Cyber ​​criminals are attacking various public and private institutions and telecommunication sector using advanced technology. Threats of cyber attacks known as Advanced Persistent Threats (APTs) cannot be detected by conventional detection methods but can be detected by machine learning technologies. And so in the first half of the year, Kaspersky's machine learning technology increased the detection rate of APT cyberattack threats by 25 percent. In a press release on Monday, the cyber security company Kaspersky reported this information.

cyber attack

According to Kaspersky's Global Research and Analysis Team (GREAT), Kaspersky's machine learning models can quickly identify cyber attacks that conventional detection methods cannot detect. Cyber ​​attack threats can be easily identified as machine learning models are regularly fed with new information.

In this regard, Amin Hasbini, head of the Meta Research Center of Kaspersky's Global Research and Analysis Team, said, 'The results were better than we expected. This technology has improved detection accuracy and is helping businesses stay ahead of cyber threats through proactive defense strategies.'