Based on ML technology, the Cloud ML for Android ensures immediate proactive identification of advanced and earlier unknown malware
Kaspersky Lab, a global cybersecurity and anti-virus brand, announced that its Kaspersky Internet Security for Android has been strengthened with a feature based on machine learning (ML).
The solution is updated with a latest feature – Cloud ML for Android, for combating the growing malware landscape. The technology allows the product to give an even faster reaction to unknown threats and keeps the number of false positives at the lowest rates.
Based on ML technology, the new feature ensures immediate proactive identification of advanced and earlier unknown malware, to reduce the risks of mobile devices being exposed to cyberattacks. In order to achieve this, the malicious applications which may have been downloaded on a mobile handset are detected even before they launch.
Uses ML algorithms for accurate verdict
If a user downloads an application on mobile device, the latest feature uses ML algorithms from the cloud that have been trained on millions of malware samples. The applied method assesses thousands of different application parameters such as requested permissions or entry points – in less than a second, and immediately gives an accurate verdict.
In case, if an application turns out to be a modified or specific type of malware that has not been previously identified, the Cloud ML for Android will recognise it as malicious, based on typical parameters that resemble with already known threats.
Commenting on the development, Timur Biyachuev, Vice President, Threat Research at Kaspersky Lab, said, “According to recent Kaspersky Lab research the number of mobile malware attacks doubled in 2018, as cybercriminals invent new ways to create and distribute malware. Obviously, anti-malware technologies need to keep up.”
“Our mobile product, Kaspersky Internet Security for Android, already protects millions of users from advanced and yet previously unknown threats. This new component improves the accuracy and speed at which these threats are detected, making mobile experiences better and more secure,” he added.