at the initial stage.

Fight against previously unknown attacks

Automatic cyber security systems are able to protect the database from previously unknown attacks, the so-called zero-day attacks.

It is possible due to the fact that the algorithms identify potentially harmful or dangerous actions in the system and detect any suspicious activity.

Cyber risk level analysis

The level of cyber risk of the company depends on many factors, including the availability of systems without ‘patches’ and unprotected ports. An important role is also played by phishing messages, password strength and the amount of unencrypted data.

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By analyzing all of these factors, AI can determine the risk level of the system at a certain time period.

AI examples in cyber security

AI2

Researchers of the Computer Science and Artificial Intelligence Laboratory at MIT, together with the PatternEx startup, developed the AI2 cybersecurity system.

According to the developers, the system based on the machine learning technology is able to identify 85% of attacks.

AI2 detects anomalies and detects suspicious activity on its own. After that, the results are provided to experts for further analysis – they manually mark the malicious activity. Then these activities are loaded into a training model. In such a way, basing on this information, a new training cycle is created, and the system becomes smarter.

In addition, manual analysis of information is simplified: experts consider about 30-40 suspicious activities per day instead of 200.

Booz Allen Hamilton

A large US consulting company, Booz Allen Hamilton, has already implemented AI in its work to increase cyber security.

The system detects weak spots in the networks and informs experts about them. According to the company representatives, AI helps to cope with alert fatigue. A problem occurs when the number of alarms is so large that experts begin to respond more slowly to them.

Artificial intelligence in cybersecurity helps to speed up the reaction to viruses, predict serious information leaks and prevent attacks. All this minimizes possible damage to the company and contributes to high-quality data protection.

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